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  • 1.
    Elsts, Atis
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Hassani Bijarbooneh, Farshid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Jacobsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Enabling design of performance-controlled sensor network applications through task allocation and reallocation2015In: Proc. 11th International Conference on Distributed Computing in Sensor Systems, IEEE Computer Society, 2015, p. 248-253Conference paper (Refereed)
    Abstract [en]

    Task Graph (ATaG) is a sensor network application development paradigm where the application is visually described by a graph where the nodes correspond to application-level tasks and edges correspond to dataflows. We extend ATaG with the option to add nonfunctional requirements: constraints on end-to-end delay and packet delivery rate. Setting up these constraints at the design phase naturally leads to enabling run-time assurance at the deployment phase, when the conditions of the constraints are used as network's performance goals. We provide both run-time middleware that checks the conditions of these constraints and a central management unit that dynamically adapts the system by doing task reallocation and putting task copies on redundant nodes. Through extensive simulations we show that the system is efficient enough to enable adaptations within tens of seconds even in large networks.

  • 2.
    Elsts, Atis
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Hassani Bijarbooneh, Farshid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Jacobsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    ProFuN TG: A tool for programming and managing performance-aware sensor network applications2015In: IEEE 40th Local Computer Networks Conference Workshops (LCN Workshops), IEEE Computer Society, 2015, p. 751-759Conference paper (Refereed)
    Abstract [en]

    Sensor network macroprogramming methodologiessuch as the Abstract Task Graph hold the promise of enablinghigh-level sensor network application development. However,progress in this area is hampered by the scarcity of tools, andalso because of insufficient focus on developing tool support forprogramming applications aware of performance requirements.

    We present ProFuN TG (Task Graph), a tool for designing sen-sor network applications using task graphs. ProFuN TG providesautomated task mapping, sensor node firmware macrocompila-tion, application simulation, deployment, and runtime mainte-nance capabilities. It allows users to incorporate performancerequirements in the applications, expressed through constraintson task-to-task dataflows. The tool includes middleware that usesan efficient flooding-based protocol to set up tasks in the network,and also enables runtime assurance by keeping track of theconstraint conditions.

    We show that the adaptive task reallocation enabled by ourapproach can significantly increase application reliability whiledecreasing energy consumption: in a network with unreliablelinks, we achieve above 99.89 % task-to-task PDR while keepingthe maximal radio duty cycle around 2.0 %.

  • 3.
    Elsts, Atis
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Hassani Bijarbooneh, Farshid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Jacobsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    ProFuN TG: A Tool Using Abstract Task Graphs to Facilitate the Development, Deployment and Maintenance of Wireless Sensor Network Applications2015In: Proc. Poster/Demo Session: 12th European Conference on Wireless Sensor Networks, 2015, p. 19-20Conference paper (Refereed)
    Abstract [en]

    In this demo abstract we present ProFuN TG (Task Graph), a tool for sensor network application development using the data-flow programming paradigm. The tool has support for the whole lifecycle of WSN application: from the initial design of its task graph, task placement on network nodes, execution in a simulated environment, deployment on real hardware, to its automated maintenance through task remapping. ProFuN TG allows to program applications that incorporate quality-of-service requirements, expressed through constraints on task-to-task data flows.

  • 4.
    Elsts, Atis
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Hassani Bijarbooneh, Farshid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Jacobsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    ProFuN TG: Programming Sensornets with Task Graphs for Increased Reliability and Energy-Efficiency2015Conference paper (Refereed)
    Abstract [en]

    Sensor network macroprogramming methodologies such as the Abstract Task Graph hold the promise of enabling high-level sensor network application development. However, progress in this area is hampered by the scarcity of tools, and also because of insufficient focus on developing tool support for programming applications aware of performance requirements.

    In this demo we present ProFuN TG (Task Graph), a tool for designing sensor network applications using task graphs. ProFuN TG provides automated task mapping, sensor nodefirmware macrocompilation, application simulation, deployment, and runtime maintenance capabilities. It allows users to incorporate performance requirements in the applications, expressed through constraints on task-to-task dataflows. The tool includes middleware that uses an efficient flooding-based protocol to set up tasks in the network, and also enables runtime assurance by keeping track of the constraint conditions.

