Dynamic Load Balancing and Pricing in Grid Computing with Communication Delay

Due to the emergence of Grid computing over the Internet, there is presently a need for dynamic load balancing algorithms which take into account the characteristics of Grid computing environments. In this paper, we consider a Grid architecture where computers belong to dispersed administrative doma...

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Bibliographic Details
Published in:Journal of grid computing 2008-09, Vol.6 (3), p.239-253
Main Authors: Zheng, Qin, Tham, Chen-Khong, Veeravalli, Bharadwaj
Format: Article
Language:English
Subjects:
Algorithms
Communication
Computational grids
Computer Science
Computer simulation
Domains
Dynamic loads
Internet
Load balancing
Load distribution (forces)
Management of Computing and Information Systems
Mathematical models
Performance evaluation
Pricing
Processor Architectures
Response time (computers)
Servers
Stress concentration
User Interfaces and Human Computer Interaction
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Summary:Due to the emergence of Grid computing over the Internet, there is presently a need for dynamic load balancing algorithms which take into account the characteristics of Grid computing environments. In this paper, we consider a Grid architecture where computers belong to dispersed administrative domains or groups which are connected with heterogeneous communication bandwidths. We address the problem of determining which group an arriving job should be allocated to and how its load can be distributed among computers in the group to optimize the performance. We propose algorithms which guarantee finding a load distribution over computers in a group that leads to the minimum response time or computational cost. We then study the effect of pricing on load distribution by considering a simple pricing function. We develop three fully distributed algorithms to decide which group the load should be allocated to, taking into account the communication cost among groups. These algorithms use different information exchange methods and a resource estimation technique to improve the accuracy of load balancing. We conducted extensive simulations to evaluate the performance of the proposed algorithms and strategies.
ISSN:1570-7873
1572-9184
DOI:10.1007/s10723-007-9093-5