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Mathematics 2019, 7(4), 315; https://doi.org/10.3390/math7040315

Optimal Task Allocation in Wireless Sensor Networks by Means of Social Network Optimization

Dipartimento di Energia, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy
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Received: 5 March 2019 / Revised: 22 March 2019 / Accepted: 25 March 2019 / Published: 28 March 2019
(This article belongs to the Special Issue Evolutionary Algorithms in Intelligent Systems)
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Abstract

Wireless Sensor Networks (WSN) have been widely adopted for years, but their role is growing significantly currently with the increase of the importance of the Internet of Things paradigm. Moreover, since the computational capability of small-sized devices is also increasing, WSN are now capable of performing relevant operations. An optimal scheduling of these in-network processes can affect both the total computational time and the energy requirements. Evolutionary optimization techniques can address this problem successfully due to their capability to manage non-linear problems with many design variables. In this paper, an evolutionary algorithm recently developed, named Social Network Optimization (SNO), has been applied to the problem of task allocation in a WSN. The optimization results on two test cases have been analyzed: in the first one, no energy constraints have been added to the optimization, while in the second one, a minimum number of life cycles is imposed. View Full-Text
Keywords: wireless sensor networks; task allocation; stochastic optimization; social network optimization wireless sensor networks; task allocation; stochastic optimization; social network optimization
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Niccolai, A.; Grimaccia, F.; Mussetta, M.; Zich, R. Optimal Task Allocation in Wireless Sensor Networks by Means of Social Network Optimization. Mathematics 2019, 7, 315.

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