    Through task allocation in a way that optimizes an objective function in a model of the network, and adaptive task reallocation in case of link, node, or sensor failures the tool helps to make sensornet applications both more energy-efficient and reliable.

  • 5.
    Hassani Bijarbooneh, Farshid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Cloud-Assisted Data Fusion and Sensor Selection for Internet-of-ThingsManuscript (preprint) (Other academic)
    Abstract [en]

    The Internet of Things (IoT) is connecting people and smart devices on a scale that once was unimaginable. One major challenge for the IoT is to handle vast amount of sensing data generated from the smart devices that are resource-limited and subject to missing data due to link or node failures. By exploring cloud computing with the IoT, we present a cloud-based solution that takes into account the link quality and spatio-temporal correlation of data to minimise energy consumption by selecting sensors for sampling and relaying data. We propose a multi-phase adaptive sensing algorithm with belief propagation protocol (ASBP), which can provide high data quality and reduce energy consumption by turning on only a small number of nodes in the network. We formulate the sensor selection problem and solve it using constraint programming (CP) and greedy search. We then use our message passing algorithm (belief propagation) for performing inference to reconstruct the missing sensing data. ASBP is evaluated based on the data collected from real sensors. The results show that while maintaining a satisfactory level of data quality and prediction accuracy, ASBP can provide load balancing among sensors successfully and preserves 80\% more energy compared with the case where all sensor nodes are actively involved.

  • 6.
    Hassani Bijarbooneh, Farshid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computing Science. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Constraint Programming for Wireless Sensor Networks2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    In recent years, wireless sensor networks (WSNs) have grown rapidly and have had a substantial impact in many applications. A WSN is a network that consists of interconnected autonomous nodes that monitor physical and environmental conditions, such as temperature, humidity, pollution, etc. If required, nodes in a WSN can perform actions to affect the environment.

    WSNs present an interesting and challenging field of research due to the distributed nature of the network and the limited resources of the nodes. It is necessary for a node in a WSN to be small to enable easy deployment in an environment and consume as little energy as possible to prolong its battery lifetime. There are many challenges in WSNs, such as programming a large number of nodes, designing communication protocols, achieving energy efficiency, respecting limited bandwidth, and operating with limited memory. WSNs are further constrained due to the deployment of the nodes in indoor and outdoor environments and obstacles in the environment.

    In this dissertation, we study some of the fundamental optimisation problems related to the programming, coverage, mobility, data collection, and data loss of WSNs, modelled as standalone optimisation problems or as optimisation problems integrated with protocol design. Our proposed solution methods come from various fields of research including constraint programming, integer linear programming, heuristic-based algorithms, and data inference techniques.

