Performance analysis of hierarchical and nonhierarchical routing techniques in wireless sensor networks

Abstract

Wireless sensor network consisting of various tiny wireless sensor nodes that are equipped with transmission devices that require some amount of energy to transmit the data to other node(s). Most often we cannot charge or change the battery of sensor nodes during transmission. To preserve the longetivity of the network it is very challenging task to build a sensor node that require very little amount of energy for data transmission. Lifetime of wireless sensor network is directly proportional to the energy source of wireless sensor node. It is proved that 70% of energy consumption is caused during data transmission process [1]. In order to maximize the network lifetime we need to optimize data transmission process. An energy efficient routing algorithm may result in better network lifetime. This is the reason why routing techniques in wireless sensor network focus mainly on the accomplishment of power conservation. Most of the recent researches have shown various algorithms mainly designed to minimize energy consumption in sensor networks. Each routing mechanism has its advantages and disadvantages over energy efficiency. There is no single, best routing protocol that is suitable for all applications. Routing mechanism might differ depending on the application, network architecture and topologies. Routing algorithms/techniques have been classified in a number of ways by various researchers. There is no general classification is available till today. Some researchers [2, 3] have classified routing algorithms into three broad categories Datacentric Routing Protocols, Hierarchical Routing Protocols and Location-based Routing Protocols. In this Paper we are providing comparison of hierarchical and nonhierarchical routing technique. Using simulation and results we are showing that how hierarchical routing mechanism is better than a nonhierarchical technique in terms of network life time of entire sensor network and mean residual energy in sensor nodes of that network.