An Ant-based Mobile Agent Approach to Resource Discovery in Grid Computing

ABSTRACT

Grid Computing is used to solve complex scientific computing problems and uses large amounts of computing resources to do so. A Grid Computing architecture is inherently complex and differs significantly from other computing paradigms such as client-server technologies. Resource Discovery in particular is non-trivial in Grid Computing owing to the complex nature of its heterogeneous components, geographic distances between components and the dynamic nature of a typical Grid. An evaluation of three prominent approaches reveals that each technique was created for a specific type of Grid Computing architecture. On the strengths and shortcoming of these approaches, we propose a framework for an enhanced model for resource discovery in grid computing. Our model is inspired by Mobile agent- and Bio-ant technology, coupled with Ant Colony optimization techniques for improved ways of solving the resource discovery problem in grid computing.

References

1. Al- Raweshidy, H., Kurdi, H., and Maozhen, L. Taxonomy of Grid Systems. In Handbook of research on P2P and grid systems for service-oriented computing: Models, Methodologies and Applications. IGI Global, 2010, 20--43.
2. Cokuslu, D., Hameurlain, A., and Erciyes, K. Grid Resource Discovery Based on Centralized and Hierarchical Architectures. International Journal for Informatics 3, 1 (2010), 227--233.
3. Deng, Y., Wang, F., and Ciura, A. Ant colony optimization inspired resource discovery in P2P Grid systems. The Journal of Supercomputing 49, 1 (2008), 4--21.
4. Devi, S.N., Pethalakshmi, A., Krishna, P.V., Babu, M.R., and Ariwa, E. Resource Discovery for Grid Computing Environment Using Ant Colony Optimization by Applying Routing Information and LRU Policy. In Global Trends in Computing and Communication Systems -Communications in Computer and Information Science. Springer, Berlin, 2012, 124--133.
5. Dorigo, M. and Stützle, T. Ant Colony Optimization. Bradford Books, Scituate, MA, USA, 2004.
6. Forestiero, A., Leonardi, E., Mastroianni, C., and Meo, M. Self-Chord: A Bio-Inspired P2P Framework for Self-Organizing Distributed Systems. IEEE/ACM Transactions on Networking 18, 5 (2010), 1651--1664.
7. Gray, R.S., Kotz, D., Cybenko, G., and Rus, D. D' Agents: Security in a multiple-language, mobile-agent system. Mobile Agents and Security 1419/1998, (1998), 154--187.
8. Gray, R.S., Kotz, D., Nog, S., Rus, D., and Cybenko, G. Mobile agents for mobile computing. Proceedings of the 2nd Aizu International Symposium on Pharallel Algorithms/Architectures Synthesis, (1996).
9. Horvat, D., Cvetković, D., and Milutinović, V. Mobile agents and java mobile agents toolkits. in Proceedings of the 33rd Hawaii International Conference on System Sciences 00, January (2001), 1--10.
10. Huang, Y., Bessis, N., Brocco, A., Kuonen, P., Courant, M., and Hirsbrunner, B. Using Metadata Snapshots for Extending Ant-Based Resource Discovery Service in Inter-cooperative Grid Communities. 2009 First International Conference on Evolving Internet, (2009), 89--94.
11. Lange, D.B., Oshima, M., Kosaka, K., and Günter, K. Aglets: Programming mobile agents in Java. Worldwide Computing and Its Applications, Springer Berlin (1997), 253--266.
12. Mollamotalebi, M., Samad, A., Haji, B., and Ahmed, A.A. A New Model for Resource Discovery in Grid Environment. International Conference on Informatics Engineering and Information Science, Springer Berlin Heidelberg (2011), 72--81.
13. Picco, P. Mobile agents: An introduction. Microprocessors and Microsystems 25, 2 (2001), 65--74.
14. Rahman, M., Ranjan, R., Buyya, R., and Benatallah, B. A taxonomy and survey on autonomic management of applications in grid computing environments. Concurrency and Computation: Practice and Experience 23, 16 (2011), 1990--2019.
15. Roy, S. and Mukherjee, N. Efficient resource management for running multiple concurrent jobs in a computational grid environment. Future Generation Computer Systems 27, 8 (2011), 1070--1082.
16. Singh, M., Cheng, X., and Belavkin, R. Resource Discovery Using Mobile Agents. 2010 Fifth International Conference on Frontier of Computer Science and Technology, (2010), 72--77.
17. Sotiriadis, S., Bessis, N., Huang, Y., Sant, P., and Maple, C. Towards decentralized grid agent models for continuous resource discovery of interoperable grid Virtual Organisations. 2010 Fifth International Conference on Digital Information Management (ICDIM), IEEE (2010), 530--535.
18. Spooner, D., Turner, J.D., Jarvis, S., Kerbyson, D.J., Saini, S., and Nudd, G. Agent-Based Resource Management for Grid Computing. 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID'02), IEEE (2002), 350--350.
19. Stoica, I., Morris, R., Karger, D., Kaashoek, M.F., and Balakrishnan, H. Chord: A Scalable Peer-to-Peer Lookup Service for Internet Applications. Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications - SIGCOMM '01, ACM Press (2001), 149--160.
20. Tripathi, A., Ahmed, T., and Karnik, N. Experiences and Future Challenges in Mobile Agent Programming. Microprocessors and Microsystems 25, Y (2000), 121--129.
21. Zhang, L., Li, X., and Ru, B. The Research of Mobile Agent-Based Mobile Grid Resource Discovery. 2010 International Conference on Intelligent Computing and Cognitive Informatics, (2010), 487--490.

Index Terms

• Software and its engineering

  • Software organization and properties

    • Software system structures

      • Distributed systems organizing principles

        • Organizing principles for web applications