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Abstract: We propose a method for increasing incentives for sites to host arbitrary mobile agents in which mobile agents purchase their computing needs from host sites. We present a scalable market-based CPU allocation policy and an on-line algorithm that plans a mobile agent's expenditure over a multihop ordered itinerary. The algorithm chooses a set of sites at which to execute and computational priorities at each site to minimize execution time while preserving a prespecified budget constraint. We present simulation results of our algorithm to show that our allocation policy and planning algorithm scale well as more agents are added to the system.

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   Jonathan Bredin, David Kotz, and Daniela Rus, "Mobile-Agent Planning in a Market-Oriented Environment." Dartmouth Computer Science Technical Report PCS-TR99-345, May 1999.

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