A softbot-based interface to the Internet
Communications of the ACM
Data model and query evaluation in global information systems
Journal of Intelligent Information Systems - Special issue: networked information discovery and retrieval
Query reformulation for dynamic information integration
Journal of Intelligent Information Systems - Special issue on intelligent integration of information
Integrating heterogeneous databases: lazy or eager?
ACM Computing Surveys (CSUR) - Special issue: position statements on strategic directions in computing research
A Hands-On Look at Java Mobile Agents
IEEE Internet Computing
MA '98 Proceedings of the Second International Workshop on Mobile Agents
Scaling heterogeneous databases and the design of Disco
ICDCS '96 Proceedings of the 16th International Conference on Distributed Computing Systems (ICDCS '96)
Planning executing sensing and replanning for information gathering
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Dynamic information retrieval optimization using mobile agents
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Using agents for multi-target search on the Web
Proceedings of the 2003 ACM symposium on Applied computing
A mobile agent approach for global database constraint checking
Proceedings of the 2004 ACM symposium on Applied computing
Mobile Agents for Distributed and Heterogeneous Information Retrieval
Information Retrieval
Using ECA rules to implement mobile query agents for fast-evolving pure P2P database systems
Proceedings of the 6th international conference on Mobile data management
Guest Editorial: Agent-based information fusion
Information Fusion
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The heterogeneous, distributive and voluminous nature of many government and corporate data sources impose severe constraints on meeting the diverse requirements of users who analyze the data. Additionally, communication bandwidth limitations, time constraints, and multiplicity of data formats impose further restrictions on users of these distributed data sources. What is required is a reliable, robust, and efficient data retrieval technique that can access data from distributed data sources while maintaining the autonomy of individual sources. In this paper, we present an Agent-based Complex QUerying and Information Retrieval Engine (ACQUIRE) for large, heterogeneous, and distributed data sources. ACQUIRE acts as a softbot or interface agent by presenting users with the appearance of a single, unified, homogenous data source, against which users can pose high-level declarative queries. ACQUIRE translates each such user query into a set of sub-queries by employing a combination of planning and traditional database query optimization techniques. For each sub-query, ACQUIRE then spawns a corresponding mobile agent, which retrieves data from the appropriate data source. These mobile agents carry with them data-processing code that can be executed at the remote site, thus reducing the size of data returned by the agent. When all mobile agents have returned, ACQUIRE filters and merges the retrieved data and presents the results to the user. Validation experiments on simulated NASA Distributed Active Archive Centers (DAACs) have demonstrated that complex queries can be effectively decomposed and retrieved by this approach, resulting in the twin benefits of improved ease of use and significantly reduced query retrieval times.