Adaptation and Specialization for High Performance Mobile Agents
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Mobile agents as a new design paradigm for distributed computing potentially permit network applications to operate across dynamic and heterogeneous systems and networks. Agent computing, however, is subject to inefficiencies due to the complexities of the environments in which agents are deployed, which requires agent-based programs to rely on underlying agent systems to mask some of those complexities, by using system-wide, uniform representations of agent code and data and by 'hiding' the volatility in agents' 'spatial' relationships. This paper explores two approaches for improving the performance of agent-based programs: (1) runtime adaptation and (2) agent specialization. Our general aim is to enable programmers to employ these techniques to improve program performance without sacrificing the fundamental advantages promised by mobile agent programming. The specific results in this paper demonstrate the beneficial effects of agent adaptation both for a single mobile agent and for several cooperating agents, using the adaptation techniques of agent morphing and agent fusion. Experimental results are attained with two sample high performance distributed applications, derived from the scientific domain and from sensor-based codes, respectively.