CFP last date
20 January 2025
Reseach Article

A Hierarchical Shared Memory Cluster Architecture with Load Balancing and Fault Tolerance

by Minakshi Tripathy, C.R. Tripathy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 25 - Number 6
Year of Publication: 2011
Authors: Minakshi Tripathy, C.R. Tripathy
10.5120/3038-4121

Minakshi Tripathy, C.R. Tripathy . A Hierarchical Shared Memory Cluster Architecture with Load Balancing and Fault Tolerance. International Journal of Computer Applications. 25, 6 ( July 2011), 8-18. DOI=10.5120/3038-4121

@article{ 10.5120/3038-4121,
author = { Minakshi Tripathy, C.R. Tripathy },
title = { A Hierarchical Shared Memory Cluster Architecture with Load Balancing and Fault Tolerance },
journal = { International Journal of Computer Applications },
issue_date = { July 2011 },
volume = { 25 },
number = { 6 },
month = { July },
year = { 2011 },
issn = { 0975-8887 },
pages = { 8-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume25/number6/3038-4121/ },
doi = { 10.5120/3038-4121 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:11:01.477001+05:30
%A Minakshi Tripathy
%A C.R. Tripathy
%T A Hierarchical Shared Memory Cluster Architecture with Load Balancing and Fault Tolerance
%J International Journal of Computer Applications
%@ 0975-8887
%V 25
%N 6
%P 8-18
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recently a great deal of attention has been paid to the design of hierarchical shared memory cluster system. Cluster computing has made hierarchical computing systems increasingly common as target environment for large-scale scientific computations. This paper proposes hierarchical shared memory cluster architecture with load balancing and fault tolerance. Hierarchies of shared memory and caches structure the architecture. The hierarchical load balancing approach focuses on reducing the redistribution cost. The fault tolerant model is adopted to build highly available clusters in hierarchical shared memory clusters. Performance analysis and results reveal that hierarchical shared memory clusters performs much better creating a reliable hierarchical network cluster system with high scalability.

