A Trace-Driven Simulation Study of Dynamic Load Balancing
IEEE Transactions on Software Engineering
A comparative study of load sharing in heterogeneous multicomputer systems
ANSS '92 Proceedings of the 25th annual symposium on Simulation
Journal of Parallel and Distributed Computing
SETI@home: an experiment in public-resource computing
Communications of the ACM
Towards efficient resource on-demand in Grid Computing
ACM SIGOPS Operating Systems Review
A Comparison among Grid Scheduling Algorithms for Independent Coarse-Grained Tasks
SAINT-W '04 Proceedings of the 2004 Symposium on Applications and the Internet-Workshops (SAINT 2004 Workshops)
A Grid Portal for an Undergraduate Parallel Programming Course
IEEE Transactions on Education
An adaptive load balancing algorithm with use of cellular automata for computational grid systems
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part I
A hybrid policy for fault tolerant load balancing in grid computing environments
Journal of Network and Computer Applications
Balanced Job Scheduling Based on Ant Algorithm for Grid Network
International Journal of Grid and High Performance Computing
Performance modelling and analysis of mobile grid computing systems
International Journal of Grid and Utility Computing
| Hi-index | 12.05 |
Grid computing has become conventional in distributed systems due to technological advancements and network popularity. Grid computing facilitates distributed applications by integrating available idle network computing resources into formidable computing power. As a result, by using efficient integration and sharing of resources, this enables abundant computing resources to solve complicated problems that a single machine cannot manage. However, grid computing mines resources from accessible idle nodes and node accessibility varies with time. A node that is currently idle, may become occupied within a second of time and then be unavailable to provide resources. Accordingly, node selection must provide effective and sufficient resources over a long period to allow load assignment. This study proposes a hybrid load balancing policy to integrate static and dynamic load balancing technologies. Essentially, a static load balancing policy is applied to select effective and suitable node sets. This will lower the unbalanced load probability caused by assigning tasks to ineffective nodes. When a node reveals the possible inability to continue providing resources, the dynamic load balancing policy will determine whether the node in question is ineffective to provide load assignment. The system will then obtain a new replacement node within a short time, to maintain system execution performance.