Placing Multiple Sinks in Time-Sensitive Wireless Sensor Networks using a Genetic Algorithm

Performance issues in Wireless Sensor Networks (WSNs) play a vital role in many applications. Often the maximum allowable message transfer delay must be bounded in order to enable time-sensitive applica- tions of WSNs like fire or intrusion detection systems. Hence, it is crucial to develop algorithms that minimize the worst-case delay in WSNs. In this work, we focus on the problem of placing multiple sinks such that the maximum worst-case delay is minimized while keeping the energy consumption as low as possible. For that purpose we develop an algo- rithm based on the Genetic Algorithm (GA) paradigm. To model and consequently control the worst-case delay of a given WSN we build upon the so-called sensor network calculus (a recent methodology introduced in (10)). In order to be able to assess the performance of the GA-based sink placement strategy we compare it to an exhaustive search algorithm as well as a Monte-Carlo search. All of the strategies are based on a dis- cretization of the originally continuous search space into a finite search space, which forms a contribution of our work of independent interest. In the performance comparison with the other strategies the GA exhibits a favourable behaviour with respect to the quality of the solutions found and the computational eort invested. It thus seems to be a good candi- date for addressing the problem of placing multiple sinks in large-scale time-sensitive WSNs.