Abstract. We introduce SensorDCSP, a naturally distributed benchmark based on a real-world application that arises in the context of networked distributed systems. In order to study the performance of Distributed CSP (DisCSP) algorithms in a truly distributed setting, we use a discrete-event network simulator, which allows us to model the impact of different network traffic conditions on the performance of the algorithms. We consider two complete DisCSP algorithms: asynchronous backtracking (ABT) and asynchronous weak commitment search (AWC). In our study of different network traffic distributions, we found that, random delays, in some cases combined with a dynamic decentralized restart strategy, can improve the performance of DisCSP algorithms. More interestingly, we also found that the active introduction of message delays by agents can improve performance and robustness, while reducing the overall network load. Finally, our work confirms that AWC performs better than ABT on satisfiable instances. However, on unsatisfiable instances, the performance of AWC is considerably worse than ABT.
In the context of distributed constraint satisfaction problems (DCSPs), Fernandez et al. REF have also studied the effect of communication network data load on DCSP algorithms and found that including random delays in message delivery times can in fact improve the performance and robustness of AWC.
Communication and Computation in Distributed CSP Algorithms
In Distributed Sensor Networks: A Multiagent Perspective, Series on Multiagent Systems
Computer Science