Proposed Coordinating Multiple Sampling Tasks in Sensor Field Using Geometric Progression Algorithm for Efficient Data Collection in Wireless Sensor Networks

This paper proposes a new coordinating multiple sampling tasks in sensor field using geometric progression (CMSTGP) algorithm technique for enhancing the mobile sampling in wireless sensor networks. It is possible by the sensor nodes to have multiple sampling tasks, initiated by the same or different mobile objects, whose sampling regions overlap. Hence, it is desirable to have an efficient coordination mechanism such that overlapped regions need reply only once for the sampling tasks. A geometric progression technique is proposed in this research work as a coordination mechanism to coordinate the multiple sampling tasks to facilitate the rebroadcast scheme by consuming minimum energy. Experimental simulations have been conducted to estimate the performance of the proposed coordinating multiple sampling tasks in sensor field. The performance of the proposed algorithm has been analyzed in terms of average number of messages, overlap percentage and Throughput. From the simulated results it has been reported that the proposed CMSTGP algorithm reduces the overlapping percentage upto 8 % and increases the throughput of 70 % when compared with existing Band-based Directional Broadcast method.