Publication | Closed Access
Optimizing cluster-head selection in Wireless Sensor Networks using Genetic Algorithm and Harmony Search Algorithm
36
Citations
17
References
2012
Year
Unknown Venue
Energy ConsumptionCluster ComputingTopology ControlEnergy HarvestingEngineeringWireless Sensor SystemEnergy EfficiencyEdge ComputingWireless Sensor NetworksFirefly AlgorithmWsn NodesGenetic AlgorithmHarmony Search AlgorithmCluster-head SelectionInternet Of ThingsSensor OptimizationSensor ConnectivityMulti-hop Routing
Being an important factor in designing Wireless Sensor Networks, network lifetime depends on the energy of the sensor nodes which is limited by the battery of the node. Clustering is considered to be an energy management strategy in wireless sensor networks, and Leach is one of the most well-known clustering mechanisms. Random cluster selection in this method has lead to its inefficiency. In this paper we proposed two algorithms, GP-Leach and HS-Leach. We improved the energy consumption by partitioning the network and using the evolutionary algorithms for optimized cluster head selection considering WSN nodes' position information and residual energy. The simulation results performed in MATLAB shows that our proposed algorithms are more efficient and they increased the lifetime of the network.
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