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)
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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 |
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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: | 05 Nov 2024 10:14 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/31927 (The current URI for this page, for reference purposes) |
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