Internet-Oriented Environment for Scientific Computing Resource Sharing

Abstract:

In this paper, we introduced a scientific computing environment for Internet-Oriented computing resource sharing, abbreviate ISCEs, which is a high-performance computing environment that allows users to write and evaluate parallel distributed applications for different hardware and software configurations using a web interface. We described the software architecture of ISCEs by emphasizing Application editor, Application Scheduling Components, and Application execution/runtime modules. ISCEs is efficient which is strongly supported by the time measurement scheduling polices. The system resource monitoring can also benefit a lot from the Application execution/runtime modules. The results obtained from performance analysis show that Scalability and Speedup of ISCEs was good.

• Periodical: Applied Mechanics and Materials (Volumes 241-244)
• Pages: 2953-2956
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.241-244.2953
• Online since: December 2012
• Authors: Shu Fang Zhang, Jun Han, Fei Jiang
• Keywords: Distributed Computing, Network Computing, Parallel Computing, Resource Sharing, Scientific Computing

References

[1] Korpela, Eric J. Annual Review of Earth & Planetary Sciences. Vol. 40, No. 1 (2012), pp.69-87.

[2] Weichang Yeh, Shangchi Wei. Future Generation Computer Systems. Vol. 28, No. 7 (2012), pp.989-1002.

[3] Domenico Talia, Paolo Trunfio, Jingdi Zeng. Peer-to-Peer Models for Resource Discovery in Large-Scale Grids: A Scalable Architecture. High performance computing for computational science - VECPAR 2006. pp.66-78(2006).

DOI: 10.1007/978-3-540-71351-7_6

[4] Xianyong Wang, Shengchao Xu . P2HP: Construction of a Cooperative Server Group Based Volunteer Computing Environment. Internet Computing in Science and Engineering, 2008. ICICSE '08. International Conference on. pp.389-395(2008).

DOI: 10.1109/icicse.2008.99

[5] Loebbert A., Finnie G. A Multi-agent Framework for Distributed Business Intelligence Systems. System Science (HICSS), 2012 45th Hawaii International Conference on. p.4129 – 4137 (2012 ).

DOI: 10.1109/hicss.2012.68

[6] Morrison J. P., Coghlan B., Shearer A., Foley S. Power D., Perrott R. International Journal of High Performance Computing Applications. Vol. 20, NO. 3 (2006), pp.409-422.

DOI: 10.1177/1094342006067475

[7] S.V. Saboji, C.B., Akki. Agent based bandwidth estimation in heterogeneous wireless networks 3rd International Conference on Advances in Recent Technologies in Communication and Computing. p.256–258 (2011).

DOI: 10.1049/ic.2011.0093