References
  1. Guzman A., Krall E.J., McGehearty P.F. and Bagherzadeh N., “The effect of application characteristics on performance in a parallel architecture”, Proceedings of the Twenty-First Annual Hawaii International Conference on Architecture Track, 5-8 Jan 1988, pp 167-172.
  2. ShenggangChen, Shuming Chen, and YamingYin, “Performance Impact of SMP-Cluster on the On-chip Large-scale Parallel Computing Architecture”, IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW), 19-23 April 2010, pp 1 – 7.
  3. Minakshi tripathy and C.R.Tripathy, “Design and analysis of a Dynamically Reconfigurable Shared Memory Cluster”, International Journal of Computer Science and network Security, Vol.10, No.9, Sept 2010, pp 145-158.
  4. Yen-Jen Oyang, David Jinsung Sheu, Chih-Yuan Cheng and Cheng-Zen Yang, “The M2 hierarchical multiprocessor”, International journal of Future Generation Computer Systems, Vol. 9, No. 3, Sept 1993, pp 235-240.
  5. Morris, D. and Theaker, C.J., “Hierarchical multiprocessor architecture”, IEEE Proceedings on Computers and Digital Techniques, July 1987, Vol. 134, No. 4, pp 161 – 167.
  6. A. W. Wilson Jr., “Hierarchical cache/bus architecture for shared memory Multiprocessors”, In Proceedings of the 14th Annual International Symposium on Computer Architecture, June 1987, pp 244-252.
  7. Khokhar A. and Dubois M., “Matching algorithms and architecture in hierarchical shared-memory multiprocessor (HSM) systems”, Proceedings of Sixth International Symposium on Parallel Processing, 23-26 Mar 1992, pp 558 – 561.
  8. X. Liu, H. Jiang, and L. K. Soh, “A Distributed Shared Object Model Based on Hierarchical Consistency Protocol for Heterogeneous Clusters”, Proceedings of 4th IEEE/ACM Int. Symp. On Cluster Computing and the Grid, April 2004, pp. 515-522.
  9. Feipei Lai, Lea-Ming Tzeng, Thom-Ling Chang and Tai-Ming Parng, “MARS performance evaluation with different interconnection networks”, Proceedings of the First International Conference on Systems Integration, 23-26 April 1990, pp 248-257.
  10. Syed Masud Mahmud , L. Tissa Samaratunga and Shilpa Kommidi,”Fault-Tolerant Hierarchical Networks for Shared Memory Multiprocessors and their Bandwidth Analysis”, The Computer Journal, Vol. 45, No. 2, Feb. 2002, pp. 147-161.
  11. Sokolinsky L. B., “Survey of Architectures of Parallel Database systems”, Programming and Computer Software, Vol.30, No.6, 2004, pp 337-346.
  12. Rocco Aversa, Beniamino Di Martino, Nicola Mazzocca and Salvatore Venticinque, “A hierarchical distributed-shared memory parallel Branch & Bound application with PVM and OpenMP for multiprocessor clusters”, Parallel Computing, Vol. 31, No. 10-12, Oct-Dec. 2005, pp 1034-1047.
  13. J. H. Abawajy, “Adaptive hierarchical scheduling policy for enterprise grid computing systems”, Journal of Network and Computer Applications, Vol. 32 No. 3, May 2009, pp 770-779.
  14. Emilia Rosti, Giuseppe Serazzi, Evgenia Smirni and Mark S. Squillante, “The impact of I/O on program behavior and parallel scheduling”, Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems, Vol. 26, No. 1, June 1998, pp 56-65.
  15. James D. Teresco, Jamal Faik and Joseph E. Flaherty, “Hierarchical Partitioning and Dynamic Load Balancing for Scientific Computation”, 7th International Conference on Applied Parallel Computing, June 20-23, 2004, pp 911-920.
  16. Zhiling Lana, Valerie E. Taylorb, and Yawei Lia, “DistDLB: Improving cosmology SAMR simulations on distributed computing systems through hierarchical load balancing”,---- Volume 66, Issue 5, May 2006, pp 716-731.
  17. Zhiling Lan, Valerie E. Taylor and Greg Bryan, “A novel dynamic load balancing scheme for parallel systems”, Journal of Parallel and Distributed Computing, Vol.62, No. 12, Dec. 2002, pp 1763-1781.
  18. Cristiana Amza, Alan L. Cox., Sandhya Dwarkadas and Pete Keleher, “Treadmarks: Shared Memory computing on networks of workstations”, Computer Journal, Vol 29, No.2, Feb 1996, pp 18-28.
  19. Tzu Fang Sheu, Nen Fu Huang, Hsiao Ping Lee, “Hierarchical multi pattern matching algorithm for network content inspection”, International journal of Information Sciences, Vol. 178, No. 14, July 2008, pp 2880-2898.
  20. B.Panja, S.K. Madria, B.Bhargava, “A role-based access in a hierarchical sensor network architecture to provide multilevel security”, Computer Communications Vol.31, No.4, April 2008, pp 793– 806.
  21. Minakshi Tripathy, C.R.Tripathy, “A new Coordinated Checkpointing and Rollback Recovery scheme for Distributed Shared Memory Clusters”, International Journal of Distributed and Parallel systems, Vol.2, No.1, Jan 2011, pp 49-58.
  22. Arun K. Somani and Allen M. Sansano, “Achieving Robustness and Minimizing Overhead in Parallel Algorithms through Overlapped Communication/Computation”, The Journal of Supercomputing - Special issue on embedded fault-tolerance systems, Vol. 16, No. 1-2, May 2000, pp 27-52.
  23. Chita R. Das, and Laxmi N. Bhuyan, “Bandwidth availability of multiple-bus multiprocessors”, IEEE Transactions on Computers, Vol. 34, No. 10, Oct. 1985, pp 918-926.
  24. Veglis A.A. and Pombortsis A.S., “Performance related analysis of L-level hierarchical shared-memory multiprocessors”, 8th Mediterranean Electro technical Conference, 13-16 May 1996, pp 1055-1060.
  25. Kai Hwang, Hai Jin, Chow, E., Cho-Li Wang and Zhiwei Xu, “Designing SSI clusters with hierarchical checkpointing and single I/O space”, IEEE Concurrency, Vol. 7, No. 1, Jan-Mar 1999, pp 60 – 69.
  26. K. Li, J. Naughton and J. Plank, “Low latency concurrent checkpointing for parallel programs”, IEEE transactions on Parallel and distributed systems, Vol. 5, No. 8, 1994, pp 874-879.
Index Terms

Computer Science
Information Sciences

Keywords

Cluster Controller Cluster Scheduler Data Scheduler Hierarchical Checkpointing Levels of hierarchy Recovery levels