Lakra, Sukromony (2007) Load balancing techniques for I/O intensive tasks on heterogeneous clusters. MTech thesis.
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Abstract
Load balancing schemes in a cluster system play a critically important role in developing highperformance cluster computing platform. Existing load balancing approaches are concerned with the effective usage of CPU and memory resources. I/O-intensive tasks running on a heterogeneous cluster need a highly effective usage of global I/O resources, previous CPU-or memory-centric load balancing schemes suffer significant performance drop under I/O- intensive workload due to the imbalance of I/O load. To solve this problem, Zhang et al. developed two I/O-aware load-balancing schemes, which consider system heterogeneity and migrate more I/O-intensive tasks from a node with high I/O utilization to those with low I/O utilization. If the workload is memory-intensive in nature, the new method applies a memory-based load balancing policy to assign the tasks. Likewise, when the workload becomes CPU-intensive, their scheme leverages a CPU-based policy as an efficient means to balance the system load. In doing so, the proposed approach maintains the same level of performance as the existing schemes when I/O load is low or well balanced. Results from a trace-driven simulation study show that, when a workload is I/O-intensive, the proposed schemes improve the performance with respect to mean slowdown over the existing schemes by up to a factor of 8. In addition, the slowdowns of almost all the policies increase consistently with the system heterogeneity.
Item Type: | Thesis (MTech) |
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Uncontrolled Keywords: | Load balancing techniques, I/O intensive tasks, Heterogeneous clusters |
Subjects: | Engineering and Technology > Computer and Information Science |
Divisions: | Engineering and Technology > Department of Computer Science |
ID Code: | 4359 |
Deposited By: | Hemanta Biswal |
Deposited On: | 12 Jul 2012 09:16 |
Last Modified: | 18 Jul 2012 16:20 |
Supervisor(s): | Sahoo, B D |
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