|Authors||S. B. Musunoori and G. Horn|
|Title||Application Service Placement in Stochastic Grid Environments Using Learning and Ant Based Methods|
|Publication Type||Journal Article|
|Year of Publication||2007|
|Journal||Multi Agent and Grid Systems|
Achieving acceptable application performance in a grid environment remains a difficult challenge. In particular this is true for applications composed of services requiring some quality requirements to be fulfilled in order to satisfy users' needs. The problem considered here is partitioning of application services onto the available execution nodes of grid environment in such a way that they satisfy some minimum quality requirements. Fundamentally this is an NP-hard problem. In this paper we propose three algorithms that are the first ones to be based on the concepts of learning automata and the metaphor of foraging ants. The algorithms naturally follow a decentralised multi-agent method for solving the service partitioning problem. Moreover they establish a distributed problem solving mechanism that does not require the use of a central controller. The proposed algorithms have been rigorously tested and evaluated through extensive simulations on randomly generated application services and grid environments. The results indicate that learning is an essential component to achieve scalability and efficiency in nature inspired systems.
Special Issue on Nature Inspired Systems for Parallel, Asynchronous and Decentralised Environments