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Hierarchal Placement of Smart Mobile Access Points in Wireless Sensor Networks Using Fog Computing
Mälardalen University, Sweden.ORCID iD: 0000-0001-6289-1521
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2017 (English)In: Proceedings - 2017 25th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2017, Institute of Electrical and Electronics Engineers Inc. , 2017, p. 176-180Conference paper (Refereed)
Abstract [en]

Recent advances in computing and sensor technologies have facilitated the emergence of increasingly sophisticated and complex cyber-physical systems and wireless sensor networks. Moreover, integration of cyber-physical systems and wireless sensor networks with other contemporary technologies, such as unmanned aerial vehicles (i.e. drones) and fog computing, enables the creation of completely new smart solutions. By building upon the concept of a Smart Mobile Access Point (SMAP), which is a key element for a smart network, we propose a novel hierarchical placement strategy for SMAPs to improve scalability of SMAP based monitoring systems. SMAPs predict communication behavior based on information collected from the network, and select the best approach to support the network at any given time. In order to improve the network performance, they can autonomously change their positions. Therefore, placement of SMAPs has an important role in such systems. Initial placement of SMAPs is an NP problem. We solve it using a parallel implementation of the genetic algorithm with an efficient evaluation phase. The adopted hierarchical placement approach is scalable, it enables construction of arbitrarily large SMAP based systems.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2017. p. 176-180
Keywords [en]
cyber-physical systems, evolutionary computing, fog computing wireless sensor networks, genetic algorithms, multi-objective optimization, multi-population, parallel approaches, parallel programming, placement, smart mobile access point, Cyber Physical System, Embedded systems, Fog, Hierarchical systems, Multiobjective optimization, Optimization, Scalability, Unmanned aerial vehicles (UAV), Mobile access, Multi population, Wireless sensor networks
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-216520DOI: 10.1109/PDP.2017.27ISI: 000403395100022Scopus ID: 2-s2.0-85019635352ISBN: 9781509060580 OAI: oai:DiVA.org:kth-216520DiVA, id: diva2:1161838
Conference
25th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2017, 6 March 2017 through 8 March 2017
Note

QC 20171201

Available from: 2017-12-01 Created: 2017-12-01 Last updated: 2017-12-01Bibliographically approved

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Daneshtalab, Masoud

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CiteExportLink to record
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  • apa
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