Abstract

Two significant performance factors in Mobile Agent Planning (MAP) for distributed information retrieval are the number of mobile agents and the total execution time. Using fewer mobile agents results in less network traffic and consumes less bandwidth. Regardless of the number of agents used, the total execution time for a task must be kept to a minimum. A retrieval service must minimize both these factors for better system performance, and at the same time, it must be able to supply the required information to users as quickly as possible. In this paper, we propose heuristic algorithms, called Cost-Effective MAP (CEMAP), to minimize both the number of mobile agents and the total execution time under the condition that the turnaround time is kept to a minimum. Although these algorithms tend to slightly increase the planning cost, a simulation study shows that these algorithms enhance the system performance significantly. By adopting these algorithms, systems can maintain lower network traffic while satisfying the minimum turnaround time.

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