Data Aggregation and Life Time Improvement in wireless Sensor Networks using Dynamic Clustering

Abstract

Wireless sensor network is an emerging area of research due to vulnerability of sensing information from not approachable areas. In WSN sensor nodes have been deployed for sensing information and transmit this information to base station so that various decisions can be developed. In the processing of WSN data aggregation and energy consumption are major issues. In this paper a new approach has been purposed for data management and energy consumption reduction using dynamic clustering and avoidance ofredundant information transmission over the network. This approach use check sum approach for data redundancy checking and discard redundant or repeated information. This approach provides better results than previous approaches.

Optimal data aggregation tree in wireless sensor networks based on improved river formation dynamics

“…To resolve these issues and to reduce the energy consumption in communication, data aggregation is considered as an effective technique. [1][2][3][4] The raw data redundancy can be eliminated at aggregation points, and only useful information is retrieved and sent to the base station (BS). 5 Therefore, the numbers of transmitted and received packets at the BS are reduced.…”

“…Therefore, energy dissipation and high volume traffics are the costs of duplicated data transmission. To resolve these issues and to reduce the energy consumption in communication, data aggregation is considered as an effective technique . The raw data redundancy can be eliminated at aggregation points, and only useful information is retrieved and sent to the base station (BS) .…”