Distributed Systems

Conference Papers and Demos


  1. Driving Towards Efficiency: Adaptive Resource-aware Clustered Federated Learning in Vehicular Networks (, , , and ), In The 22nd Mediterranean Communication and Computer Networking Conference (MedComNet’24)., IEEE, .

    Abstract

    Guaranteeing precise perception for fully autonomous driving in diverse driving conditions requires continuous improvement and training. In vehicular networks, federated learning (FL) facilitates this by enabling model training without sharing raw sensory data. As an extension, clustered FL reduces communication overhead and aligns well with the dynamic nature of these networks. However, current literature on this topic does not consider critical dimensions of FL, including (1) the correlation between perception performance and the networking overhead, (2) the limited vehicle storage, (3) the need for training with freshly captured data, and (4) the impact of non-IID data and varying traffic densities. To fill these research gaps, we introduce AR-CFL, an Adaptive Resource-aware Clustered Federated Learning framework. AR-CFL utilizes clustered FL to collectively model the environment of connected vehicles, integrating models from all vehicles and ensuring universal accessibility to the refined model. AR-CFL dynamically enhances system efficiency by adaptively adjusting the number of clusters and specific in-cluster participant selection strategies. Using AR-CFL, we systematically study the scenario of online car detection model training on non-IID data across varied conditions. The evaluation results highlight the robust detection performance exhibited by the trained model employing the clustered FL approach, despite the constraints posed by limited vehicle storage capacity. Furthermore, our investigation unveils superior training performance with clustered FL in comparison to specific classical FL scenarios, increasing the training efficiency in terms of participating nodes by up to 25% and reducing cellular communication by 33%.


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  2. In-Network Management of Parallel Data Streams over Programmable Data Planes ( and ), In Proceedings of the 23rd International Federation for Information Processing (IFIP) Networking Conference (IFIP NETWORKING 2024), IEEE, .

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  3. Analog In-Network Computing through Memristor-based Match-Compute Processing (, , , and ), In Proceedings of the 43rd International Conference on Computer Communications (INFOCOM 2024), IEEE, .

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  4. dAQM: Derivative-based Active Queue Management (, and ), In Proceedings of the 23rd IFIP Networking Conference (NETWORKING 2024), IFIP, .

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  5. Adaptive In-Network Queue Management using Derivatives of Sojourn Time and Buffer Size (, and ), In Proceedings of the 37th Network Operations and Management Symposium (NOMS 2024), IEEE, .

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  6. APP-CEP: Adaptive Pattern-level Privacy Protection in Complex Event Processing Systems (, , and ), In The 10th International Conference on Information Systems Security and Privacy (ICISSP 2024)., SCITEPRESS, .

    Abstract

    Although privacy-preserving mechanisms endeavor to safeguard sensitive information at the attribute level, detected event patterns can still disclose privacy-sensitive knowledge in distributed complex event processing systems (DCEP). Events might not be inherently sensitive, but their aggregation into a pattern could still breach privacy. In this paper, we study in the context of APP-CEP the problem of integrating pattern-level privacy in event-based systems by selective assignment of obfuscation techniques to conceal private information. Compared to state-of-the-art techniques, we seek to enforce privacy independent of the actual events in streams. To support this, we acquire queries and privacy requirements using CEP-like patterns. The protection of privacy is accomplished through generating pattern dependency graphs, leading to dynamically appointing those techniques that have no consequences on detecting other sensitive patterns, as well as non-sensitive patterns required to provide acceptable Quality of Service. Besides, we model the knowledge that might be possessed by potential adversaries to violate privacy and its impacts on the obfuscation procedure. We assessed the performance of APP-CEP in a real-world scenario involving an online retailer’s transactions. Our evaluation results demonstrate that APP-CEP successfully provides a privacy-utility trade-off. Modeling the background knowledge also effectively prevents adversaries from realizing the modifications in the input streams.


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  7. Memristor-based Network Switching Architecture for Energy Efficient Cognitive Computational Models ( and ), In Proceedings of the 18th International Symposium on Nanoscale Architectures (NanoArch 2023), ACM, .

    Abstract

    The Internet makes use of high performance network switches in order to route network traffic from end users to servers. Despite line-rate performance, the current switches consume huge energy and cannot support more expressive learning models, like cognitive functions using neuromorphic computations. The major reason is the use of transistors in the underlying Ternary Content-Addressable Memory (TCAM) which is volatile and supports digital computations only. These shortcomings can be bypassed by developing network memories building on novel components, like Memristors, due to their nonvolatile, nanoscale and analog storage/processing characteristics. In this paper, we propose the use of a novel memristor-based Probabilistic Associative Memory, PAmM, which provides both digital (deterministic) and analog (probabilistic) outputs for supporting cognitive computational models in network switches. The traditional digital operations can be supported by a memristor-based energy efficient TCAM, called TCAmMCogniGron. Building on PAmM and TCAmMCogniGron, we propose a novel network switching architecture and analyze its energy efficiency over the experimental dataset of a Nb-doped SrTiO3 memristive device. The results show that the proposed network switching architecture consumes only 0.01 fJ/bit/cell energy for analog compute operations which is at least 50 times less than the digital operations.


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  8. The Future is Analog: Energy-Efficient Cognitive Network Functions over Memristor-Based Analog Computations ( and ), In Proceedings of the 22nd ACM SIGCOMM Workshop on Hot Topics in Networks (HotNets 2023), ACM, .

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    Current network functions build heavily on fixed programmed rules and lack capacity to support more expressive learning models, e.g. brain-inspired Cognitive computational models using neuromorphic computations. The major reason for this shortcoming is the huge energy consumption and limitation in expressiveness by the underlying TCAM-based digital packet processors. In this research, we show that recent emerging technologies from the analog domain have a high potential in supporting network functions with energy efficiency and more expressiveness, so called cognitive functions. We propose an analog packet processing architecture building on a novel technology named Memristors. We develop a novel analog match-action memory called Probabilistic Content-Addressable Memory (pCAM) for supporting deterministic and probabilistic match functions. We develop the programming abstractions and show the support of pCAM for an active queue management-based analog network function. The analysis over an experimental dataset of a memristor chip showed only 0.01 fJ/bit/cell of energy consumption for corresponding analog computations which is 50 times less than digital computations.


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  9. PAmM: Memristor-based Probabilistic Associative Memory for Neuromorphic Network Functions (, , and ), In Proceedings of the Non-Volatile Memory Technology Symposium (NVMTS 2023), IEEE, .

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  10. Towards Pattern-Level Privacy Protection in Distributed Complex Event Processing (, and ), In The 17th ACM International Conference on Distributed and Event-Based Systems (DEBS 2023), ACM press, .

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    In event processing systems, detected event patterns can reveal privacy-sensitive information. In this paper, we propose and discuss how to integrate pattern-level privacy protection in event-based systems. Compared to state-of-the-art approaches, we aim to enforce privacy independent of the particularities of specific operators. We accomplish this by supporting the flexible integration of multiple obfuscation techniques and studying deployment strategies for privacy-enforcing mechanisms. Moreover, we share ideas on how to model the adversary’s knowledge to better select appropriate obfuscation techniques for the discussed deployment strategies. Initial results indicate that flexibly choosing obfuscation techniques and deployment strategies is essential to conceal privacy-sensitive event patterns accurately.


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  11. AQuA-CEP: Adaptive Quality-Aware Complex Event Processing in the Internet of Things (, and ), In Proceedings of the 17th ACM International Conference on Distributed and Event-Based Systems (DEBS 2023), ACM press, .

