A Local Search Algorithm Based on Clonal Selection and Genetic Mutation for Global Optimization
SBRN '10 Proceedings of the 2010 Eleventh Brazilian Symposium on Neural Networks
Repairing sensors strategies in fault-tolerant wireless sensor networks
Proceedings of the 8th ACM Symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
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Generally, the Quality of Service (QoS) in a wireless sensor network (WSN) is measured by the sensing area coverage degree and the connectivity between the deployed sensors. To conserve and protect these QoS parameters, we have used a limited number of mobile maintainer robots to handle the eventual network failed sensors. In this paper, we have introduced two Centralized Preventive Maintenance Strategies (CPMS) dedicated for the WSNs. Indeed, with an analytical energy model representing the energy consumption of each network's node, a central manager robot estimates the expected sensors failures to be repaired by the available robots before the total depletion of their energies. To schedule the available maintainer robots, we have introduced two Centralized Preventive Maintenance Strategies (CPMS) for WSNs with two scheduling approaches used to obtain the convenient maintainer robot scheduling for a fixed number of anticipated failures (fixed window): (i) CPMS with the Nearest available robot heuristic Backtracking robot scheduling algorithm (CPMS-NB) and (ii) CPMS with a Genetic robot scheduling Algorithm (CPMS-GA). Simulation results show that the CPMS-GA scheduling algorithm is more complex than that of CMSA-NB, but it gives a better network dysfunction time with a minimal robot traveling distance.