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

Alessandro Niccolai, Francesco Grimaccia, Marco Mussetta and Riccardo Zich
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Alessandro Niccolai: Dipartimento di Energia, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy
Francesco Grimaccia: Dipartimento di Energia, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy
Marco Mussetta: Dipartimento di Energia, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy
Riccardo Zich: Dipartimento di Energia, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy

Mathematics, 2019, vol. 7, issue 4, 1-15

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.

Keywords: wireless sensor networks; task allocation; stochastic optimization; social network optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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