    List of papers
    1. Energy-efficient task mapping for data-driven sensor network macroprogramming using constraint programming
    Open this publication in new window or tab >>Energy-efficient task mapping for data-driven sensor network macroprogramming using constraint programming
    2011 (English)In: Operations Research, Computing, and Homeland Defense, Hanover, MD: Institute for Operations Research and the Management Sciences , 2011, p. 199-209Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    Hanover, MD: Institute for Operations Research and the Management Sciences, 2011
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-136365 (URN)10.1287/ics.2011.0016 (DOI)978-0-9843378-1-1 (ISBN)
    Conference
    12th INFORMS Computing Society Conference
    Projects
    ProFuN
    Funder
    Swedish Foundation for Strategic Research , RIT08-0065
    Available from: 2011-01-11 Created: 2010-12-12 Last updated: 2018-01-12Bibliographically approved
    2. An optimisation-based approach for wireless sensor deployment in mobile sensing environments
    Open this publication in new window or tab >>An optimisation-based approach for wireless sensor deployment in mobile sensing environments
    2012 (English)In: Proc. Wireless Communications and Networking Conference 2012, IEEE Communications Society, 2012, p. 2108-2112Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    IEEE Communications Society, 2012
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-171536 (URN)10.1109/WCNC.2012.6214140 (DOI)000324580702038 ()978-1-4673-0436-8 (ISBN)
    Conference
    WCNC 2012
    Projects
    ProFuN
    Funder
    Swedish Foundation for Strategic Research , RIT08-0065
    Available from: 2012-06-11 Created: 2012-03-20 Last updated: 2018-01-12Bibliographically approved
    3. Optimising quality of information in data collection for mobile sensor networks
    Open this publication in new window or tab >>Optimising quality of information in data collection for mobile sensor networks
    2013 (English)In: Proc. 21st International Symposium on Quality of Service, IEEE Communications Society, 2013, p. 163-172Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    IEEE Communications Society, 2013
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-208996 (URN)10.1109/IWQoS.2013.6550277 (DOI)000325614100019 ()978-1-4799-0589-8 (ISBN)
    Conference
    IEEE/ACM 21st International Symposium on Quality of Service (IWQoS), 3-4 June, 2013, Montreal, QC
    Projects
    ProFuN
    Funder
    Swedish Foundation for Strategic Research , RIT08-0065
    Available from: 2013-10-13 Created: 2013-10-13 Last updated: 2018-01-11Bibliographically approved
    4. A constraint programming approach for managing end-to-end requirements in sensor network macroprogramming
    Open this publication in new window or tab >>A constraint programming approach for managing end-to-end requirements in sensor network macroprogramming
    Show others...
    2014 (English)In: Proc. 3rd International Conference on Sensor Networks / [ed] Postolache, Octavian; van Sinderen, Marten; Ali, Falah; Benavente-Peces, César, Setúbal, Portugal: SciTePress, 2014, p. 28-40Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    Setúbal, Portugal: SciTePress, 2014
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-210431 (URN)10.5220/0004715200280040 (DOI)978-989-758-001-7 (ISBN)
    Conference
    SENSORNETS 2014
    Projects
    ProFuN
    Funder
    Swedish Foundation for Strategic Research , RIT08-0065
    Available from: 2014-01-09 Created: 2013-11-08 Last updated: 2018-01-11Bibliographically approved
    5. Energy-efficient sensor selection for data quality and load balancing in wireless sensor networks
    Open this publication in new window or tab >>Energy-efficient sensor selection for data quality and load balancing in wireless sensor networks
    2014 (English)In: Proc. 22nd International Symposium on Quality of Service, IEEE Communications Society, 2014, p. 338-343Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    IEEE Communications Society, 2014
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-229594 (URN)10.1109/IWQoS.2014.6914338 (DOI)000355927000044 ()978-1-4799-4852-9 (ISBN)
    Conference
    IWQoS 2014, May 26–27, Hong Kong, China
    Projects
    ProFuN
    Funder
    Swedish Foundation for Strategic Research , RIT08-0065
    Available from: 2014-05-27 Created: 2014-08-11 Last updated: 2018-01-11Bibliographically approved
    6. Cloud-Assisted Data Fusion and Sensor Selection for Internet-of-Things
    Open this publication in new window or tab >>Cloud-Assisted Data Fusion and Sensor Selection for Internet-of-Things
    (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    The Internet of Things (IoT) is connecting people and smart devices on a scale that once was unimaginable. One major challenge for the IoT is to handle vast amount of sensing data generated from the smart devices that are resource-limited and subject to missing data due to link or node failures. By exploring cloud computing with the IoT, we present a cloud-based solution that takes into account the link quality and spatio-temporal correlation of data to minimise energy consumption by selecting sensors for sampling and relaying data. We propose a multi-phase adaptive sensing algorithm with belief propagation protocol (ASBP), which can provide high data quality and reduce energy consumption by turning on only a small number of nodes in the network. We formulate the sensor selection problem and solve it using constraint programming (CP) and greedy search. We then use our message passing algorithm (belief propagation) for performing inference to reconstruct the missing sensing data. ASBP is evaluated based on the data collected from real sensors. The results show that while maintaining a satisfactory level of data quality and prediction accuracy, ASBP can provide load balancing among sensors successfully and preserves 80\% more energy compared with the case where all sensor nodes are actively involved.

