Efficient sequential-hierarchical deployment strategy for heterogeneous sensor networks

An efficient strategy solution is developed for a specific deployment problem in which different types of sensors are required to simultaneously cover the same area of interest. The deployment goal is to select the sensor positions and orientations in such a way that the sensor network coverage is optimized. A general challenge within resource allocation problems is that, even with small-scale sensor networks, the number of possible final deployment solutions expands very fast and the problem becomes intractable. We assume that it is acceptable to trade solution optimality against algorithm speed. In this case, algorithms can be based on greedy and/or divide-and-conquer principles, which both results in good computational efficiency. We developed an efficient algorithm in three steps. Firstly, we developed a global search algorithm, but with improvements that reduce the search space significantly without losing optimality. Secondly, we transformed the global algorithm into a sequential and a hierarchical algorithm for more efficiency at the cost of optimality. Thirdly, we combine the sequential and hierarchical principles into one algorithm which results in even higher efficiency. In the end, the algorithms are evaluated with the use of an extensive testing scheme which generates many random cases for solving.