    Abstract

    Sensory data profoundly influences the quality of detected events in a distributed complex event processing system (DCEP). Since each sensor’s status is unstable at runtime, a single sensing assignment is often insufficient to fulfill the consumer’s quality requirements. In this paper, we study in the context of AQuA-CEP the problem of dynamic quality monitoring and adaptation of complex event processing by active integration of suitable data sources. To support this, in AQuA-CEP, queries to detect complex events are supplemented with consumer-definable quality policies that are evaluated and used to autonomously select (or even configure) suitable data sources of the sensing infrastructure. In addition, we studied different forms of expressing quality policies and analyzed how it affects the quality monitoring process. Various modes of evaluating and applying quality-related adaptations and their impacts on correlation efficiency are addressed, too. We assessed the performance of AQuA-CEP in IoT scenarios by utilizing the notion of the quality policy alongside the query processing adaptation using knowledge derived from quality monitoring. The results show that AQuA-CEP can improve the performance of DCEP systems in terms of the quality of results while fulfilling the consumer’s quality requirements. Quality-based adaptation can also increase the network’s lifetime by optimizing the sensor’s energy consumption due to efficient data source selection.


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  12. Towards adaptive quality-aware Complex Event Processing in the Internet of Things (, and ), In Proceedings of the 18th International Conference on Mobility, Sensing and Networking (MSN 2022), IEEE, .

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    This paper investigates how to complement Complex Event Processing (CEP) with dynamic quality monitoring mechanisms and support the dynamic integration of suitable sensory data sources. In the proposed approach, queries to detect complex events are annotated with consumer-definable quality policies that are evaluated and used to autonomously assign (or even configure) suitable data sources of the sensing infrastructure. We present and study different forms of expressing quality policies and explore how they affect the process of quality monitoring including different modes of assessing and applying quality-related adaptations. A performance study in an IoT scenario shows that the proposed mechanisms in supporting quality policy monitoring and adaptively selecting suitable data sources succeed in enhancing the acquired quality of results while fulfilling consumers' quality requirements. We show that the quality-based selection of sensor sources also extends the network's lifetime by optimizing the data sources' energy consumption.


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  13. TCAmMCogniGron: Energy Efficient Memristor-Based TCAM for Match-Action Processing (, , and ), In Proceedings of the 7th International Conference on Rebooting Computing (ICRC 2022), IEEE, .

    Abstract

    The Internet relies heavily on programmable match-action processors for matching network packets against locally available network rules and taking actions, such as forwarding and modification of network packets. This match-action process must be performed at high speed, i.e., commonly within one clock cycle, using a specialized memory unit called Ternary Content Addressable Memory (TCAM). Building on transistor-based CMOS designs, state-of-the-art TCAM architectures have high energy consumption and lack resilient designs for incorporating novel technologies for performing appropriate actions. In this article, we motivate the use of a novel fundamental component, the ‘Memristor’, for the development of TCAM architecture for match-action processing. Memristors can provide energy efficiency, non-volatility and better resource density as compared to transistors. We have proposed a novel memristor-based TCAM architecture called TCAmMCogniGron, built upon the voltage divider principle and requiring only two memristors and five transistors for storage and search operations compared to sixteen transistors in the traditional TCAM architecture. We analyzed its performance over an experimental data set of Nb-doped SrTiO3-based memristor. The analysis of TCAmMCogniGron showed promising power consumption statistics of 16 uW and 1 uW for match and mismatch operations along with twice the improvement in resources density as compared to the traditional architectures.


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  14. Towards Energy Efficient Memristor-based TCAM for Match-Action Processing (, , and ), In Proceedings of the 13th International Green and Sustainable Computing Conference (IGSC 2022), IEEE, .

    Abstract

    Match-action processors play a crucial role of communicating end-users in the Internet by computing network paths and enforcing administrator policies. The computation process uses a specialized memory called Ternary Content Addressable Memory (TCAM) to store processing rules and use header information of network packets to perform a match within a single clock cycle. Currently, TCAM memories consume huge amounts of energy resources due to the use of traditional transistor-based CMOS technology. In this article, we motivate the use of a novel component, the memristor, for the development of a TCAM architecture. Memristors can provide energy efficiency, non-volatility, and better resource density as compared to transistors. We have proposed a novel memristor-based TCAM architecture built upon the voltage divider principle for energy efficient match-action processing. Moreover, we have tested the performance of the memristor-based TCAM architecture using the experimental data of a novel Nb-doped SrTiO3 memristor. Energy analysis of the proposed TCAM architecture for given memristor shows promising power consumption statistics of 16 μW for a match operation and 1 μW for a mismatch operation.


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  15. On the Use of the Conformance and Compliance Keywords During Verification of Business Processes (, and ), In Business Process Management Forum (C. Di Ciccio, R. Dijkman, A. del Río Ortega, S. Rinderle-Ma, eds.), Springer, .

    Abstract

    A wealth of techniques have been developed to help organizations understand their processes, verify correctness against requirements and diagnose potential problems. In general, these verification techniques allow us to check whether a business process conforms or complies with some specification, and each of them is specifically designed to solve a particular business problem at a stage of the BPM lifecycle. However, the terms conformance and compliance are often used as synonyms and their distinct differences in verification goals is blurring. As a result, the terminology used to describe the techniques or the corresponding verification activity does not always match with the precise meaning of the terms as they are defined in the area of verification. Consequently, confusion of these terms may hamper the application of the different techniques and the correct positioning of research. In this position paper, we aim to provide comprehensive definitions and a unified terminology throughout the BPM lifecycle. Moreover, we explore the consequences when these terms are used incorrectly. In doing so, we aim to improve adoption from research to practical applications by clarifying the relation between techniques and the intended verification goals.


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  16. Window-based Parallel Operator Execution with In-Network Computing (, and ), In Proceedings of the 16th ACM International Conference on Distributed and Event-Based Systems, ACM, .

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  17. On the Incremental Reconfiguration of Time-sensitive Networks at Runtime (, , , , and ), In Proceedings of the IFIP Networking Conference., IFIP, .

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  18. Enhancing Flexibility for Dynamic Time-Sensitive Network Configurations (, , , , and ), In Proceedings of the 3rd KuVS Fachgespräch on Network Softwarization, Universität Tübingen, .

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  19. Travel light: state shedding for efficient operator migration (, , and ), In Proceedings of the 16th ACM International Conference on Distributed and Event-Based Systems (DEBS'22), ACM press, .

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  20. CO2 Emission Aware Scheduling for Deep Neural Network Training Workloads (, and ), In 2022 IEEE International Conference on Big Data (Big Data), IEEE, .

    Abstract

    Machine Learning (ML) training is a growing workload in high-performance computing clusters and data centers; furthermore, it is computationally intensive and requires substantial amounts of energy with associated emissions. To the best of our knowledge, previous works in the area of load management have never focused on decreasing the carbon emission of ML training workloads. In this paper, we explore the potential emission reduction achievable by leveraging the iterative nature of the training process as well as the variability of CO 2 signal intensity as coming from the power grid. To this end, we introduce two emission-aware mechanisms to shift the training jobs in time and migrate them between geographical locations. We present experimental results on power and carbon emission of the training process together with delay overheads associated with emission reduction mechanisms, for various, representative, deep neural network models. The results show that following emission signals, one can effectively reduce emissions by an amount that varies from 13% to 57% of the baseline cases. Moreover, the experimental results show that the total delay overhead for applying emission-aware mechanisms multiple times is negligible compared to the jobs’ completion time.