    National Category
    Computer Sciences
    Research subject
    Computer Science
    Identifiers
    urn:nbn:se:uu:diva-241377 (URN)
    Projects
    ProFuN
    Available from: 2015-01-12 Created: 2015-01-12 Last updated: 2018-01-11
  • 7.
    Hassani Bijarbooneh, Farshid
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Du, Wei
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Fu, Xiaoming
    Liu, Jiangchuan
    Cloud-assisted data fusion and sensor selection for Internet of Things2016In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 3, no 3, p. 257-268Article in journal (Refereed)
  • 8.
    Hassani Bijarbooneh, Farshid
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Du, Wei
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Fu, Xiaoming
    Energy-efficient sensor selection for data quality and load balancing in wireless sensor networks2014In: Proc. 22nd International Symposium on Quality of Service, IEEE Communications Society, 2014, p. 338-343Conference paper (Refereed)
  • 9.
    Hassani Bijarbooneh, Farshid
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Flener, Pierre
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Pearson, Justin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    An optimisation-based approach for wireless sensor deployment in mobile sensing environments2012In: Proc. Wireless Communications and Networking Conference 2012, IEEE Communications Society, 2012, p. 2108-2112Conference paper (Refereed)
  • 10.
    Hassani Bijarbooneh, Farshid
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Flener, Pierre
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Pearson, Justin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Energy-efficient task mapping for data-driven sensor network macroprogramming using constraint programming2011In: Operations Research, Computing, and Homeland Defense, Hanover, MD: Institute for Operations Research and the Management Sciences , 2011, p. 199-209Conference paper (Refereed)
  • 11.
    Hassani Bijarbooneh, Farshid
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Flener, Pierre
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Pearson, Justin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Energy-efficient task-mapping for data-driven sensor network macroprogramming using constraint programming2010In: Proc. 9th International Workshop on Constraint Modelling and Reformulation, Uppsala, Sweden: Department of Information Technology, Uppsala University , 2010, p. 13-Conference paper (Other academic)
  • 12.
    Hassani Bijarbooneh, Farshid
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Flener, Pierre
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Pearson, Justin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Optimising quality of information in data collection for mobile sensor networks2013In: Proc. 21st International Symposium on Quality of Service, IEEE Communications Society, 2013, p. 163-172Conference paper (Refereed)
  • 13.
    Hassani Bijarbooneh, Farshid
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Flener, Pierre
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Pearson, Justin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Dynamic demand-capacity balancing for air traffic management using constraint-based local search: First results2009In: Proc. 6th International Workshop on Local Search Techniques in Constraint Satisfaction, 2009, p. 27-40Conference paper (Refereed)
  • 14.
    Hassani Bijarbooneh, Farshid
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Jacobsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Macroprogramming of Wireless Sensor Networks using Task Graphs and Constraint Solving2012Conference paper (Refereed)
    Abstract [en]

    Programming a wireless sensor network (WSN) on node level is a tedious, difficult, and error-prone task. A way to address this problem is to use a high-level programming language specifically designed for WSNs. However, we anticipate to go one step further and provide a standard and generic model for macro-level programming of WSNs. We propose a platform for WSNs as a multi-layer abstraction approach for macroprogramming, where, on the highest level of abstraction, the developer uses an interactive graphical interface to specify the features of a sensor network as a data-driven task graph. The task graph expresses the functionality of the entire network as a whole, and it encapsulates the requirements and resource limitations on the network and the sensor nodes, as well as the data flows among the tasks. This platform makes use of several optimization methods, such as constraint programming, to map the tasks to nodes optimally, and to plan the configuration for deployment to maximize the network life time. It makes use of more realistic network abstractions and takes into account the dynamics of WSNs. We present our model for macro-level programming and show that many optimization problems in this context can be solved more efficiently with suitable techniques.

  • 15.
    Hassani Bijarbooneh, Farshid
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Pathak, Animesh
    Pearson, Justin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Issarny, Valérie
    Jonsson, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    A constraint programming approach for managing end-to-end requirements in sensor network macroprogramming2014In: Proc. 3rd International Conference on Sensor Networks / [ed] Postolache, Octavian; van Sinderen, Marten; Ali, Falah; Benavente-Peces, César, Setúbal, Portugal: SciTePress, 2014, p. 28-40Conference paper (Refereed)
1 - 15 of 15
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