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A flexible model supporting QoS and reallocation for grid applications

The rise of business-oriented and commercial applications for Grid computing environments has recently gathered pace. Grid computing traditionally has been linked with scientific environments, where heterogeneous resources provided by Grid systems and infrastructures were employed for carrying out computationally-intensive and data-intensive scientific experiments or applications that may have not been possible before. The natural progression is that business-oriented applications will look to build on this success and utilise the large number of heterogeneous Grid resources including computational resources such as CPUs and memory and storage resources such as disk space, potentially available. The success of introducing these applications into the mainstream is directly related to whether service providers can deliver a level of Quality of Service (QoS) to a consumer and the ability of the consumer to request high-level QoS such as the numbers of CPUs required or the RAM required. QoS refers to the guidelines and requirements requested by a user/consumer from the service providers and resources. The communication and agreement establishment processes between user and provider must be defined clearly to accommodate a new type of user where knowledge of the underlying infrastructure cannot be assumed. QoS parameters have generally been defined at the Grid resource level using low level definitions. This tailors to specific applications and models related to scientific domains where brokering, scheduling and QoS delivery is designed for specific applications within specific domains. This thesis presents a flexible model for high-level QoS requests. Business Grid Quality of Service (BGQoS) is introduced for business-oriented and commercial Grid applications which may wish to make use of the resources made available by Grid system environments. BGQoS allows GRCs (Grid Resource Consumers) to specify varying types of high-level QoS requirements which are delivered via querying up-to-date resource information, matchmaking and monitoring operations. Moreover, we present dynamically calculated metrics for measuring QoS such as reliability, increasing the accuracy of meeting the GRC’s requirements. On the other hand GRPs (Grid Resource Provider) are also capable of advertising their resources, their capabilities, their usage policies and availability both locally and globally. This leads to a flexible model that could be carried across domains without altering the core operations and which could easily be expanded in order to accommodate different types of GRC, resources and applications.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:628921
Date January 2011
CreatorsAl Bodour, R.
PublisherCoventry University
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://curve.coventry.ac.uk/open/items/208265d9-ee5d-4c88-a955-466c9fc3dfa3/1

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