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  21. FA2: Fast, Accurate Autoscaling for Serving Deep Learning Inference with SLA Guarantees (, , , and ), In Proceedings of the 28th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2022), IEEE, .

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  22. PANDA: performance prediction for parallel and dynamic stream processing (, , and ), In Proceedings of the 16th ACM International Conference on Distributed and Event-Based Systems, ACM press, .

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  23. Accelerating the Performance of Data Analytics using Network-centric Processing (), In Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems, ACM, .

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  24. Leveraging Flexibility of Time-Sensitive Networks for dynamic Reconfigurability (, , , , and ), In Proceedings of IFIP Networking 2021, IFIP, .

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  25. Leveraging PIFO Queues for Scheduling in Time-Sensitive Networks (, , , , , and ), In In the Proceedings of the IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN 2021)., IEEE, .

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  26. Workload Distribution on Heterogeneous Platforms ( and ), In 2021 International Conference on Computer, Information and Telecommunication Systems (CITS), volume , .

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  27. P4-CoDel: Experiences on Programmable Data Plane Hardware (, , , , and ), In Proceedings of the IEEE International Conference on Communications (ICC 2021): Next-Generation Networking and Internet Symposium, IEEE, .

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  28. Towards QoE-Driven Optimization of Multi-Dimensional Content Streaming (, , , , , , and ), In Proceedings of the Conference on Networked Systems 2021 (NetSys 2021), European Association of Software Science and Technology, .

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  29. Towards Service-Oriented and Intelligent Microgrids (, and ), In Proceedings of the 3rd International Conference on Applications of Intelligent Systems, Association for Computing Machinery, .

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  30. Predictive Multi-Objective Scheduling with Dynamic Prices and Marginal CO2-Emission Intensities ( and ), In ACM e-Energy 2020, .

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  31. Sustainability Choices when Cooking Pasta (, and ), In ACM e-Energy 2020, .

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  32. Operator as a Service: Stateful Serverless Complex Event Processing (, , , and ), In Proceedings of the 2020 IEEE International Conference on Big Data, IEEE, .

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  33. The Community Structure of Constraint Satisfaction Problems and Its Correlation with Search Time ( and ), In 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI), .

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  34. Microbursts in Software and Hardware-based Traffic Load Generation (, and ), In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, .

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  35. Flexible Content-based Publish/Subscribe over Programmable Data Planes (, , , and ), In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, .

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  36. P4STA: High Performance Packet Timestamping with Programmable Packet Processors (, , , and ), In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, .

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  37. Development of a decision-aid for patients with depression considering treatment options: prediction of treatment response using a data-driven approach (, , , , , , , , , and ), In ISPOR Europe 2019, Copenhagen, Denmark, .

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  38. Predictive CO2-Efficient Scheduling of Hybrid Electric and Thermal Loads ( and ), In 2019 IEEE International Conference on Energy Internet (ICEI), .

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  39. ECiDA: Evolutionary Changes in Data Analysis (, , , , , , , and ), In ICT.Open, Hilversum, The Netherlands, .

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  40. Office Multi-Occupancy Detection using BLE Beacons and Power Meters (, and ), In 2019 IEEE 10th Annual Ubiquitous Computing, Electronics, and Mobile Communication Conference, .

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  41. Temporal Analysis of 911 Emergency Calls Through Time Series Modeling (, , and ), In The International Conference on Advances in Emerging Trends and Technologies, .

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  42. Prediction of Imports of Household Appliances in Ecuador Using LSTM Networks (, , and ), In Conference on Information Technologies and Communication of Ecuador, .

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  43. Robustness of reconfigurable complex systems by a multi-agent simulation: Application on power distribution systems (, , , and ), In 2018 Annual IEEE International Systems Conference (SysCon), .

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  44. Low-power Appliance Recognition using Recurrent Neural Networks (, , and ), In Applications of Intelligent Systems, .

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  45. A remotely piloted aerial system for a faster processing of traffic collisions towards reducing the resulting road congestion (, and ), In , .

    Abstract

    This paper presents the motivation, design, implementation, and testing of a remotely piloted aerial system, designed to facilitate police officers processing traffic collisions. A drone remotely controlled by the police officer can reach faster the accident scene and act as the police officer's eye, ear, and voice in the sky. A complete system prototype has been constructed and tested to validate the proposed system. The results show that the system performance is promising in terms of system functionality, safety, and cost.


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  46. Household CO2-efficient energy management ( and ), In Energy Informatics, Springer, .

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  47. Mining Sequential Patterns for Appliance Usage Prediction (, , , and ), In International Conference on Smart Cities and Green ICT Systems, .

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  48. Modeling 911 emergency events in Cuenca-Ecuador using geo-spatial data (, , and ), In International Conference on Technology Trends, .

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  49. LOD-GF: an integral linked open data generation framework (, , , , , and ), In Conference on Information Technologies and Communication of Ecuador, .

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  50. Automated compliance verification of business processes in Apromore (, and ), In Proceedings of the BPM Demo Track 2017, CEUR Workshop Proceedings (CEUR-WS.org), .

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    This paper presents the integration of two plugins, a declarative process specification generator and a compliance verifier, into the Apromore advanced business process analytics platform. The integrated toolchain has a range of applications of interest to both practitioners and researchers. For example, it can be used in the areas of business process compliance, flexibility and variability. The generator can extract a set of formal specifications that declaratively describe a set of business process variants; whereas the verifier can check whether temporal properties over business process models hold. The verifier can use two different model checker tools: NuSMV2 and NuXMV. These plugins allow business analysts to verify if a newly developed process model adheres to rules and regulations or a specification dictated by existing process model variants.


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  51. Post Summarization of Microblogs of Sporting Events (, , , , and ), In Proceedings of the 26th International Conference on World Wide Web Companion, .

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    Every day 645 million Twitter users generate approximately 58 million tweets. This motivates the question if it is possible to generate a summary of events from this rich set of tweets only. Key challenges in post summarization from microblog posts include circumnavigating spam and conversational posts. In this study, we present a novel technique called lexi-temporal clustering (LTC), which identifies key events. LTC uses k-means clustering and we explore the use of various distance measures for clustering using Euclidean, cosine similarity and Manhattan distance. We collected three original data sets consisting of Twitter microblog posts covering sporting events, consisting of a cricket and two football matches. The match summaries generated by LTC were compared against standard summaries taken from sports sections of various news outlets, which yielded up to 81% precision, 58% recall and 62% F-measure on different data sets. In addition, we also report results of all three variants of the recall-oriented understudy for gisting evaluation (ROUGE) software, a tool which compares and scores automatically generated summaries against standard summaries.


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  52. Prediction of Running Injuries from Training Load: a Machine Learning Approach (, , and ), In International Conference on eHealth, Telemedicine, and Social Medicine, .

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  53. Comparison of Energy Consumption in Wi-Fi and Bluetooth Communication in a Smart Building (, , and ), In IEEE Annual Computing and Communication Workshop and Conference, .

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  54. Power-Based Device Recognition for Occupancy Detection (, , and ), In Service-Oriented Computing - ICSOC 2017 Workshops, volume in press, .

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  55. Semantic web and augmented reality for searching people, events and points of interest within of a university campus (, , and ), In 2017 XLIII Latin American Computer Conference (CLEI), .

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  56. Tv program recommender using user authentication on middleware ginga (, , , and ), In 2017 IEEE Second Ecuador Technical Chapters Meeting (ETCM), .

