LAUSR

Abstract Multi-hop and multi-sink wireless sensor networks have the potential to provide network performance through efficient data exchanges. In multi-sink phenomena, clusters of nodes are defined using distance vector and thereby specific node that lies at the center of the cluster is identified as a sink. The performance of multi-hop and multi-sink wireless networks is significantly affected by sink node placement and routing of data packets within the cluster. In this paper, the authors propose an application of three different algorithms to improve the performance of a sensor network in terms of sink node placement along with route construction and optimization using nature-inspired computational methods. Furthermore, at potential relays, opportunistic coding is used to reduce the number of transmissions. Hence, the proposed implementation integrates three algorithms, which combines the merits of each for significant enhancement in data transmission. First is the placement of sink node through particle swarm optimization, second is the route construction from sensors and sink of the particular cluster using minimum wiener spanning tree, which further optimized by artificial bee colony technique and third is opportunistic packet amalgamation before transmitting to neighbors. Finally, the proposed work is evaluated and validated for coded transmissions and non-coded transmissions through comparisons of evaluation metrics like throughput, energy conservation, packet delivery ratio and average hop-count between sensor and sink node.