Implementation and advancement of LEACH protocol using NS2
AbstractWireless Sensor Network is a modern era technique of computing, which is in demand and been using by the modern society for multiple purposes i.e., from connectivity to security. Multiple Cluster-Based Routing techniques has been proposed and been researched up till now, but only few of them are kind of successful. Most of the techniques are emphasized on Cluster-Head Election techniques, ignoring how to be done? Furthermore they tend to use non-realistic parameters and assumptions for it. Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. In this paper, we develop and analyze low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality In this paper, we are proposing Enhancement of LEACH Protocol using Particle Swarm Optimization Techniques [PSO], followed by Linear Programming Formulations to the problems of Clustering and Routing. Clustering Algorithms find optimal set of Cluster Heads that maximizes energy efficiency, cluster quality and network coverage. Extensive simulations on 100 independent nodes are done, cross referenced, evaluated and compared against well-known cluster based sensor network protocols. Results show that proposed protocol performs better than existing available protocols in terms of performance metrics. The simulation of proposed protocol is done using NS-2 Simulator.
How to Cite
SAWANT, Gopal. Implementation and advancement of LEACH protocol using NS2. International Journal Of Emerging Technology and Computer Science, [S.l.], v. 2, n. 2, june 2017. ISSN 2455-9954. Available at: <https://aspirepublishers.com/index.php/ijetcs/article/view/124>. Date accessed: 31 may 2020.