Methods of resource management in problem-oriented computing environment
One of the important classes of computational problems is problem-oriented workflow applications executed in distributed computing environment. A problem-oriented workflow application can be represented by a directed graph whose vertices are tasks and arcs are data flows. For a problem-oriented workflow application, we can get a priori estimates of the task execution time and the amount of data to be transferred between the tasks. A distributed computing environment designed for the execution of such tasks in a certain subject domain is called problem-oriented environment. To efficiently use resources of the distributed computing environment, special scheduling algorithms are applied. Nowadays, a great number of such algorithms have been proposed. Some of them (like the DSC algorithm) take into account specific features of problem-oriented workflow applications. Others (like Min–Min algorithm) take into account many-core structure of nodes of the computational network. However, none of them takes into account both factors. In this paper, a mathematical model of problem-oriented computing environment is constructed, and a new problem-oriented scheduling (POS) algorithm is proposed. The POS algorithm takes into account both specifics of the problem-oriented jobs and multi-core structure of the computing system nodes. Results of computational experiments comparing the POS algorithm with other known scheduling algorithms are presented.
KeywordsSchedule Algorithm Directed Acyclic Graph Communication Cost Critical Path Computing Node
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