Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Hardness Results for the Power Range Assignmet Problem in Packet Radio Networks
RANDOM-APPROX '99 Proceedings of the Third International Workshop on Approximation Algorithms for Combinatorial Optimization Problems: Randomization, Approximation, and Combinatorial Algorithms and Techniques
Strong Minimum Energy Topology in Wireless Sensor Networks: NP-Completeness and Heuristics
IEEE Transactions on Mobile Computing
Maximum lifetime routing in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Journal of Global Optimization
Wireless sensor network survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Amdahl's Law in the Multicore Era
Computer
GSA: A Gravitational Search Algorithm
Information Sciences: an International Journal
Introduction to Algorithms, Third Edition
Introduction to Algorithms, Third Edition
Relay Node Deployment Strategies in Heterogeneous Wireless Sensor Networks
IEEE Transactions on Mobile Computing
Fault-Tolerant Relay Node Placement in Heterogeneous Wireless Sensor Networks
IEEE Transactions on Mobile Computing
IEEE Transactions on Evolutionary Computation - Special issue on preference-based multiobjective evolutionary algorithms
Coverage problems in sensor networks: A survey
ACM Computing Surveys (CSUR)
IEEE Transactions on Wireless Communications
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Relay node positioning in wireless sensor networks by means of evolutionary techniques
AIS'12 Proceedings of the Third international conference on Autonomous and Intelligent Systems
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At this time, Wireless Sensor Networks (WSNs) are widely used in many fields. This kind of network has some attractive features that have promoted their use, such as the absence of wires and the use of low-cost devices. However, WSNs also have important shortcomings that affect some features like energy cost and quality of service. In this paper, we optimize traditional static WSNs (a set of sensors and a sink node) by means of adding routers to simultaneously optimize a couple of important factors: energy consumption and average coverage. This multiobjective optimization problem was solved in a previous work using two genetic algorithms (NSGA-II and SPEA2) which had an important limitation: the computing time was very high and then, to address complex instances was difficult. In this paper, both algorithms are parallelized using OpenMP in order to reduce the computing time, and a more realistic data set is included. The results obtained are analyzed in depth from both multiobjective and parallel viewpoints. A Quite good efficiency is obtained with a wide range of processing cores, observing that NSGA-II provides the best results in small and medium instances, but in the largest ones the behavior of both algorithms is similar.