By Topic

Decentralized work-in-process optimization in cooperative resource allocation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Doraid Dalalah ; Industrial Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, PO Box 3030, Irbid, 22110, Jordan

Resource allocation entails deciding how to split a resource of restricted availability among various demands in a way that optimizes current objectives. In this paper, we focus on one type of distributed resource allocation problems in which a distributed system comprising networked heterogeneous agents and processors/servers where the agents strive to boost their efficiencies by issuing more work transactions for higher throughput. Each agent can issue work transactions which comprise a set of tasks that have to be completed by a networked set of servers. The agents get more utilities as their transactions delivery rate increases, however, network administration entails a set of constraints on the tolerable delay on the transactions. An optimization model is constructed to characterize the system in which the available servers are allocated to the present agents. The optimization model is solved in a decentralized way so that the agents can work separately to maximize the global benefit measure of the network. The presented model numerical solution is put together using ARENA simulation package and experimented for different network topologies. The simulation results show fair allocation of the resources whereas the anonymous agents work in parallel to achieve optimality.

Published in:

Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2011 7th International Conference on

Date of Conference:

15-18 Oct. 2011