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  57. Runtime Modifications of Spark Data Processing Pipelines (, , , and ), In 2017 International Conference on Cloud and Autonomic Computing, ICCAC, .

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  58. Methodological guidelines for publishing library data as linked data (, , , , and ), In 2017 International Conference on Information Systems and Computer Science (INCISCOS), .

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  59. Cloud Ready Applications Composed via HTN Planning (, , and ), In IEEE International Conference on Service Oriented Computing and Applications, .

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  60. iTrack: A residential energy monitoring system tailored to meet local needs (, , , , and ), In , .

    Abstract

    The Kingdom of Saudi Arabia, like many other Gulf Council Countries, is lately experiencing a very rapid population and industrial growth, which results in an increasing demand for energy. To meet this growing demand, the GCC too is transitioning towards a smarter electricity grid with increased penetration of renewable sources. However, all agree that the success of such a shift in paradigm also depends on demand side management, most of energy demands coming for residential area. Providing residents with real-time feedback on their energy consumption is a promising way to promote energy saving behavior through an increased awareness. This paper outlines the design and development phases of a residential energy monitoring system that has been tailored to meet local needs, that is to say a non-intrusive system with a user friendly interface available both in English and Arabic endowed with an alert system providing real-time consumption information, as well as energy saving and awareness tips.


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  61. Tracing back the chain: Cognitive pre-requisite analysis for CIS capstone project ( and ), In , volume Part F1346, .

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    © 2017 Association for Computing Machinery. When teaching the first part of the capstone project to the senior students at the College of Computer Sciences and Information Technology, some problems have been reported for the past few semesters. This paper aims to identify the cause of the problem by comparing necessary skills for the capstone project to skills acquired in prior courses, tracing back through the pre-requisite dependency chain. The comparison is set between the Course Learning Outcomes identified in the capstone project and the Course Objectives of courses offered in previous years. The analysis revealed two main discrepancies, namely: Several mismatches and missing links that explained the problems initially observed. It also led to identifying a weakness in one of the previous courses and triggered an adjustment in the course content.


    Keywords: Bloom's taxonomy, CIS capstone, Course design, Course evaluation


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  62. Challenges and trends about smart big geospatial data: A position paper (, and ), In 2017 IEEE International Conference on Big Data (Big Data), .

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  63. A price-based approach for voltage regulation and power loss minimization for the electrical power distribution system (, and ), In 55th IEEE Conference on Decision and Control, .

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  64. Memory-efficient string matching for intrusion detection systems using a high-precision pattern grouping algorithm (, , and ), In Proceedings of the 2016 Symposium on Architectures for Networking and Communications Systems, ACM, .

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  65. Sentiment Classification of Tweets using Hierarchical Classification (, , , and ), In International Conference on Communications, .

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    This paper addresses the problem of sentiment classification of short messages on microblogging platforms. We apply machine learning and pattern recognition techniques to design and implement a classification system for microblog messages assigning them into one of three classes: positive, negative or neutral. As part of this work, we contributed a dataset consisting of approximately 10, 000 tweets, each labeled on a five point sentiment scale by three different people. Experiments demonstrate a detection rate between approximately 70% and an average false alarm rate of approximately 18% across all three classes. The developed classifier has been made available for online use.


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  66. Power Management of Personal Computers based on User Behaviour (, , and ), In International Conference on Smart Cities and Green ICT Systems, .

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  67. Benchmark Datasets for Fault Detection and Classification in Sensor Data (, , and ), In International Conference on Sensor Networks, .

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  68. Influence Maximization in Social Networks with Genetic Algorithms ( and ), In European Conference on the Applications of Evolutionary and Bio-inspired Computation (Evo* EvoApplications), track EvoComplex: Evolutionary Algorithms and Complex Systems, .

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  69. Detecting National Political Unrest on Twitter (, , , and ), In International Conference on Communications, .

    Abstract

    The popular uprisings in a number of countries in the Middle East and North Africa in the Spring of 2011 were broadcasted live and enabled by local populations' access to social networking services such as Twitter and Facebook. The goal of this paper is to study the flow characteristics of the information flow of these broadcasts on Twitter. We have used language independent features of Twitter traffic to identify differences in information flows on Twitter mentioning countries experiencing some form of unrest, compared to traffic mentioning countries with peaceful political situations. We used these features to identify countries with political unstable situation. For empirical analysis, we collected several data sets of countries that were experiencing political unrest, as well as a set of countries in a control group that were not subject to such socio-political condition. Several different methods are used to model the flow of information between Twitter users in data sets as graphs, called information cascades. By using the dynamic properties of information cascades, naïve Bayes and SVM classifiers both achieve true positives rates of 100%, with false positives rates of 3% and 0%, respectively.


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  70. On the relationship between automation and occupants in smart buildings ( and ), In International Conference on ICT for Sustainability, .

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  71. Design-time Compliance of Service Compositions in Dynamic Service Environments (), In 8th IEEEE International Conference on Service Oriented Computing & Applications (SOCA), IEEE (The Institute of Electrical and Electronics Engineers), .

    Abstract

    In order to improve the flexibility of information systems, an increasing amount of business processes is being automated by implementing tasks as modular services in service compositions. As organizations are required to adhere to laws and regulations, with this increased flexibility there is a demand for automated compliance checking of business processes. Model checking is a technique which exhaustively and automatically verifies system models against specifications of interest, e.g. a finite state machine against a set of logic formulas. When model checking business processes, existing approaches either cause large amounts of overhead, linearize models to such an extent that activity parallelization is lost, offer only checking of runtime execution traces, or introduce new and unknown logics. In order to fully benefit from existing model checking techniques, we propose a mapping from workflow patterns to a class of labeled transition systems known as Kripke structures. With this mapping, we provide pre-runtime compliance checking using well-known branching time temporal logics. The approach is validated on a complex abstract process which includes a deferred choice, parallel branching, and a loop. The process is modeled using the Business Process Model and Notation (BPMN) standard, converted into a colored Petri net using the workflow patterns, and subsequently translated into a Kripke structure, which is then used for verification.


    Keywords: Business Process Management, BPMN, Petri net, Kripke models, Verification, Temporal Logic


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  72. CNTFET Full-Adders for Energy-Efficient Arithmetic Applications (, , , , and ), In 6th International Conference on Computing, Communication and Networking Technologies (ICCCNT), IEEE, .

    Abstract

    In this paper, we present two energy-efficient full adders (FAs) which are a crucial building block of nano arithmetic logic units (nano-ALUs) with the Cell Design Methodology (CDM). Since the most suitable design configuration for CNT-based ICs is pass transistor configuration (PTL), CDM which properly benefits from PTL advantages is utilized. So the designs herewith take full advantages of simplicity, fewer transistors and better immunity against threshold voltage fluctuations of the PTL than the CCMOS configuration. CDM also resolves two problems of PTL by employing elegant mechanisms which are threshold voltage drop and loss of gain. Using the amend mechanisms and SEA sizing algorithm for CNTFETs, the proposed circuits enjoy full swing in all outputs and internal nodes, structural symmetry, reduced power-delay product (PDP) and energy-delay product (EDP), fairly balanced outputs and high driving capability. The state of the art includes both bulk CMOS and CNTFET technologies. The simulation results exhibit an average PDP and EDP improvement of 9-98% and 55-99% respectively compared with the referenced FAs. All HSPICE simulations were performed on 32nm CNTFET and CMOS process technologies.


