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. Namely, due to the heterogeneous nature of the environments in which agents are executed, agent-based programs must 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 runtime adaptation and agent specialization for improving the performance of agent-based programs. 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.
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