5 QoS Guided Job Scheduling
5.6 Summary
In this chapter, we have presented two task rescheduling techniques, which are based on QoS guided Min-Min algorithm, aim to reduce the makespan of grid applications in batch style and minimize the total resource cost. Achievements of this work are twofold;
firstly, with a limited amount of computing resources, the execution time of a batch of grid tasks can be reduced by 7%~15% using the MOR approach; on the other hand, the total resource cost can be reduced by the ROR approach with an average rate of 50% without increasing overall execution time, which presents a significant improvement to the state of the art scheduling technique. The proposed MOR and ROR techniques are with characteristics of low complexity and high scalability in large-scale grid systems that have QoS constraint.
Co
The scheduling tree has no link contention and uses the shortest paths for broadcasting on switch based HNOW. In Chapter 3, we have presented efficient task allocation techniques to improve system performance in heterogeneous network with master slave tasking paradigm. One significant improvement of the ESCR algorithm is that network latency was considered as an influence factor in our algorithm design. The other advantage of the proposed techniques is that system resources are well utilized either by scheduling extra tasks or minimizing overall task completion time.
The heterogeneous computing need to be designed to provide the services of efficient resource management, system rebalancing, or job allocations in virtual or physical machines. The problem of job scheduling platform design has been main challenges. In Chapter 4, we have present grouping strategy and parallel dispatching services of JGDS and JGDS-D for grid computing. In order to avoid unnecessary replica of jobs in client nodes, a processed task recording table is constructed. Other algorithms FCFS, Min-Min and Max-Min are compared in this study. The significant improvement of the proposed method is that system throughput could be maximized via selecting adaptive client with
Chapter 6
nclusions and Future Work
The problem of resource management and scheduling has been one of main challenges in grid computing. In Chapter 2, a scheme called Location Aware Broadcast Scheme (LABS) for broadcasting on switch based HNOW is presented. The purpose of LABS is the design of a scheduling tree for broadcasting the messages between workstations via the shortest paths and without link contention. The LABS method operates in two parts: it constructs a location oriented spanning tree with restricted depth and width. And, it designs a scheduling tree using binomial-like scheduling for broadcasting.
d dispatching. Overall speaking, main contribution of this study is adapting the dynamic scheduling of job scheduling in different constructions of
e presented two task rescheduling techniques, which are based on QoS guided Min-Min algorithm, aim to reduce the makespan of grid applications in batch st
combining jobs an
heterogeneous environments. In Chapter 5, we hav
yle and minimize the total resource cost. The proposed MOR and ROR techniques are with characteristics of low complexity and high scalability in large-scale grid systems that have QoS constraint.
Our proposed method can be applied to the services of virtual platform in cloud system. In the future, we intend to focus on the services and virtual machine design for cloud users can utilize any resources efficiently which they want. We will compare more researches and analyze the performance on cloud system.
Current Publication Lists
Journal Papers
1. Ching-Hsien Hsu and Tai-Lung Chen, “Performance and Economization Oriented Scheduling Techniques for Managing Applications with QoS Demands in Grids”, International Journal of Ad-Hoc and Ubiquitous Computing, Vol. 5, No. 4, pp.
219-226, 2010. (SCIE, EI)
2. Ching-Hsien Hsu, Chi-Guey Hsu, Shih-Chang Chen and Tai-Lung Chen,
“Message Transmission Techniques for Low Traffic P2P Services”, International Journal of Communication Systems, Vol. 22, No. 9, pp. 1105-1122, September 2009. (SCI, EI)
3. Ching-Hsien Hsu, Tai-Lung Chen and Jong-Hyuk Park, “On Improving Resource Utilization and System Throughput of Master Slave Jobs Scheduling in Heterogeneous Systems,” Journal of Supercomputing, Springer, Vol. 45, No. 1, pp. 129-150, July 2008. (SCI, EI)
4. Ching-Hsien Hsu, Tai-Lung Chen and Kuan-Ching Li, "Performance Effective Pre-scheduling Strategy for Heterogeneous Communication Grid Systems,"
Future Generation Computer Systems, Vol. 23, Issue 4, pp. 569-579, May 2007.
