Searching strategies for target discovery in wireless networks

In this paper, we address a fundamental problem concerning the optimal searching strategy in terms of searching cost for the target discovery problem in wireless networks. In order to find the nearest k targets from a total of m members using the minimum cost, should we search the network only once, or should we apply a so-called “expansion ring scheme?” Specifically, how many searching attempts should we use, and how large should each searching area be? To answer these questions, we provide a generic model and formulate the expected cost as a function of the parameters of the number of searching attempts n and the searching area for each attempt, Ai. Using this model, we propose several algorithms to determine the optimal parameters, either pre-calculated or performed online. We experiment with these algorithms on general wireless network scenarios and show that our algorithms perform consistently close to optimal and better than other heuristic schemes. The desired performance is achieved by adapting the searching radius to estimates of network parameters such as the total number of nodes and the total number of targets.