Routing optimization in mobile wireless sensor networks using soft computing techniques

Abstract

The Mobile Wireless Sensor Networks (MWSN) has a great deal of node power which affects the quality of various service parameters. The sensor nodes have been built with fixed energy and spent a certain amount of energy for each data transmission leading to energy loss. However, the nodes transmit through cooperative communication to complete any data transfer. There are some routing approaches available for the mobile wireless sensor networks, but the cluster based routing has a significant impact on achieving the required performance. In cluster based routing, the nodes of the network transfer the data packets to a gateway for the group of nodes to reach any destination which is not present in the group. A new bee colony optimization technique is used to support efficient routing in mobile wireless sensor networks. The wireless sensor networks have been considered with clustering mobile sink nodes which collects information available at the sensor nodes located at various locations of the network. The sensor nodes post their recent updates and they are present at neighbor geographic regions. Then, an inter-cluster routing scheme is developed for the cluster members to route the collected messages based on fuzzy logic. A mobility management technique is proposed for Mobile Wireless Sensor Networks (MWSN) by using Hidden Markov Model (HMM). Here, the mobility of any node is predicted using the metrics Received Signal Strength Indication (RSSI), Link Loss, and anticipated Expected Transmission Count (ETX). Initially, a prediction timer is started during which the RSSI and Link iv Loss metrics are measured. newline