Using Answer Set Programming to Improve Sensor Network Lifetime

Sensor network lifetime maximization can be solved using heuristic methods, but they produce only suboptimal sensor activity schedules. However, knowing the quality of these solutions, we can use methods for solving decision problems to find better solutions than these suboptimal ones. We apply an answer set programming (ASP) system to answer the question, "Is there a schedule of length k?" where k is at least one unit higher than the best schedule returned by the heuristic method. First, we convert the problem's constraints and a particular data instance into a high-level constraint language theory. Then we use a grounder for this language and a solver for the language of grounder's output to find a more extended schedule or determine that no such schedule exists. The paper presents the conversion rules and the experiments' results with one of the ASP tools for selected classes of the SCP1 benchmark.