Abstract
Modern cost-effective computing in industry is heavily dependent on the ability of engineering management to replace older (more expensive) mainframes with the use of idle (less expensive) resources that are a part of the engineers normal work environment. With this shift in paradigm comes a need to duplicate many of the job management facilities that are normally associated with central mainframes. One example of this comes in the form of job scheduling. In particular, if engineers are to rely on clusters of workstations as a replacement to a mainframe for most of their routine work, then reliable job scheduling that ensures fault tolerance, interoperability of systems software, and load balancing is a necessary requirement. At present, most job scheduling software, that is available for the cluster environment, does not have the ability to schedule a job on a cluster based on network load. This work is an attempt at addressing some of the fundamental issues regarding network load balancing so that deployment requirements for network job scheduling of parallel and distributed computing applications can better be understood.
In this paper, a control system (via Fuzzy Logic) is described that prioritizes the allocation of parallel jobs to, and their suspension from, a cluster of networked workstations. The algorithm presented here augments the scheduling capabilities of existing network queuing systems by including, in addition to the available number of machines, network load as a cluster resource and an application's communication requirements as a resource specification in the ranking decisions. It will be demonstrated that the resulting fuzzy controller of this paper can be used as an easily extensible, inexpensive, modular interface to network queuing systems for the scheduling of parallel and sequential jobs.
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References
Green, T.P, “DQS 3.0 User Guide”, Supercomputer Computations Research Institute, Florida State University, Tallahassee, Florida, April 1, 1994.
Beguelin, A., Dongarra, J.J, Geist, G.A., Mancheck, R., and Sunderam, V.S., “A Users' Guide to PVM Parallel Virtual Machine,” Technical Report ORNL/TM-11826, Oak Rigde National Laboratory, July 1991.
Chang, T.C. and Ibbs, C.W., “PRIORITY RANKING — A Fuzzy Expert System for Priority Decision Making in Building Construction Resource Allocation”, Building and Environment, the International Journal of Building Science and its Applications, Vol. 44, No. 2, pp. 169–186, 1991.
Mamdani, E.H. and Assilian, S., “An experiment in linguistic synthesis with a fuzzy logic controller”, International Journal of Man-Machine Studies 7, 1–13, 1975.
Manke, J.W and Patterson, J.C., “Message Passing Performance of Intel Paragon, IBM SP1 and Cray T3D Using PVM,” 7th SIAM Conference on Parallel Processing for Scientific Computing, 1994.
Manke, J. W., Neves, K. W., and Wicks, T. M., “Parallel Computing for Helicopter Rotor Design”, Proceedings of the Second International Symposium on High-Performance Distributed Computing, IEEE, July 1993.
TILShell Version 3.0 by Ortech Engineering (used to be Togai Infralogic Inc.), 5 Vanderbilt, Irvine, CA 92718.
Venkateswaran, R., Obradovic, Z., Raghavendra, C.S., “Cooperative Genetic Algorithm for Optimization Problems in Distributed Computer Systems”, personal communication.
M.Litzkow, M. Livny, and M.Mutka, “Condor-A Hunter of Idle Workstations,” In Proceedings of the 8th International Conference on Distributed Computer Systems, June 1988.
“Load Leveler”, commerical product, IBM
“Task Broker”, commerical product, Hewlett-Packard
Songnian Zhou, Jingwen Wang, Xiaohu Zheng, and Pierre Delisle, “UTOPIA: A Load sharing Facility for Lagre, Heterogeneous distributed Computer Systems: Technical Report, University of Toronto, CSRI-257, April 1992
“NQE”, commerical product, Cray Research, Eagon, Minn.
Lee, C.C. “Fuzzy Logic in Control Systems”, IEEE Transactions on Systems, Man, and Cybernetics, Vol 20, No. 2, March/April 1990.
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© 1995 Springer-Verlag Berlin Heidelberg
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Kipersztok, O., Patterson, J.C. (1995). Intelligent fuzzy control to augment scheduling capabilities of network queuing systems. In: Feitelson, D.G., Rudolph, L. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP 1995. Lecture Notes in Computer Science, vol 949. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60153-8_32
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DOI: https://doi.org/10.1007/3-540-60153-8_32
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