Download e-book for kindle: Advances in Grid Computing by Zoran Constantinescu

By Zoran Constantinescu

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5 are considered. e. C1 to C5) the weights are having values with an increasing mean from C1 to C5 and also an increasing standard deviation to represent variant weight vector settings. Note that upon moving from C1 to C5 the success rate tends to decrease which is normal as the more the mean of the weight vector increases the more the scheduling process relay on QoS other than the time and cost. This consequently minimizes the set of resource candidates for each task and causes less success rate.

Zhao, D. & Li, J. (2007). Scheduling algorithm based on integrated utility of multiple qos attributes on service grid, GCC ’07: Proceedings of the Sixth International Conference on Grid and Cooperative Computing, IEEE Computer Society, Washington, DC, USA, pp. 288–295. , Munetomo, M. & Akama, K. (2008). Linkage in Evolutionary Computation, Springer Berlin / Heidelberg, chapter Parallel GEAs with Linkage Analysis over Grid, pp. 159–187. , Zic, J. & Chen, S. (2008). Wsla+: Web service level agreement language for collaborations, scc 2: 485–488.

Therefore, it is necessary to provide a language and a tool to specify aggregation formulae, and to allow the schedular to interpret such formulae for estimating the QoS of the grid services. The method by which the framework defines and evaluates subjective QoS attributes is as follows: QoS definition language: For a language to permit specifying new QoS attributes, two things are required; type and scale. The type can be only primitive types (integer, real and Boolean) as in WSLA+ languageNepal et al.

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