Skip to main content

Concurrent Negotiation and Coordination for Grid Resource Coallocation

Sim, Kwang Mong (2010) Concurrent Negotiation and Coordination for Grid Resource Coallocation. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 40 (3). pp. 753-766. ISSN 1083-4419. (doi:10.1109/TSMCB.2009.2028870) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:31927)

PDF Publisher pdf
Language: English

Restricted to Repository staff only
[thumbnail of Sim-SMCB-concurrent-Grid-nego.pdf]
Official URL:
http://dx.doi.org/10.1109/TSMCB.2009.2028870

Abstract

Bolstering resource coallocation is essential for realizing

the Grid vision, because computationally intensive applications

often require multiple computing resources from different

administrative domains. Given that resource providers and consumers

may have different requirements, successfully obtaining

commitments through concurrent negotiations with multiple resource

providers to simultaneously access several resources is a

very challenging task for consumers. The impetus of this paper

is that it is one of the earliest works that consider a concurrent

negotiation mechanism for Grid resource coallocation. The

concurrent negotiation mechanism is designed for 1) managing

(de)commitment of contracts through one-to-many negotiations

and 2) coordination of multiple concurrent one-to-many negotiations

between a consumer and multiple resource providers. The

novel contributions of this paper are devising 1) a utility-oriented

coordination (UOC) strategy, 2) three classes of commitment management

strategies (CMSs) for concurrent negotiation, and 3) the

negotiation protocols of consumers and providers. Implementing

these ideas in a testbed, three series of experiments were carried

out in a variety of settings to compare the following: 1) the CMSs

in this paper with the work of others in a single one-to-many

negotiation environment for one resource where decommitment

is allowed for both provider and consumer agents; 2) the performance

of the three classes of CMSs in different resource market

types; and 3) the UOC strategy with the work of others [e.g.,

the patient coordination strategy (PCS)] for coordinating multiple

concurrent negotiations. Empirical results show the following:

1) the UOC strategy achieved higher utility, faster negotiation

speed, and higher success rates than PCS for different resource

market types; and 2) the CMS in this paper achieved higher final

utility than the CMS in other works. Additionally, the properties

of the three classes of CMSs in different kinds of resource markets

are also verified.

Item Type: Article
DOI/Identification number: 10.1109/TSMCB.2009.2028870
Uncontrolled keywords: Grid resource allocation, negotiation, resource management, software agent.
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Kwang Mong Sim
Date Deposited: 24 Oct 2012 10:14 UTC
Last Modified: 16 Nov 2021 10:09 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/31927 (The current URI for this page, for reference purposes)

University of Kent Author Information

Sim, Kwang Mong.

Creator's ORCID:
CReDIT Contributor Roles:
  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.