Abstract
The paper describes a solution to the key problem of ensuring high performance behavior of the Grid, namely the scheduling of activities. It presents a distributed, fault-tolerant, scalable and efficient solution for optimizing task assignment. The scheduler uses a combination of genetic algorithms and lookup services for obtaining a scalable and highly reliable optimization tool. The experiments have been carried out on the MonALISA monitoring environment and its extensions. The results demonstrate very good behavior in comparison with other scheduling approaches.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11914952_55.
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Iordache, G.V., Boboila, M.S., Pop, F., Stratan, C., Cristea, V. (2006). A Decentralized Strategy for Genetic Scheduling in Heterogeneous Environments. In: Meersman, R., Tari, Z. (eds) On the Move to Meaningful Internet Systems 2006: CoopIS, DOA, GADA, and ODBASE. OTM 2006. Lecture Notes in Computer Science, vol 4276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11914952_13
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DOI: https://doi.org/10.1007/11914952_13
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