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Social Network Optimization for WSN Routing: Analysis on Problem Codification Techniques

Dipartimento di Energia, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy
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Mathematics 2020, 8(4), 583; https://doi.org/10.3390/math8040583
Received: 25 February 2020 / Revised: 1 April 2020 / Accepted: 9 April 2020 / Published: 14 April 2020
(This article belongs to the Special Issue Evolutionary Computation & Swarm Intelligence)
The correct design of a Wireless Sensor Network (WSN) is a very important task because it can highly influence its installation and operational costs. An important aspect that should be addressed with WSN is the routing definition in multi-hop networks. This problem is faced with different methods in the literature, and here it is managed with a recently developed swarm intelligence algorithm called Social Network Optimization (SNO). In this paper, the routing definition in WSN is approached with two different problem codifications and solved with SNO and Particle Swarm Optimization. The first codification allows the optimization algorithm more degrees of freedom, resulting in a slower and in many cases sub-optimal solution. The second codification reduces the degrees of freedom, speeding significantly the optimization process and blocking in some cases the convergence toward the real best network configuration. View Full-Text
Keywords: wireless sensor networks; routing; Swarm Intelligence; Particle Swarm Optimization; Social Network Optimization wireless sensor networks; routing; Swarm Intelligence; Particle Swarm Optimization; Social Network Optimization
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Niccolai, A.; Grimaccia, F.; Mussetta, M.; Gandelli, A.; Zich, R. Social Network Optimization for WSN Routing: Analysis on Problem Codification Techniques. Mathematics 2020, 8, 583.

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