Efficient Data Collection in Interference-Aware Wireless Sensor Networks

Abstract

In this paper, we study the Minimum Latency Collection Scheduling (MLCS) problem in Wireless Sensor Networks (WSNs) adopting the two interference models: the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR). The main issue of the MLCS problem is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that all data from all nodes can be collected to a sink node without any collision or interference. First, we describe an approximation algorithm with O(1)-approximation ratio that works in both the interference models by yielding a schedule whose latency is bounded by O(n), where n is the number of nodes in the network. Then, we validate the latency performance of the proposed algorithm with various simulated networks, demonstrate the robustness of the algorithms with different network parameters, and discuss the effect of the interference models’ parameter values on the latency