(SCI, EI)
Conference Papers
1. Tai-Lung Chen, Ching-Hsien Hsu and Shih-Chang Chen, “Scheduling of Job Combination and Dispatching Strategy for Grid and Cloud System,” Proceedings on the 5rd International Conference on Grid and Pervasive Computing (GPC’10),
2. Shih-Chang Chen, Tai-Lung Chen LNCS 6104, pp. 612-621, May 2010.
and Ching-Hsien Hsu, “Message Clustering Efficient Communication Scheduling in Clusters and Grids,”
Proceedings of the 10th International Conference on Algorithms and Techniques towards
Architectures for Parallel Processing (ICA3PP’10), LNCS 6081, pp. 283-291, May 2010.
3. Shih-Chang Chen, Ching-Hsien Hsu, Tai-Lung Chen, Kun-Ming Yu, Hsi-Ya Chang and Chih-Hsun Chou, “A Compound Scheduling Strategy for Irregular
, Chien-Jung Huang, Tai-Lung Chen
Array Redistribution in Cluster Based Parallel System,” Proceedings of the 2nd Russia-Taiwan Symposium on Methods and Tools for Parallel Programming (MTPP’10), LNCS 6083, May 2010.
4. Chao-Tung Yang and Ching-Hsien Hsu, “File
Replication Maintenance Strategy Using Bayesian Network in Date Grids,”
Proceedings of the 2nd Russia-Taiwan Symposium on Methods and Tools for Parallel Programming (MTPP’10), LNCS 6083, May 2010.
5. Ching-Hsien Hsu, Tai-Lung Chen and Kun-Ho Lee, "QoS Based Parallel File
en Hsu, Tai-Lung Chen
Transfer for Grid Economics" Proceedings of the 2009 International Conference on Multimedia Information Networking and Security (MINES’09), pp. 653-657, November 2009.
6. Ching-Hsi , Bing-Ru Tsai and Kuan-Ching Li, “Scheduling for Atomic Broadcast Operation in Heterogeneous Networks with One Port
the 3rd International Conference on Grid and Pervasive Model,” Proceedings on
Computing (GPC’08), LNCS 5036, pp. 166-177, May 2008.
7. Ching-Hsien Hsu, Ming-Hsiung Tsai, Tai-Lung Chen and Kun-Min Yu,
“Performance-Effective and Contention-Free Broadcasts on Irregular Network
EEE Proceedings of the 2nd International with Heterogeneous Workstations”, I
Workshop on Service, Security and its Data management technologies for Ubiquitous Computing (SSDU’08), pp. 352-357, May 2008.
8. Ching-Hsien Hsu and Tai-Lung Chen, "An Efficient Task Dispatching Method in Heterogeneous Networks," IEEE Proceedings of the 2007 International Conference on Multimedia and Ubiquitous Engineering (MUE’07), pp. 17-22, April 2007.
9. Tai-Lung Chen and Ching-Hsien Hsu, "An Efficient Processor Selection Scheme for Master Slave Paradigm on Heterogeneous Networks," Proceedings of Network and Parallel Computing (NPC’06), October 2006.
10. Tai-Lung Chen and Ching-Hsien Hsu, "Performance Effective Pre-scheduling Strategy for Heterogeneous Communication Grid Systems," Proceedings of the 12th Workshop on Compiler Techniques for High-Performance Computing (CTHPC’06), pp. 120-129, March 2006.
11. Ching-Hsien Hsu, Tai-Lung Chen and Guan-Hao Lin, “Grid Enabled Master Slave Task Scheduling for Heterogeneous Processor Paradigm,” Grid and Cooperative Computing (GCC’05), LNCS 3795, pp. 449-454, December 2005.
Workstations),” IEEE Micro, pp.54-64, 1995.
eduling Heuristics for Efficient Broadcast
for Improving QoS in Public Computing Utilities,” Proceedings of the 9th International Conference on Computer and Information Technology, 2006.
[7] M. D. Assuncao, A. D. Costanzo and R. Buyya, “Evaluating the Cost-Benefit of Using Cloud Computing to Extend the Capacity of Clusters,” Proceedings of the 18th ACM International Symposium on High Performance Distributed Computing, pp. 141-150, 2009.
[8] F. M. Aymerich, G. Fenu and S. Surcis, “A Real Time Financial System based on Grid and Cloud Computing,＂Proceedings of the 2009 ACM Symposium on Applied
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