Energy Efficient Scheduling In Wireless Sensor Networks For Periodic Data Gathering

Energy efficient scheduling in wireless sensor networks for periodic data gathering

Abstract:

Nodes in the wireless sensor networks (WSNs) are battery operated thus, the efficient use of the node’s energy during wireless communication is crucial for the long battery life. This paper addresses the challenges in energy efficient data aggregation and transmission scheduling for each node by using time Division Multiple Access (TDMA). We have a tendency to introduce multi-channel TDMA scheduling algorithms with the objective of minimizing the total energy consumption in the network. The proposed algorithms utilize multiple radio channels to bestow efficient scheduling while eliminating collisions and overhearing. First, we formulate an integer linear programming (ILP) algorithm that finds the minimum sure for the network’s energy consumption. Then we propose a near-optimal heuristic algorithm based on backtracking, which uses memorization to refuse the suboptimal schedules. Subsequently, we propose a computationally efficient heuristic algorithm by victimization Langford set generation. The algorithm reduces the energy consumption in each timeslot while avoiding revisiting the same timeslot. We conducted extensive simulations to evaluate three projected algorithms. The simulations results demonstrate that the proposed heuristic algorithms provide performance admire the optimum results of the ILP algorithm and reduce the magnitude of computation time.