Lifetime Enhancement of Wireless Sensor Network with Data Aggregation

Abstract

Nowadays wireless sensor networks (WSN) are widely used in various domains such as disaster relief operation, military applications, environmental monitoring, home applications, structural monitoring, agricultural sector, health applications etc. Energy saving is the rudimentary provocation in wireless sensor networks. The energy of the WSNs can be conserved in many ways such as: duty cycling of nodes, clustering, energy efficient routing, data energy etc. The data aggregation is one of the approach which is used to conserve the energy of the WSN nodes by removing redundant packets from the collected packets. This helps in increasing the network lifetime and on the other hand, it saves the network bandwidth as well. Data aggregation algorithms are broadly classified on the basis of their data collection strategy into three types. In this thesis we have attempted to present a broader review of the data aggregation algorithms on the basis of their categorization as discussed earlier. Moreover, we have also proposed a centralized data aggregation algorithm that is Levelling and Self Localization based Clustering(LSLC) algorithm. This algorithm allows the nodes to self-localized themselves and also the data aggregation is performed at multiple levels which reduces the energy consumption of the nodes. This also reduces the number of packets sent to the base station and thereby enhances the network lifetime. In addition to this, the LSLC algorithm is compared with different existing data aggregation algorithms in terms of network lifetime, residual energy, packet to delivery ratio, latency, packet sent to the base station. Initially, the simulation results are obtained to analyze the impact of different metrics like increasing the number of nodes in the same area, with and without data aggregation etc. Then the LSLC is compared with some existing algorithm and it shows a considerable improvement in network lifetime, residual energy etc.