Adjusted fair scheduling and non-linear workload prediction for QoS guarantees in grid computing

Doulamis, N; Doulamis, A; Litke, A; Panagakis, A; Varvarigou, T; Varvarigos, E

dc.contributor.author	Doulamis, N	en
dc.contributor.author	Doulamis, A	en
dc.contributor.author	Litke, A	en
dc.contributor.author	Panagakis, A	en
dc.contributor.author	Varvarigou, T	en
dc.contributor.author	Varvarigos, E	en
dc.date.accessioned	2014-03-01T01:25:52Z
dc.date.available	2014-03-01T01:25:52Z
dc.date.issued	2007	en
dc.identifier.issn	0140-3664	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17785
dc.subject	Fair grid scheduling	en
dc.subject	Grid-enabled networking middleware	en
dc.subject	Non-linear workload modeling	en
dc.subject	QoS requirements	en
dc.subject	Workload prediction	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.classification	Telecommunications	en
dc.subject.other	Algorithms	en
dc.subject.other	Computer simulation	en
dc.subject.other	Computer software	en
dc.subject.other	Middleware	en
dc.subject.other	Nonlinear systems	en
dc.subject.other	Quality of service	en
dc.subject.other	Fair grid scheduling	en
dc.subject.other	Grid-enabled networking middleware	en
dc.subject.other	Non-linear workload modeling	en
dc.subject.other	QoS requirements	en
dc.subject.other	Workload prediction	en
dc.subject.other	Distributed computer systems	en
dc.title	Adjusted fair scheduling and non-linear workload prediction for QoS guarantees in grid computing	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.comcom.2005.11.013	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.comcom.2005.11.013	en
heal.language	English	en
heal.publicationDate	2007	en
heal.abstract	In this paper, we propose an efficient non-linear task workload prediction mechanism incorporated with a fair scheduling algorithm for task allocation and resource management in Grid computing. Workload prediction is accomplished in a Grid middleware approach using a non-linear model expressed as a series of finite known functional components using concepts of functional analysis. The coefficient of functional components are obtained using a training set of appropriate samples, the pairs of which are estimated based on a runtime estimation model relied on a least squares approximation scheme. The advantages of the proposed non-linear task workload prediction scheme is that (i) it is not constrained by analysis of source code (analytical methods), which is practically impossible to be implemented in complicated real-life applications or (ii) it does not exploit the variations of the workload statistics as the statistical approaches does. The predicted task workload is then exploited by a novel scheduling algorithm, enabling a fair Quality of Service oriented resource management so that some tasks are not favored against others. The algorithm is based on estimating the adjusted fair completion times of the tasks for task order selection and on an earliest completion time strategy for the grid resource assignment. Experimental results and comparisons with traditional scheduling approaches as implemented in the framework of European Union funded research projects GRIA and GRIDLAB grid infrastructures have revealed the outperformance of the proposed method. (c) 2005 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Computer Communications	en
dc.identifier.doi	10.1016/j.comcom.2005.11.013	en
dc.identifier.isi	ISI:000244222500002	en
dc.identifier.volume	30	en
dc.identifier.issue	3	en
dc.identifier.spage	499	en
dc.identifier.epage	515	en