A genetic approach for the maximum network lifetime problem with additional operating time slot constraints
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METHODOLOGIES AND APPLICATION
A genetic approach for the maximum network lifetime problem with additional operating time slot constraints Ciriaco D’Ambrosio1
· Antonio Iossa2
· Federica Laureana1
· Francesco Palmieri2
© Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The maximum network lifetime problem is a well-known and challenging optimization problem which has been addressed successfully with several approaches in the last years. It essentially consists in finding an optimal schedule for sensors activities in a wireless sensor network (WSN) aiming at maximizing the total amount of time during which the WSN is able to perform its monitoring task. In this paper, we consider a new scenario in which, in order to monitor some locations in a geographical area, the sensors need to be active for a fixed amount of time, defined as operating time slot. For this new scenario, we derive an upper bound on the maximum lifetime and propose a genetic algorithm for finding a near-optimal node activity schedule. The performance evaluation results obtained on numerous benchmark instances show the effectiveness of the proposed approach. Keywords Wireless sensor networks · Maximum network lifetime · Time slot · Genetic algorithm
1 Introduction Wireless Sensor Networks (WSNs) represent nowadays one of the most advanced technologies able to collect and process information in heterogeneous contexts (Hu et al. 2011; Bathiya et al. 2016; Cardei et al. 2005). WSNs are generally composed of low-cost devices (sensors) which collect information about the surrounding space (sensing area) that usually contains specific targets of interest. While advancements in wireless communications and microelectromechanical systems allowed the adoption of sensor networks in many scenarios, battery technologies experienced much smaller improvements over time. Indeed, energy consumption is still Communicated by V. Loia.
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Ciriaco D’Ambrosio [email protected] Antonio Iossa [email protected] Federica Laureana [email protected] Francesco Palmieri [email protected]
1
Department of Mathematics, University of Salerno, Fisciano, SA, Italy
2
Department of Computer Science, University of Salerno, Fisciano, SA, Italy
one of the most important issues that has generated a great research interest, especially in the last years due to the diffusion of Internet of Things (IoT) applications and cyber physical systems. In more detail, one of the most important aspects considered to face such an issue concerns scheduling sensors activities. The sensors are generally powered by batteries that keep them fully functional only for a limited amount of time. Given a WSN deployed with such sensors, the determination of an efficient scheduling of their operational states (idle or active) could help in overcoming the limitations in terms of battery duration which characterizes each individual sensor. Usually the deployed sensors provide redundant coverage so that keeping them all simultaneously in an active state causes only a waste of energy witho
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