Single and Group Agent Migration: Algorithms, Bounds, and Optimality Issues

Recent embedded middleware platforms enable the structuring of an application as a set of collaborating agents deployed on various nodes of the underlying wireless sensor network (WSN). Of particular importance is the network cost incurred due to agent communication, which in turn depends on how the agents are placed within the WSN system. In this paper, we present two agent migration algorithms with the aim of minimizing the total network overhead. The first one takes independent single agent migration decisions, while the second one considers groups of agents for migration. Both algorithms work in a fully distributed fashion based on the knowledge available locally at each node, and can be used both for one-shot initial application deployment as well as for the continuous updating of agent placement. We also propose two methodologies to tackle the problem when WSN nodes have limited capacity. We show through theoretical analysis that one of our algorithms (called GRAL*) always results in an optimal placement, while for the rest of the algorithms, we derive approximation ratios pertaining to their performance. We evaluate the performance of our algorithms through a series of simulation experiments. Results show that group migration algorithms are superior compared to single agent migration algorithms with the performance difference reaching 34% for some settings.