Mobile Agent Based Adaptive Scheduling Mechanism in Peer to Peer Grid Computing
In a peer to peer grid computing environment, volunteers are exposed to failures such as crash and link failures. In addition, since volunteers can dynamically join and leave executions and they are not dedicated only to a peer to peer grid computing, the executions of volunteers are stopped or suspended more frequently than in a grid computing environment. These failures result in the delay and blocking of the executions of tasks and even partial or entire loss of the executions. In addition, these failures make it difficult for a volunteer server to schedule tasks and manage the allocated tasks as well as volunteers. Existing peer to peer grid computing systems, however, do not deal with these failures in scheduling mechanisms. Moreover, since existing scheduling mechanisms are performed only by a volunteer server in a centralized way, there is a high overhead.
To solve these problems, we propose a mobile agent based adaptive scheduling mechanism (MAASM). We implemented MAASM in Korea@Home and ODDUGI mobile agent system. The MAASM reduces the overhead of volunteer server by using mobile agents in scheduling procedure in a distributed way. In addition, it tolerates the various failures(especially, volunteer autonomy failures) which frequently occur in a peer to peer grid computing environment. Consequently, MAASM guarantees reliable and continuous executions in spite of the failures, so it decreases total execution time.
KeywordsMobile Agent Total Execution Time Volunteer Group Schedule Mechanism Desktop Grid
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- 1.SETI@home, http://setiathome.ssl.berkeley.edu
- 2.Distributed.net, http://distributed.net
- 3.Milojicic, D.S., Kalogeraki, V., Lukose, R., Nagaraja, K., Pruyne, J., Richard, B., Rollins, S., Xu, Z.: Peer-to-Peer Computing. HP Laboratories Palo Alto HPL-2002-57 (March 2002)Google Scholar
- 5.Berman, F., Fox, G.C., Hey, A.J.G.: Grid Computing: Making the Global Infrastructure a Reality. Wiley, Chichester (2003)Google Scholar
- 6.Sarmenta, L.F.G., Hirano, S.: Bayanihan: Building and Studying volunteer computing Systems Using Java. Future Generation Computer Systems Special Issue on Metacomputing 15(5/6) (1999)Google Scholar
- 7.Neary, M.O., Brydon, S.P., Kmiec, P., Rollins, S., Cappello, P.: Javelin++: Scalability Issues in Global Computing. Concurrency: Parctice and Experience, 727–735 (December 2000)Google Scholar
- 8.Fedak, G., Germain, C., Neri, V., Cappello, F.: XtremWeb: A Generic Global Computing System. In: CCGrid 2001 workshop on Global Computing on Personal Devices, May 2001, pp. 582–587 (2001)Google Scholar
- 9.Fukuda, M., Tanaka, Y., Suzuki, N., Bic, L.F.: A Mobile-Agent-Based PC Grid. In: Autonomic Computing Workshop AMS 2003, June 2003, pp. 142–150 (2003)Google Scholar
- 10.Kondo, D., Taufer, M., Karanicolas, J., Brooks, C.L., Casanova, H., Chien, A.: Characterizing and Evaluating Desktop Grids: An Empirical Study. In: IPDPS 2004 (April 2004)Google Scholar
- 11.Jalote, P.: Fault Tolerance in Distributed Systems. Prentice-Hall, Englewood Cliffs (1994)Google Scholar
- 13.Korea@Home, http://www.koreaathome.org/eng/
- 14.ODDUGI mobile agent system, http://oddugi.korea.ac.kr/
- 15.Baik, M., Choi, S., Hwang, C., Gil, J., Yu, H.: Adaptive Group Computation Approach in the Peer-to-peer Grid Computing Systems. Concurrency and Computation: Practice and Experience (2005)Google Scholar