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  73. Black Holes and Revelations: Using Evolutionary Algorithms to Uncover Vulnerabilities in Disruption-Tolerant Networks (, , and ), In European Conference on the Applications of Evolutionary and Bio-inspired Computation, track EvoComNet: Application of Nature-inspired Techniques for Communication Networks and other Parallel and Distributed Systems, .

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  74. Public acceptance of renewable energy and Smart-Grid in Saudi Arabia (, , and ), In , .

    Abstract

    © 2015 IEEE. This study aims to measure the public's knowledge about renewable energy sources, their willingness to use solar energy as a main source in their households, and to understand their main motivation in undergoing (or not) such an energy shift; hence, potential influencing factors that will help win public support can be determined. A survey is tailored in order to capture relevant public belief, perception, and planned behavior, then a descriptive analysis of the data is performed to examine the associations between the willingness to use solar panels in households and the other explanatory variables. Initial results show that government policies and subsidies are main factors affecting the desire to adopt green energy. These results will help overcome obstacles that might be faced prior or during a transition to the Smart-Grid, especially in residential area.


    Keywords: Kingdom of Saudi Arabia, Renewable Energy, Residential Area, Social Acceptance, Solar Energy, Willingness to Pay


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  75. A Service-Oriented Architecture for Web Applications in e-mental health: two case studies ( and ), In IEEE International Conference on Service Oriented Computing & Applications, .

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  76. An automatic method for the enrichment of dicom metadata using biomedical ontologies (, , , and ), In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), .

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  77. Simulating the Interaction with a Smart Grid with Real Services ( and ), In IEEE International Conference on Service Oriented Computing & Applications, .

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  78. IM Session Identification by Outlier Detection in Cross-correlation Functions (, , , and ), In 49th Annual Conference on Information Sciences and Systems, .

    Abstract

    The identification of encrypted Instant Messaging (IM) channels between users is made difficult by the presence of variable and high levels of uncorrelated background traffic. In this paper, we propose a novel Cross-correlation Outlier Detector (CCOD) to identify communicating end-users in a large group of users. Our technique uses traffic flow traces between individual users and IM service provider's data center. We evaluate the CCOD on a data set of Yahoo! IM traffic traces with an average SNR of -6.11dB (data set includes ground truth). Results show that our technique provides 88% true positives (TP) rate, 3% false positives (FP) rate and 96% ROC area. Performance of the previous correlation-based schemes on the same data set was limited to 63% TP rate, 4% FP rate and 85% ROC area.


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  79. A Self-healing Framework for Online Sensor Data (, , and ), In International Workshop on Self-Aware Internet of Things, .

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  80. Rdf-ization of dicom medical images towards linked health data cloud (, , , and ), In VI Latin American Congress on Biomedical Engineering CLAIB 2014, Paraná, Argentina 29, 30 & 31 October 2014, .

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  81. WebMedSA: a web-based framework for segmenting and annotating medical images using biomedical ontologies (, , , , , , and ), In 11th International Symposium on Medical Information Processing and Analysis, volume 9681, .

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  82. Self-healing protocols for infrastructural networks (, , and ), In International Conference on Critical Information Infrastructures Security, .

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  83. The Tradeoffs between Data Delivery Ratio and Energy Costs in Wireless Sensor Networks: A Multi-Objective Evolutionary Framework for Protocol Analysis (, , and ), In Genetic and Evolutionary Computation Conferenc, .

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  84. E-learning Quality Assurance Practices and Benchmarks in Higher Education (), In World Conference on Educational Media and Technology, .

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  85. HowNutsAreTheDutch: Personalized feedback on a national scale (, , , , , , , , , , and ), In AAAI Fall Symposium on Expanding the Boundaries of Health Informatics Using AI, .

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  86. Leefplezier: Personalized well-being (, , and ), In Doctoral Consortium of the IEEE International Conference on Healthcare Informatics, .

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  87. Gamification in a Consulting Company (, and ), In 7th GI Workshop on Autonomous Systems, .

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  88. GreenMind - An Architecture and Realization for Energy Smart Buildings (, , and ), In International Conference on ICT for Sustainability, .

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  89. Network Disruption and Recovery: Co-Evolution of Defender and Attacker in a Dynamic Game (, , , and ), In CompleNet 2014 5th Workshop on Complex Networks, .

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  90. Predicting New Collaborations in Academic Citation Networks of IEEE and ACM Conferences (, , , , , , , and ), In International Conference on Social Computing, .

    Abstract

    In this paper we study the time evolution of academic collaboration networks by predicting the appearance of new links between authors. The accurate prediction of new collaborations between members of a collaboration network can help accelerate the realization of new synergies, foster innovation, and raise productivity. For this study, the authors collected a large data set of publications from 630 conferences of the IEEE and ACM of more than 257, 000 authors, 61, 000 papers, capturing more than 818, 000 collaborations spanning a period of 10 years. The data set is rich in semantic data that allows exploration of many features that were not considered in previous approaches. We considered a comprehensive set of 98 features, and after processing identified eight features as significant. Most significantly, we identified two new features as most significant predictors of future collaborations; 1) the number of common title words, and 2) number of common references in two authors’ papers. The link prediction problem is formulated as a binary classification problem, and three different supervised learning algorithms are evaluated, i.e. Na¨ıve Bayes, C4.5 decision tree and Support Vector Machines. Extensive efforts are made to ensure complete spatial isolation of information used in training and test instances, which to the authors’ best knowledge is unprecedented. Results were validated using a modified form of the classic 10-fold cross validation (the change was necessitated by the way training, and test instances were separated). The Support Vector Machine classifier performed the best among tested approaches, and correctly classified on average more than 80% of test instances and had a receiver operating curve (ROC) area of greater than 0.80.


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  91. Utility-Based HTN Planning ( and ), In European Conference on Artificial Intelligence, .

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  92. Spatial optimality in power distribution networks ( and ), In IEEE Complexity in Engineering Workshop, .

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  93. The Smart Grid's Data Generating Potentials ( and ), In Federated Conference on Computer Science and Information Systems, .

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  94. Towards a Robustness Evaluation Framework for BPEL Engines (, , and ), In International Conference on Service Oriented Computing & Applications, .

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  95. Breaching IM Session Privacy Using Causality (, , , , , , , and ), In Global Communications Conference, .

    Abstract

    The breach of privacy in encrypted instant messenger (IM) service is a serious threat to user anonymity. Performance of previous de-anonymization strategies was limited to 65%. We perform network de-anonymization by taking advantage of the cause-effect relationship between sent and received packet streams and demonstrate this approach on a data set of Yahoo! IM service traffic traces. An investigation of various measures of causality shows that IM networks can be breached with a hit rate of 99%. A KCI Causality based approach alone can provide a true positive rate of about 97%. Individual performances of Granger, Zhang and IGCI causality are limited owing to the very low SNR of packet traces and variable network delays.


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  96. Itemset-based Mining of Constraints for Enacting Smart Environments (, , and ), In Symposium on Activity and Context Modeling and Recognition, .

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  97. A survey of formal business process verification: From soundness to variability ( and ), In Proceedings of International Symposium on Business Modeling and Software Design, SciTePress, .

    Abstract

    Formal verification of business process models is of interest to a number of application areas, including checking for basic process correctness, business compliance, and process variability. A large amount of work on these topics exist, while a comprehensive overview of the field and its directions is lacking. We provide an overview and critical reflections on existing approaches.


    Keywords: Business Process Management, Verification, Model Checking, Survey


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  98. An Evolutionary Framework for Routing Protocol Analysis in Wireless Sensor Networks (, , and ), In European Conference on the Applications of Evolutionary and bio-inspired Computation, volume 7835, .

