Abstract
In this work we present the design and development of an adaptive task scheduling model which enables the definition and exploitation of a framework especially suitable for managing environments of intensive computing load. The framework supplies queuing mechanisms, priority-based scheduling and resources allocation strategies, load monitoring, and implements fault tolerance procedures. Buffering strategies have been used to reduce idle time for load reposition and to take advantage of I/O overlapping, increasing efficiency in the use of resources. Several tests have been performed using applications from the bioinformatics domain for which adaptive strategies have shown their ability to produce a noticeable reduction on execution time.
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Hidalgo-Conde, M., Rodríguez, A., Ramírez, S., Trelles, O. (2005). Adaptive Task Scheduling in Computational GRID Environments. In: Sloot, P.M.A., Hoekstra, A.G., Priol, T., Reinefeld, A., Bubak, M. (eds) Advances in Grid Computing - EGC 2005. EGC 2005. Lecture Notes in Computer Science, vol 3470. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11508380_90
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DOI: https://doi.org/10.1007/11508380_90
Publisher Name: Springer, Berlin, Heidelberg
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