An Enhanced Routing Technique for Wireless Sensor Networks

Abstract

In recent years, wireless sensor networks (WSNs) have emerged as one of the most promising technology in our day to day life. WSNs have played a major role in applications such as tracking and monitoring in remote environments. There are various open issues in WSNs such as limited network lifetime, higher energy consumption, handling mobility of SNs, link failures and lower network performance due to dynamicity of operations. Designing energy efficient protocols for routing of data events is a major challenge due to the dynamic topology and distributed nature of WSNs. Route selection is a critical activity while transmitting messages from source to destination. Major amount of energy is consumed during the data transmission. Hierarchical routing architecture has proved to be extremely effective in solving the problem of excessive energy consumption. In cluster based routing protocols cluster heads are overburdened with the task of data forwarding to BS which causes unbalanced energy consumption. Novel cluster head selection is an important task which needs emphasis in order to reduce energy consumption and network lifetime enhancement. Hardware restrictions necessitate the requirement of energy efficient design and development of hierarchical routing protocols. This thesis is an effort towards this direction. In this thesis three protocols have been proposed which are: “An energy efficient load balanced cluster based routing using ACO (LB-CR-ACO)”, “An Unequal clustering using meta-heuristic Ant Colony Optimization (MHACO-UC) and An Enhanced Energy Proficient Clustering (EEPC) Algorithm for relay selection in heterogeneous WSNs. The first protocol “An energy efficient load balanced cluster based routing using Ant Colony Optimization (LB-CR-ACO)” is an effort to enhance network life time. It performs optimal clustering based on cluster head selection weighing function. The cluster formation utilizes various parameters like remaining energy of the nodes, received signal strength indicator and node density. The priority weights are assigned among these parameters. The presented protocol also performs a dynamic selection of optimal cluster head periodically which conserves energy, thereby utilizing network resources in an efficient and balanced manner. The optimal route construction is done using ACO in steady state phase for multi hop data transfer. It has been observed through simulations that proposed protocol exhibits better performance for number of alive nodes, energy consumption per round than its peer protocols. The second protocol is “Meta-heuristic ant colony optimization based unequal clustering (MHACO-UC) for wireless sensor networks". The protocol's main focus is to deal with the issues related to unbalanced energy consumption, network performance dynamics. Apart from the optimal cluster head selection this protocol emphasizes on unequal clustering to maintain a fair balance between intra and inter cluster communication load. The initialization of nodes nearer to Base Station (BS) as relay nodes increases the performance. Meta-Heuristic Ant Colony Optimization approach selects the optimal path between the nodes which increases the packets delivered to destination. Unequal clustering, novel CH selection, prediction of optimal path using metaheuristic ant colony optimization reduces the energy consumption effectively. The simulation and comparative analysis of proposed Meta- Heuristic Ant Colony Optimization based Unequal Clustering (MHACOUC) with the existing unequal clustering approaches on the basis of various performance parameters such as packet delivery ratio (PDR), number of packets sent to the BS, energy consumption and residual energy shows the effectiveness of proposed work in WSN applications. The third protocol is "An Enhanced Energy Proficient Clustering (EEPC) algorithm for relay selection in heterogeneous WSNs". It reduces the energy consumption in the field of sensor tracking events. The main focus of the presented work is to handle mobility of SNs and to deal with link failures. In this work, network is constructed with both static and mobile nodes, which are placed in grid structures, and deployed randomly. The nodes select their cluster head (CH) on the basis of their associated placement and energy level. The mobile nodes transmit the data to the CH. Generally, CH transmits the sensing information to the base station. The proposed approach introduces the concept of finding relay nodes, which are static nodes. The EEPC algorithm selects the relay nodes based on its velocity and location by calculating particle fitness value. The selected intermediate relay static nodes transmit the collected sensing information to the Base Station (BS) using sensor data fusion technique. The link fault could be predicted based on the deviation value. The simulation results show that the proposed approach minimizes the energy depletion and hence enhances the network lifetime.