Summary
This chapter reviews dynamism in desktop Grid computing and explains the advanced stochastic scheduling scheme with the Markov Job Scheduler based on Availability (MJSA) in the environment.
In recent years, Grid computing [1] has received considerable interest in the field of academics and enterprise. Numerous attempts have been made to organize cost efficient large-scale Grid computing. Desktop Grid computing [13,19,2] is a more flexible paradigm that is used to achieve high performance and high throughput with desktop resources that are less stable and has more inferior performance compared to traditional Grid. It is comprised of a diverse set of desktops interconnected with various network forms ranging from Local Area Network (LAN) to the Internet. Desktop Grid system has played a leading role in the development of large scale aggregated computing power harvested from the edge of the Internet at lower cost. The main goals of the system are to accomplish high throughput and performance by mobilizing the potential colossal computational resources of idle desktops.
However, since a desktop peer is a fluctuating resource that connects to the system, performs computations and disconnects to the network at will, desktop volatility makes the system unstable and unreliable. To develop a reliable desktop Grid computing system, a scheduling scheme must consider the dynamic nature (i.e., volatility) of volunteers and a resource selection scheme should adapt to such a dynamic environment, as the selection is getting complicated due to the uncertain behavior of desktops.
This chapter demonstrates desktop state change modelling and an advanced resource selection scheme, Selection of Credible Resource with Elastic Window (SCREW), to choose reliable resources in dynamic computational desktop Grid environments. Markov modelling of the dynamic state turning provides understanding of the pattern of desktop behavior while SCREW selects qualified desktops that satisfy time requirements to complete given workloads and adapts to the needs of the user and the application on the fly.
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References
Berman, F., Fox, G.C., Hey, J.G.: Grid Computing: Making the Global Infrastructure a Reality. Wiley, Chichester (2003)
Entropia, http://www.entropia.com
Bhagwan, R., Savage, S., Voelker, G.M.: Understanding availability. In: Kaashoek, M.F., Stoica, I. (eds.) IPTPS 2003. LNCS, vol. 2735, pp. 256–267. Springer, Heidelberg (2003)
Chu, J., Labonte, K., Levine, B.N.: Availability and Popularity Measurements of Peer-to-Peer File systems, Technical report 04-36 (2004)
Nurmi, D., Brevik, J., Wolski, R.: Modeling Machine Availability in Enterprise and Wide-Area Distributed Computing Environments. In: Cunha, J.C., Medeiros, P.D. (eds.) Euro-Par 2005. LNCS, vol. 3648, pp. 432–441. Springer, Heidelberg (2005)
Mutka, M.W., Livny, M.: The Available Capacity of a Privately Owned Workstation Environmont. Performance Evaluation 12(4), 269–284 (1991)
Yang, L., Schopf, J.M., Foster, I.: Conservative scheduling: Using predicted variance to improve scheduling decisions in dynamic environment. In: Proceedings of the SC 2003, pp. 31–46 (2003)
Sarmenta, L.F.G., Hirano, S.: Bayanihan: Building and Studying Web-Based Volunteer Computing Systems Using Java. Future Generation Computer Systems 15(5-6), 675–686 (1999)
Neary, M.O., Christiansen, B.O., Cappello, P., Schauser, K.E.: Javelin: Parallel computing on the Internet. Future Generation Computer Systems 15(5-6), 659–674 (1999)
Neary, M.O., Cappello, P.: Advanced Eager Scheduling for Java Based Adaptively Parallel Computing. In: Proceedings of the JGI 2002, pp. 56–65 (2002)
Anderson, D.P., Cobb, J., Korpela, E., Lebofsky, M., Werthimer, D.: SETI@home: an experiment in public-resource computing. Communications of the ACMÂ 45(11) (November 2002)
Lau, L.F., Ananda, A.L., Tan, G., Wong, W.F.: Gucha: Internet-based parallel computing using Java. In: Proceedings of the ICA3PP, pp. 397–408 (2000)
Fedak, G., Germain, C., Neri, V., Cappello, F.: XtremWeb: A Generic Global Computing System. In: Workshop on Global Computing on Personal Devices, Proceedings of the CCGRID 2001, pp. 582–587 (2001)
Baratloo, A., Karaul, M., Kedem, Z.M., Wijckoff, P.: Charlotte: Metacomputing on the Web. Future Generation Computer Systems 15(5-6), 559–570 (1999)
Nisan, N., London, S., Regev, O., Camiel, N.: Globally Distributed Computation over Internet? The POPCORN Project. In: Proceedings of the ICDCS 1998, pp. 592–601 (1998)
Morrison, J.P., Kennedy, J.J., Power, D.A.: WebCom: A Web Based Volunteer Computer. The Journal of Supercomputing 18(1), 47–61 (2001)
Korea@Home, http://www.koreaathome.org
Byun, E.J., Choi, S.J., Baik, M.S., Park, C.Y., Jung, S.Y., Hwang, C.S.: Scheduling Scheme based on Dedication Rate in Volunteer Computing Environment. In: Proceedings of the ISPDC 2005, pp. 234–241 (2005)
Kondo, D., Fedak, G., Cappello, F., Chien, A., Casanova, H.: Characterizing resource availability in enterprise desktop grids. Future Generation Computing Systems 23(7), 888–903 (2007)
Casanova, H., Legrand, A., Zagorodnov, D., Berman, F.: Heuristics for Scheduling Parameter Sweep Applications in Grid Environments. In: Proceedings of the 9th Heterogeneous Computing Workshop, pp. 349–363 (2000)
Wolski, R., Spring, N., Hayes, J.: The Network Weather Service: A Distributed Resource Performance Forecasting Service for Metacomputing. Future Generation Computing Systems 15(5-6), 757–768 (1999)
Litzkow, M., Livny, M., Mutka, M.: Condor - A Hunter of Idle Workstations. In: Proceedings of the ICDCS 1998, pp. 104–111 (1988)
Kondo, D., Chien, A., Casanova, H.: Resource Management for Rapid Application Turnaround on Enterprise Desktop Grids. In: Proceedings of the SC 2004, pp. 17–29 (2004)
Schopt, J., Berman, F.: Stochastic Scheduling. In: Proceedings of the SC 1999, p. 48 (1999)
Rainer, L.R.: A Tutorial on Hidden Markov Models and Selected Application in Speech Recognition. Proceedings of the IEEE 77(2), 257–286 (1989)
Forney Jr., G.D.: The Viterbi Algorithm. Proceedings of the IEEE 61(3), 268–278 (1973)
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Byun, E., Choi, S., Kim, H., Hwang, C., Lee, S. (2008). Advanced Job Scheduler Based on Markov Availability Model and Resource Selection in Desktop Grid Computing Environment. In: Xhafa, F., Abraham, A. (eds) Metaheuristics for Scheduling in Distributed Computing Environments. Studies in Computational Intelligence, vol 146. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69277-5_6
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