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

Alessandro Niccolai, Francesco Grimaccia, Marco Mussetta, Alessandro Gandelli 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
Alessandro Gandelli: 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, 2020, vol. 8, issue 4, 1-21

Abstract: 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.

Keywords: wireless sensor networks; routing; Swarm Intelligence; Particle Swarm Optimization; Social Network Optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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