ECABBO: Energy-efficient clustering algorithm based on Biogeography optimization for wireless sensor networks

FLAG: fuzzy logic augmented game theoretic hybrid hierarchical clustering algorithm for wireless sensor networks

“…In this work, election of CHs based on ratio between residual energy of sensor node and average energy of the network. A stable election protocol(SEP) for heteroge- Few of the meta-heuristic algorithms for clustering are described in [7,10,11,19]. The genetic algorithm based clustering algorithm is proposed in [7].…”

“…This technique uses residual energy and distance to the base station for fitness function design. In [19], the authors adopted Biogeography-based optimization for clustering. This algorithm elects appropriate CH using residual energy, distance to base station, and distance to its member nodes.…”

Optimization of Submodularity and BBO-Based Routing Protocol for Wireless Sensor Deployment

“…This causes either the nodes far away from the base station to be selected as the cluster head or the nodes far away from the cluster head to die prematurely [22]. In [23], Simon proposed the biogeography-based optimization algorithm with advantages of simple operation, few parameters, and high search accuracy [24]. In [25], Pal and others used the Biogeography-Based Optimization (BBO) algorithms to select cluster heads and cluster nodes, and obtained good energy efficiency.…”