Heuristic algorithm for finding boundary cycles in location-free low density wireless sensor networks

Abstract

Wireless sensor networks (WSNs) comprise a large number of sensor nodes, which are spread out within a region to be monitored and communicate using wireless links. In some WSN applications, recognizing boundary nodes is important for topology discovery, geographic routing, tracking and guiding. In this paper, we study the problem of identifying the boundary nodes of a WSN. In a WSN, close-by nodes can establish direct communications with their neighbors and have the ability to estimate distances to nearby nodes, but not necessarily the true distances. Our objective is to find the boundary nodes by using only the connectivity relation and neighbor distance information without any other knowledge of node locations. Moreover, our main aim is to design a distributed algorithm that works even when the average degree is low. We propose a heuristic algorithm to find the boundary nodes which are connected in a boundary cycle of a location-free, low density (average degree 5-6), randomly deployed WSN. We develop the key ideas of our boundary detection algorithm in the centralized scenario and extend these ideas to the distributed scenario. The distributed implementation is more realistic for real WSNs, especially for sparse networks when all local information cannot be collected very well due to sparse connectivity. In addition, the distributed implementation can tolerate faults by recomputing the boundary locally when a boundary node is faulty. Simulations in ns-2 show that the distributed implementation outperforms the centralized one with higher quality of boundaries.