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Title: Agent warehouse: A new paradigm for mobile agent deployment
Authors: Chi, C.-H. 
Sim, J.
Lam, K.-Y.
Issue Date: 2002
Citation: Chi, C.-H.,Sim, J.,Lam, K.-Y. (2002). Agent warehouse: A new paradigm for mobile agent deployment. Proceedings of the International Conference on Tools with Artificial Intelligence : 455-462. ScholarBank@NUS Repository.
Abstract: This paper describes a novel concept of agent warehouse. Non-mobile web agents typically operate from their users' computer and make request for data possibly from a very far location. In addition, much of this data will be irrelevant to the user, thus aggravating the bandwidth scarcity problem of the Internet. With current mobile agent paradigm, many of these problems such as bandwidth reduction and off-line autonomous negotiation are solved. However, this paradigm does have some significant limitations in its common deployment scenarios; system resource consumption, server collaboration, and accumulated agent size along the travelling path, etc. are some typical ones. These limitations are becoming more important when multiple visits to the same server host are required: updating time of host information is non-deterministic and the decision of negotiation is also not simultaneous. In this paper, the intermediate "proxy-like" agent warehouse is proposed to address these issues. The agent warehouse locates near the data sources and supports agent execution, thus allowing agents to operate much closer to these data sources and minimising the effect of discarded search results. In addition, it is able to provide more resources than a normal web server host does as it is dedicated to cater for agents. More importantly, even if the remote site does not support agent execution, the agent will still be able to complete its task through the warehouse. This changes the typical approach of how agents can be deployed by providing a more generic, flexible system environment for agents to execute.
Source Title: Proceedings of the International Conference on Tools with Artificial Intelligence
ISSN: 10636730
Appears in Collections:Staff Publications

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