Routing in Wireless Sensor Networks Using Soft Computing

Abstract

Wireless sensor networks are the evolutionary self-organizing multi-node networks. Due to dynamic network conditions and stochastically varying network environments, routing in WSNs is critically affected and needs to be optimized. The routing strategies developed for WSNs must be efficient to make it an operationally self-configurable network. For this we need to resort to near shortest path evaluation. Therefore, some soft computing approaches that can calculate the near shortest path available in an affordable computing time are required. WSNs have a high computational environment with limited and precise transmission range, processing, and limited energy sources. The sever power constraints strongly affect the existence of active nodes and hence the network lifetime. So, here, the authors use the power of soft computing because the potential features of soft-computing (SC) approach highly address their adaptability and compatibility to overwhelm the complex challenges in WSNs.