Runtime efficiency of adaptive mobile software agents in pervasive computing environments

Abstract

Developing software that can support heterogeneous hardware platforms, adapt to dynamic highly variable environments and meet rapidly changing requirements is a challenge of pervasive computing. Dynamic adaptive software agents are a promising approach to develop software for such environments. We previously proposed an agent architecture which brings together features such as runtime adaptivity, agent mobility, platformindependence, context-awareness and lightweightness which are desirable in pervasive environments. In this paper, we propose and analyse a cost model of network load for our runtime adaptive mobile software agents. We compare our adaptive agents against standard non-adaptive mobile agents using this cost model. Subsequent experimental results demonstrate that our agents outperform non-adaptive mobile agents. We also propose and discuss further features which make our adaptive agent based software solution more suitable for pervasive computing environments.