Genetic Algorithm Based Threshold Sensitive Routing Protocol for Wireless Sensor Network

Tigga, Anjali Priyanka (2015) Genetic Algorithm Based Threshold Sensitive Routing Protocol for Wireless Sensor Network. MTech thesis.



Wireless sensor network (WSN) is an advancing technological field of wireless communication with a wide range of applications. It comprises of geographically wide-spread unattended micro-sensors. Such autonomous characteristics of nodes have led to design of various routing protocols which encounter performance augmentation with respect to energy efficiency and network lifetime. Design of routing protocols is highly contingent on the application which uses it. However, hierarchical cluster-based structure is ascertained to yield considerable potential. Rooted from it is the widely known cluster-based LEACH protocol. Considerable contribution is also done in protocols based upon genetic algorithms such as ERP and HCR. They tend to extend network lifetime but are liable to attainable modifications which can direct to better performances. The aim of this paper is to acquire effective fitness function to construct clusters efficiently which can operate with high stability and attain low energy dissipation over the rounds of transmission. Another moderation is the route configuration for aggregated data to be transmitted along the cluster heads only. Simulation and comparison with LEACH, TEEN and ERP shows that GA-TSRP is significantly stable for a number of transmission rounds. And thus, energy utilized is spread uniformly over an adequate duration of sensor network lifetime.

Item Type:Thesis (MTech)
Uncontrolled Keywords:Genetic Algorithm, Hierarchical Clustering, Stability Period, Energy Efficiency, Data Aggregation
Subjects:Engineering and Technology > Computer and Information Science > Wireless Local Area Network
Divisions: Engineering and Technology > Department of Computer Science
ID Code:7788
Deposited By:Mr. Sanat Kumar Behera
Deposited On:16 Sep 2016 17:52
Last Modified:16 Sep 2016 17:52
Supervisor(s):Sahoo, M N

Repository Staff Only: item control page