The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
An Autonomous Agent Approach to Query Optimization in Stream Grids
|
|
Author(s): Saikat Mukherjee (International Institute of Information Technology, India), Srinath Srinivasa (International Institute of Information Technology, India)and Krithi Ramamritham (Indian Institute of Technology, India)
Copyright: 2012
Pages: 24
Source title:
Intelligent and Knowledge-Based Computing for Business and Organizational Advancements
Source Author(s)/Editor(s): Hideyasu Sasaki (Chinese University of Hong Kong, Hong Kong), Dickson K.W. Chiu (The University of Hong Kong, Hong Kong), Epaminondas Kapetanios (University of Westminster, UK), Patrick C.K. Hung (University of Ontario Institute of Technology, Canada), Frederic Andres (National Institute of Informatics, Japan), Ho-fung Leung (The Chinese University of Hong Kong, Hong Kong)and Richard Chbeir (Bourgogne University, LE2I CNRS, France)
DOI: 10.4018/978-1-4666-1577-9.ch016
Purchase
|
Abstract
Stream grids are wide-area grid computing environments that are fed by a set of stream data sources, and Queries arrive at the grid from users and applications external to the system. The kind of queries considered in this work is long-running continuous (LRC) queries, which are neither short-lived nor infinitely long lived. The queries are “open” from the grid perspective as the grid cannot control or predict the arrival of a query with time, location, required data and query revocations. Query optimization in such an environment has two major challenges, i.e., optimizing in a multi-query environment and 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, which is also autonomously decided by each grid node.
Related Content
|
Shaun Ruysenaar.
© 2021.
26 pages.
|
|
Rasheed O. Azeez.
© 2021.
13 pages.
|
|
Ziska Fields.
© 2021.
28 pages.
|
|
Chunfang Zhou, Lars Bo Henriksen, Søren Kerndrup.
© 2021.
15 pages.
|
|
Cookie M. Govender.
© 2021.
26 pages.
|
|
Crystal Yolande Herborn, Frances Scholtz.
© 2021.
23 pages.
|
|
Ziska Fields, Zainab Mahammad Abdullah, Aidah Nakayiwa Musisi, Nadine Kirsten Mitchley.
© 2021.
23 pages.
|
|
|