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  99. Wireless sensor network based monitoring system for photovoltaic panels in extreme GCC climate conditions: A literature review of current approaches ( and ), In , .

    Abstract

    Photovoltaic system performance highly depends on environmental conditions. Hence system requirements to optimize energy yield are unique, and in most cases no relevant data are available to make implementation decisions. This is why monitoring of such systems is very essential for initial system evaluation, and continuous output optimization. This paper is the result of a thorough literature survey about existing performance monitoring system for photovoltaic panels, aiming to propose a system tailored for photovoltaic panels under the very particular environmental conditions experienced in the GCC region, as these countries are in an area with tremendous potential for development of solar energy projects. A wireless sensor network based monitoring system is proposed, that measures data relevant for desert climate like dust, temperature and humidity. A small-scale prototype is described, along with initial experimental results. © 2013 IEEE.


    Keywords: PV panels, Renewable energy, monitoring system, wireless sensor network


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  100. A Machine Learning Approach for Vehicle Classification using Passive Infrared and Ultrasonic Sensors ( and ), In ACM/IEEE Conference on Information Processing in Sensor Networks, .

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  101. Testing of Distributed Service-Oriented Systems (), In ICSOC, volume 8377, .

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  102. Modeling the Last Mile of the Smart Grid ( and ), In PES Innovative Smart Grid Technologies Conference, .

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  103. Cost and Benefits of Denser Topologies for the Smart Grid ( and ), In Computer and Information Sciences III from the 27th International Symposium on Computer and Information Sciences (ISCIS'12), .

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  104. Planning for Coordination of Devices in Energy-Smart Envronments (), In Doctoral Consortium of the 23rd International Conference on Automated Planning and Scheduling, .

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  105. Combining Activity Recognition and AI Planning for Energy-Saving Offices (, and ), In IEEE International Conference on Ubiquitous Intelligence and Computing, .

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  106. Continuous Correctness of Business Processes against Process Interference ( and ), In IEEE International Conference on Service Oriented Computing and Applications, .

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  107. Capacity Analysis of Combined IPTV and VoIP over IEEE 802.11n (, and ), In 38th Annual IEEE Conference on Local Computer Networks, .

    Abstract

    Internet Protocol Television (IPTV) and Voice over Internet Protocol (VoIP) have gained unprecedented growth rates in the past few years. Data rate and high coverage area of IEEE 802.11n motivate the concept of combined IPTV and VoIP over IEEE 802.11n. Transmission of combined IPTV and VoIP over a wireless network is a challenging task. In this paper, we deal with the capacity evaluation of combined IPTV and VoIP over IEEE 802.11n. We evaluate the use of Datagram Congestion Control Protocol (DCCP) at transport layer of IPTV and VoIP. Our study shows that DCCP can enhance capacity of IPTV by 25%. Our study confirms that performance of DCCP deteriorates severely in presence of any other UDP flow because of congestion-less mechanism of UDP. Our fairness analysis with TCP traffic shows that IPTV and VoIP using DCCP provides fair share in bandwidth to TCP with 19% increase in combined capacity. We study the effect of IEEE 802.11n parameters and obtain optimal values. We show the optimal values and trends of Access Point (AP) parameters including Queue size, Transmission Opportunity, Aggregation and Block ACK etc. Our study shows that nearly 9 more VoIP users are supported with a queue size of 70 packets and transmission opportunity of 9. Our study concludes that selection of DCCP and optimized parameters over IEEE 802.11n can enhance the capacity of IPTV and VoIP by atleast 25% and 19% respectively as compared to the use of UDP.


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  108. IPTV Capacity Analysis using DCCP over IEEE 802.11n (, and ), In 78th Vehicular Technology Conference, .

    Abstract

    Internet Protocol Television (IPTV) has gained an enormous growth rate by revolutionizing personal entertainment. High data rates with increased coverage radius of IEEE 802.11n Wireless Local Area Networks (WLANs) motivate the concept of wireless IPTV. Streaming of Television contents over highly pervasive wireless environment with satisfactory Quality of Service (QoS) is a challenging task. Focusing on wireless IPTV, our work deals with the capacity evaluation of IPTV users over IEEE 802.11n. We first present an upper capacity limit for supporting maximum number of users over IEEE 802.11n. We then propose that 4-times packet size is the optimal frame aggregation size for IPTV which maximizes users capacity and QoS. Finally, we suggest the use of Datagram Congestion Control Protocol (DCCP) at transport layer for IPTV. We show that DCCP capacity for IPTV increases upto 35% by reducing packet losses at Access Point (AP), compared to User Datagram Protocol (UDP). We further evaluate fairness of IPTV traffic in the presence of Transmission Control Protocol (TCP) traffic in the network. Our study concludes that IPTV using DCCP over IEEE 802.11n not only provides increased user's capacity but also co-exists fairly with TCP traffic.


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  109. Applying Time Series Analysis and Neighbourhood Voting in a Decentralised Approach for Fault Detection and Classification in WSNs (, , and ), In International Symposium on Information and Communication Technology, .

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  110. A Decentralized Scheme for Fault Detection and Classification in WSNs (, and ), In IEEE International Conference on Cyber-Physical Systems, Networks, and Applications (CPSNA 2013, Work in Progress session), .

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  111. Towards Context Consistency in a Rule-Based Activity Recognition Architecture (, , , , and ), In International Symposium on Ubiquitous Intelligence and Autonomic Systems, .

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  112. Dynamic Constraint Reasoning in Smart Environments ( and ), In IEEE International Conference on Tools with Artificial Intelligence, .

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  113. Service-Oriented Architecture for Smart Environments (, , , , , and ), In IEEE International Conference on Service Oriented Computing and Applications, .

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  114. Business Process Variability: A Tool for Declarative Template Design (, and ), In Service-Oriented Computing, Springer, volume 7221, .

    Abstract

    To lower both implementation time and cost, many Business Process Management tools use process templates to implement highly recurring processes. However, in order for such templates to be used, a process has to adhere substantially to the template. Therefore, current practice for processes which deviate more than marginally is to either manually implement them at high costs, or for the business to inflexibly comply to the template. In this paper, we describe a tool which demonstrates a variability based solution to process template definition.


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  115. A Machine Learning Approach for Identifying and Classifying Faults in Wireless Sensor Networks (, and ), In 10th IEEE International Conference on Embedded and Ubiquitous Computing, .

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  116. Fault Detection in Wireless Sensor Networks: a Hybrid Approach (, , and ), In ACM Conference on Information Processing in Sensor Networks (IPSN'12 POSTER Session), .

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  117. A Statistical Analysis of Power Grid Vulnerabilities ( and ), In Workshops of The seventh CRITIS Conference on Critical Information Infrastructures Security, .

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  118. Service Ecologies for Home/Building Automation (, , , , and ), In 10th Int. IFAC Symposium on Robot Control, .

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  119. Adaptive Game-based Agent Negotiation in Deregulated Energy Markets (, , and ), In Workshop on Adaptive Collaboration at (CTS 2012), .

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  120. An Agent-based Application to Enable Deregulated Energy Markets (, , and ), In IEEE Computer Software and Applications Conference, .

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  121. Automatic Detection of Business Process Interference (, , , and ), In International Workshop on Knowledge-intensive Business Processes, .

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  122. Beyond Indoor Presence Monitoring with Simple Sensors ( and ), In International Conference on Pervasive and Embedded Computing and Communication Systems, .

