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A Cost Efficient Design of a Multi-Sink Multi-Controller Wireless Sensor Networks in a Smart Factory
Mälardalen University, , .
Mälardalen University, , .
Mälardalen University, , .
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2017 (English)In: IEEE International Conference on High Performance Computing and Communications, IEEE Press , 2017Conference paper (Refereed)
Abstract [en]

Internet of Things (IoT), one of the key elements of a smart factory, is dubbed as Industrial IoT (IIoT). Software defined networking is a technique that benefits network manage- ment in IIoT applications by providing network reconfigurability. In this way, controllers are integrated within the network to advertise routing rules dynamically based on network and link changes. We consider controllers within Wireless Sensor Networks (WSNs) for IIoT applications in such a way to provide reliability and timeliness. Network reliability is addressed for the case of node failure by considering multiple sinks and multiple controllers. Real-time requirements are implicitly applied by limiting the number of hops (maximum path-length) between sensors and sinks/controllers, and by confining the maximum workload on each sink/controller. Deployment planning of sinks should ensure that when a sink or controller fails, the network is still connected. In this paper, we target the challenge of placement of multiple sinks and controllers, while ensuring that each sensor node is covered by multiple sinks (k sinks) and multiple controllers (k′ controllers). We evaluate the proposed algorithm using the benchmark GRASP-MSP through extensive experiments, and show that our approach outperforms the benchmark by lowering the total deployment cost by up to 24%. The reduction of the total deployment cost is fulfilled not only as the result of decreasing the number of required sinks and controllers but also selecting cost-effective sinks/controllers among all candidate sinks/controllers.

Place, publisher, year, edition, pages
IEEE Press , 2017.
Keyword [en]
Industrial Internet of Things; wireless sensor net- works; software defined networking; cloud computing; fog computing.
National Category
Computer Engineering
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-151446OAI: oai:DiVA.org:su-151446DiVA: diva2:1173305
Available from: 2018-01-12 Created: 2018-01-12

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Citation style
  • apa
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Output format
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