An autonomous agent approach to query optimization in stream grids

  • Authors:
  • Saikat Mukherjee;Srinath Srinivasa;Krithi Ramamritham

  • Affiliations:
  • International Institute of Information Technology, Bangalore, India;International Institute of Information Technology, Bangalore, India;Indian Institute of Technology, Bombay, India

  • Venue:
  • Proceedings of the International Conference on Management of Emergent Digital EcoSystems
  • Year:
  • 2009

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Abstract

Stream grids are wide-area grid computing environments that are fed by a set of stream data sources. Queries arrive at the grid from users and applications external to the system. The kind of queries considered in this work are long-running continuous (LRC) queries, that we also term as "open-world" queries. These queries are neither short-lived nor infinitely long lived. They live long enough to make the prospect of multi-query optimization meaningful. But queries may also terminate at any time, requiring re-optimization of the query plans. The queries are "open" from the grid perspective as the grid cannot control or predict: (1) arrival of a query with time, location, required data and, (2) query revocations. Query optimization in such an environment has two major challenges: (a) optimizing in a multi-query environment and (b) continuous optimization due to new query arrivals and revocations. As generating a globally optimal query plan is an intractable problem, this work explores the idea of emergent optimization, where globally optimal query plans emerge as a result of local autonomous decisions taken by the grid nodes. Drawing concepts from evolutionary game theory, grid nodes are modeled as autonomous agents that seek to maximize a self-interest function using one of a set of different strategies. Grid nodes change strategies in response to variations in query arrival and revocation patterns. Changing of strategies is also autonomously decided by each grid node based on how its strategy is faring with respect to other strategies in the grid.