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  123. Cost-efficient Context-aware Rule Maintenance ( and ), In Workshop on Context Modeling and Reasoning, .

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  124. Declarative Enhancement Framework for Business Processes (, and ), In Service-Oriented Computing (G. Kappel, Z. Maamar, H.R. Motahari Nezhad, eds.), Springer, volume 7084, .

    Abstract

    While Business Process Management (BPM) was designed to support rigid production processes, nowadays it is also at the core of more flexible business applications and has established itself firmly in the service world. Such a shift calls for new techniques. In this paper, we introduce a variability framework for BPM which utilizes temporal logic formalisms to represent the essence of a process, leaving other choices open for later customization or adaption. The goal is to solve two major issues of BPM: enhancing reusability and flexibility. Furthermore, by enriching the process modelling environment with graphical elements, the complications of temporal logic are hidden from the user.


    Keywords: BPM, Variability, Temporal Logic, e-Government


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  125. Assessing Schizophrenia with an Interoperable Architecture (, , and ), In ACM International Conference on Information and Knowledge Management, .

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  126. An agent-based wide area protection scheme for self-healing grids (), In , .

    Abstract

    This paper presents a wide area protection multi-agent system with high degree of tolerance to faults. Agents in this protection system detect and locate faults by comparing current measurements across the protected component following principles of conventional differential protection; yet they perform sensor data integrity evaluation through a trip confirmation mechanism, by cooperating and collaborating with neighbor agents. This mechanism prevent from possible false trips caused by measurement failure or a failure of communication channel, resulting in explicit sensor failure detection and location. A missing sensor restoration mechanism is initiated to mitigate the effects of sensor failure, applying a self-healing strategy. The principles of cooperation and collaboration are presented, and the structure and hierarchy of protection agents are designed. © 2011 IEEE.


    Keywords: Distributed Energy Resources, Distributed-Intelligence, Fault Detection, Location and Isolation, Multi-Agent System, Self-Healing, Wide-Area Protection


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  127. A distributed fault protection method for power grid with high penetration of renewable energy sources (, and ), In , .

    Abstract

    This study addresses the fault protection issues that will be caused by the increased penetration of Renewable Energy Sources (RES). A new Distributed Wide Area Differential Protection (DWADP) scheme is proposed to overcome these problems, and hence to improve reliability of power systems. Tools of intelligence are integrated at the relay level, capable of generating optimal responses, based on communication with direct neighbors only, instead of a system wide communication, thus minimizing both the required bandwidth and the degree of connectivity between different relays. The proposed DWADP scheme contains a conventional differential protection scheme cascaded with a trip confirmation mechanism (TCM), which performs sensor data integrity evaluation, and a missing sensor restoration mechanism (MSRM). Hence, false trip can be avoided, while locating sensor failures, thus making it possible to take preventive action. © 2011 IEEE.


    Keywords: Fault Location, Fault Tolerance, Power System Protection, Renewable Energy Sources


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  128. A sensor failure resilience metric for ship-board power system (, and ), In , .

    Abstract

    This study defines a metric of resilience to sensor faults for ship-board power system. Hence, one is able to compare different power system topology with respect to their robustness to sensor faults, which provides valuable information in the design phase. For a given power system topology, we first present a distributed wide area differential protection (DWAPS) scheme, that is able to cope with the difficulties caused by short cables used to connect the various busbars on board. The proposed scheme is an elaboration of previous studies yet integrates tools of intelligence at the relay level based on a communication with direct neighbors only, instead of a system wide communication, thus minimizing both the required bandwidth and the degree of connectivity between different relays. We then demonstrate how to explicitly reconstruct lost data after sensor failure. Finally, we define the minimum number of sensor that makes this restoration possible as sensor failure resilience metric. © 2011 IEEE.


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  129. Continual Planning with Sensing for Web Service Composition (, and ), In AAAI Conference on Artificial Intelligence, .

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  130. Heterogeneous Device Discovery Framework For the Smart Homes (, , , and ), In IEEE GCC Conference & Exhibition, .

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  131. Testing for Highly Distributed Service-oriented Systems using Virtual Environments (, and ), In Postproceedings of 17th Dutch Testing Day, .

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  132. Smart Homes to Improve the Quality of Life for All (, , , , , , , , , and ), In 33rd Annual International IEEE Engineering in Medicine and Biology Conference, .

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  133. Smart Meter aware Domestic Energy Trading Agents (, , and ), In International E-Energy Market Challenge at 8th ACM Autonomic Computing Conference, .

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  134. Business Process Customization using Process Merging Techniques (, and ), In International Conference on Service-Oriented Computing and Applications, .

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  135. Sensor optimization and placement for enhanced power system monitoring using entropy (, , and ), In , .

    Abstract

    In this paper we propose a new methodology for sensor optimization and placement in a power system. The objectives of this study are to identify basic concepts on sensor optimization and placements to enhance the reliability and for efficient sensor data collection, processing, and transmission. Two approaches based on automatic control and information theory have been proposed. Condition of observability and fault detectability and isolability is developed to determine the optimal number of sensors and to determine the set of candidate sensors necessary for state estimation and fault detection and isolation. An entropy-based heuristic is proposed for the selection of the best sensors candidate that increases the information gain, thereby decreasing the drawback of system complexity and information uncertainty. © 2011 IEEE.


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  136. Interpretation of Inconsistencies via Context Consistency Diagrams ( and ), In Annual IEEE International Conference on Pervasive Computing and Communications, .

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  137. A survey of variability management requirements (, and ), In 5th SIKS/BENAIS Conference on Enterprise Information Systems, EIS 2010, CEUR Workshop Proceedings (CEUR-WS.org), volume 662, .

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  138. Requirements and Tools for Variability Management (, and ), In Computer Software and Applications Conference Workshops (COMPSACW), IEEE (The Institute of Electrical and Electronics Engineers), .

    Abstract

    Explicit and software-supported Business Process Management has become the core infrastructure of any medium and large organization that has a need to be efficient and effective. The number of processes of a single organization can be very high, furthermore, they might be very similar, be in need of momentary change, or evolve frequently. If the ad-hoc adaptation and customization of processes is currently the dominant way, it clearly is not the best. In fact, providing tools for supporting the explicit management of variation in processes (due to customization or evolution needs) has a profound impact on the overall life-cycle of processes in organizations. Additionally, with the increasing adoption of Service-Oriented Architectures, the infrastructure to support automatic reconfiguration and adaptation of business process is solid. In this paper, after defining variability in business process management, we consider the requirements for explicit variation handling for (service based) business process systems. eGovernment serves as an illustrative example of reuse. In this case study, all local municipalities need to implement the same general legal process while adapting it to the local business practices and IT infrastructure needs. Finally, an evaluation of existing tools for explicit variability management is provided with respect to the requirements identified.


    Keywords: workflow management software, software architecture, business data processing, web services


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  139. ValySeC: a Variability Analysis Tool for Service Compositions using VxBPEL (, and ), In , .

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  140. Interoperation, Composition and Simulation of Services at Home (, , , and ), In International Conference on Service Oriented Computing, .

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  141. A tool for integrating pervasive services and simulating their composition (, , , and ), In International Conference on Service Oriented Computing, Demo Session, .

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  142. Towards a Service-Oriented Energy Market: Current state and trend ( and ), In Workshop on Service, Energy and Ecosystems (colocated with ICSOC-10), .

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  143. Modeling Enterprise Information Systems Integration Evaluation as a Dynamic System (, and ), In International Conference on Computing and ICT Research, .

