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Enhanced variants of CTP for improved data delivery ratio and energy consumption

Efficient Data Aggregation in Wireless Sensor Network(WSN) is a challenging task due to highly application specific nature, dynamic topology, spatiotemporal traffic, and stringent constraints on resources available, including Energy. CTP has been one of the important protocol being used for data aggregation in WSN. However, CTP suffers from several drawbacks like frequent update of its various tables due to variation in the quality of link or inconsistent behavior of neighbor nodes which are part of path for data transmission, repeated incoming link quality calculation overhead etc. The work being presented in this paper aims at improving the overall performance of CTP and specifically the Data Delivery Ratio and Energy Consumed parameters, by attempting to reduce the number of updates to various tables at various layers due to variations in the link quality and node behavior which are present on collection tree. In this regard, this paper proposes two new approaches to the original CTP. In the First Approach, variations in the quality of the link over a given time period in the past is analyzed, use this information in reducing the frequency of updating various tables in various layers. Second Approach, analyzes the behavior of node participating in data transmission over a set of packets sent to it in the past in order to reduce the frequency of updating various tables in various layers. Simulation results, result analysis, and comparison with original CTP protocol presented in this paper show that, First Approach proposed yields increased improvement in overall performance, 8% increase in Data Delivery Ratio, and 2% improvement in Energy Consumed respectively. Similarly, Second Approach proposed too, indicate that there is an increased improvement in overall performance, 9% increase in Data Delivery Ratio, and 1% improvement in Energy Consumed by each node respectively. The paper is concluded with mentioning of future directions for research.