X. Bai, G. Wang, Y. Ji, G.M.Marinescu, D.C. Marinescu, and L. Bölöni

Coordination in Intelligent Grid Environments


Cite as:

X. Bai, G. Wang, Y. Ji, G.M.Marinescu, D.C. Marinescu, and L. Bölöni. Coordination in Intelligent Grid Environments. Proceedings of the IEEE, 93(3):613–630, 2005.

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Abstract:

A computational grid is a complex system. The state space of a complex system is very large and it is infeasible to create a rigid infrastructure implementing optimal policies and strategies which take into account the current state of the system. An alternative to a rigid infrastructure is to base the system´┐Żs reactions on logical inference, planning, and learning, the quintessential elements of an intelligent system. An intelligent grid is one where societal services exhibit intelligent behavior. A coordination service acting as a proxy on behalf of end users reacts to unforeseen events, plans how to carry out complex tasks, and learns from the history of the system. Various policies implemented by the societal services of an intelligent grid, such as brokerage and matchmaking, are based upon rules and facts gathered with the aid of a monitoring service. The question we address is how to construct intelligent computational grids which are truly scalable and could respond to the needs of a diverse user community.We present a prototype of a system used for a virtual laboratory in computational biology.

BibTeX:

@article{Bai-2005-Coordination,
author = "X. Bai and G. Wang and Y. Ji and G.M.
Marinescu and D.C. Marinescu and L. B{\"o}l{\"o}ni",
title = "Coordination in Intelligent Grid Environments",
journal = "Proceedings of the IEEE",
volume = "93",
number = "3",
pages = "613--630",
year = "2005",
abstract = {
  A computational grid is a complex system. The state space of a complex
  system is very large and it is infeasible to create a rigid
  infrastructure implementing optimal policies and strategies which take
  into account the current state of the system. An alternative to a rigid
  infrastructure is to base the system�s reactions on logical inference,
  planning, and learning, the quintessential elements of an intelligent
  system. An intelligent grid is one where societal services exhibit
  intelligent behavior. A coordination service acting as a proxy on behalf
  of end users reacts to unforeseen events, plans how to carry out complex
  tasks, and learns from the history of the system. Various policies
  implemented by the societal services of an intelligent grid, such as
  brokerage and matchmaking, are based upon rules and facts gathered with
  the aid of a monitoring service. The question we address is how to
  construct intelligent computational grids which are truly scalable and
  could respond to the needs of a diverse user community.We present a
  prototype of a system used for a virtual laboratory in computational
  biology.
 }
}

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