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  144. Resolving Business Process Interference via Dynamic Reconfiguration (, , and ), In International Conference on Service Oriented Computing, .

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  145. Mining Twitter in the Cloud: A Case Study (, and ), In IEEE 3rd International Conference on Cloud Computing, .

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  146. Parity space approach for enhanced fault detection and intelligent sensor network design in power systems (, , and ), In , .

    Abstract

    In this study, the model-based fault detection and isolation (FDI) approach of parity-space is adapted to the diagnosis of sensor faults in power systems. Hardware redundancy is conventionally utilized to overcome this problem. However, this is an expensive solution. Instead, we propose to detect and locate faults by the systematic use of the system's analytical redundancy, with a global view of the system. This redundancy can be used to detect and isolate sensor failure as well. We also give necessary and sufficient conditions for a sensor network to be able detect faults, sensor failures included. Hence, the sensor configuration problem boils down to an optimization problem that can be intelligently guided by our method. The principle of parity-space approach is described in detail and illustrated on a simple power system model. The method is then validated through simulation. ©2010 IEEE.


    Keywords: Fault diagnosis, Power system protection, Sensor, Wide-Area protection


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  147. Concept mapping for faster QoS-Aware Web Service Composition (, , and ), In IEEE Conference on Service Oriented Computing and Applications, .

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  148. Planning in a Smart Home: Visualization and Simulation (, , and ), In International Conference on Automated Planning and Scheduling, .

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  149. Extended Goals for Composing Services (, and ), In International Conference on Automated Planning and Scheduling, .

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  150. Services inside the Smart Home: A Simulation and Visualization tool (, , , and ), In International Conference on Service Oriented Computing, .

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  151. General Chair's Report (), In 18th IEEE International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises, 2009, .

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  152. Optimal QoS-Aware Web Service Composition (, , and ), In Joint 11th IEEE Conference on E-Commerce Technology (CEC'08) and the 6th IEEE Conference on Enterprise Computing, E-Commerce and E-Services IEEE Computer, .

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  153. Bluetooth Broadcasting: How far can we go? An experimental study (, and ), In International Conference on Pervasive Computing and Applications, .

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  154. Smart Homes Infrastructures and Interactions (, and ), In IEEE International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises, .

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  155. Maintenance of customized processes (), In PhD symposium, hosted by 7th International Conference on Service Oriented Computing, .

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  156. Visualizing Compositions of Services from Large Repositories (, and ), In E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services, 2008 10th IEEE Conference on, .

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  157. Towards Variable Service Compositions using VxBPEL ( and ), In International Conference on Software Reuse (H. Mei, ed.), volume LNCS 5030, .

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  158. Structural analysis for assessment of monitoring possibilities: Application to simple power system topologies (, , and ), In , .

    Abstract

    Any power system, either an integrated power system in an all-electric ship or a utility power system, needs to be highly reliable. Reliability of a complex system strongly depends on the possibility of detecting faults and isolating them from each other, i.e., on the monitoring potential of the system. The area of power system engineering that is concerned with the fault detection and isolation is called protection. As power systems becoming more and more complex, current standards for their protection should be adjusted accordingly to meet the challenges associated with increased system complexity. The standard approach used in power system protection is local, that is, current and voltage sensors are placed at or near individual breakers that open up to isolate a fault (short circuit). Coordination between breakers is achieved indirectly by setting the voltage or current trip points of the breakers differently so they open up in a desired sequence. Wide-area (global) protection is a new research direction. Wide-area protection schemes provide protection at more unified, global level than local protection schemes, and often operate as a backup level of protection. However, these schemes are usually developed manually, that is, the arrangement of protective actions within areas are made by hand, following heuristic considerations. More systematic and automated approaches are required for successful wide-area protection of larger systems. The objective of the current study is to adapt the model-based fault detection and isolation approach based on structural analysis to power systems in order to evaluate the monitoring potential of a given power system topology (architecture) in a systematic and automated manner. A new methodology is applied to evaluate the monitoring potential of a few simple topologies. © 2008 IEEE.


    Keywords: Fault detection and isolation, Power systems, Protection algorithms, Structural analysis


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  159. A new methodology for automated assessment of fault detection and isolation possibilities in large power systems (, , and ), In , .

    Abstract

    Any power system, whether an integrated power system in an all-electric ship or a utility power system, needs to be highly reliable. Reliability of a complex system strongly depends on the monitoring possibilities of the system. The area of power system engineering that is concerned with fault detection and isolation is called protection. As power systems become more complex, current methods for their protection should be adjusted accordingly to meet the challenges associated with increased system complexity. The standard approach for power system protection is local, that is, current and voltage sensors are placed at or near individual breakers that can open in order to isolate a fault. Coordination between breakers is achieved indirectly by setting the voltage or current trip points of the breakers differently so that they open in a desired sequence. Wide-area protection is a new research direction that provides protection at a more unified level, and often operates as a backup level of protection. However, these schemes are usually developed manually following heuristic considerations. This study proposes a new methodology based on the structural analysis of control theory, and provides the possibility of a systematic and automated approach to global power-system protection. © 2008 SIMULATION COUNCILS, INC.


    Keywords: Fault detection and isolation, Power systems, Protection algorithms, Structural analysis


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  160. Requirements and Evaluation of Protocols and Tools for Transaction Management in Service Centric Systems ( and ), In Computer Software and Applications Conference, 2007. COMPSAC 2007. 31st Annual International, volume 2, .

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  161. The Mathematical Morpho-Logical view on Reasoning about Space ( and ), In International Joint Conference on Artificial Intelligence, .

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  162. DMC Workshop Final Report (, and ), In Enabling Technologies: Infrastructure for Collaborative Enterprises, 2007. WETICE 2007. 16th IEEE International Workshops on, .

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  163. Adaptive structural analysis for FDI design in evolving systems (, and ), In , volume 6, .

    Abstract

    Although structural analysis for Fault Detection and Isolation (FDI) is a well formalized method, a significant effort has still to be made concerning implementation issues and algorithmic aspects in order to make the method better applicable for real-life industrial problems. System's evolution is one of these points to be considered. The main contribution of this paper is an adaptive/evolutive algorithm that avoids unnecessary duplication of work by efficiently making use of already generated results. Copyright © 2006 IFAC.


    Keywords: Adaptive algorithm, FDI, Structural analysis, System evolution


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  164. Structural analysis for residual generation: Towards implementation (, and ), In , volume 2, .

    Abstract

    In that paper an innovative way of dealing with the generation of residuals for fault-detection and isolation based on structural information is presented. The developed technique considers implementation issues therefore it has a more realistic point of view compared to classical structural approaches. First practical issues that can be encountered such as computational complexity or implementation considerations are introduced. Then the way of incorporating them to the existing structural analysis framework is explained. Finally, we show how the Stable Marriage Problem can be successfully adapted in order to choose the most suited matching that leads to residual computational sequences. The algorithm has been implemented and tested using a real life benchmark model: the Damadics valve © 2004 IEEE.


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  165. Improving fault isolability properties by structural analysis of faulty behavior models: Application to the damadics benchmark problem (, , and ), In , volume 36, .

    Abstract

    Structural analysis is a powerful tool for early determination of detectability/isolability possibilities. It is shown how different levels of knowledge about faults can be incorporated in a structural fault-isolability analysis and how they result in different isolability properties. The results are evaluated on the DAMADICS valve benchmark model. It is also shown how to determine which faults in the benchmark that need further modeling to get desired isolability properties of the diagnosis system.


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