Service level agreements (SLAs), as formal contractual agreements, increase the confidence level between the End User and the Grid Resource provider, as compared to the best effort approach. However, SLAs fail short of assessing the risk in acceptance of the SLA; Risk Assessment in Grid computing fills that gap. Risk Assessment is crucial for the Resource provider as failing to fulfil an SLA will result in facing a financial penalty_ Thus risk, a deterrent to the commercial viability of Grids, needs to be assessed and mitigated to overcome the pitfalls associated with SLAs. The current approaches to assess and manage risk in Grid computing are a major step towards the provisioning of Quality of Service (QoS) to the end-user. However these approaches are based on node or machine level Assessment. As a node may contain CPU(s), storage devices, connections for communication and software resource, consequently a node failure may actually be a failure of any of these components. Our approach towards Risk Assessment is aimed at a granularity level of individual components as compared to machine level in previous efforts. Moreover the past efforts of risk assessment at node level fail short of considering the nature of the Grid Failure data that is repairable or replaceable. Thus to overcome the short comings of the previous efforts, we propose Risk Assessment Model(s) at component level considering the resources repairable and replaceable. A three step methodology was utilized in this work consisting of Data analysis, Risk modelling and Experimentation. The Probabilistic model, proposed at the component level based on senes and parallel model(s) considers Grid Resources as replaceable is based on. Similarly an R-out-N model is proposed for the aggregation of risk values for a number of nodes and provides more detailed results but with some pitfalls, against the parallel model. On the other hand, a risk assessment model at the component level based on NonHomogeneous Poisson Process (NHPP) model is proposed considering Grid Resources as Repairable. Grid failure data is used for the experimentation at the component level. The proposed NHPP based Grid risk model selection is validated by using a goodness of fit test along with graphical approaches. Similarly, considering Grid resources as repairable, a Semi Markov based Risk assessment model is also proposed. The Semi Markov based risk assessment model provides slight advantages over the NHPP based model such as taking repairability extrinsically and assessing the probabilities of repair for an individual components within a node. The three proposed risk models are evaluated by conducting the experimentation and are further evaluated by conducting a comparative evaluation and performance analysis of the proposed models. Detailed risk assessment information at the component level is provided by the experimental results of the proposed risk assessment models which can help enable Grid Resource provider to manage and use the Grid resources efficiently. These results can in turn help enhance the commercial viability and QoS provisioning to End Users by utilization of risk aware scheduling by Grid Resource Provider.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:590154 |
| Date | January 2012 |
| Creators | Sangrasi, Asif |
| Publisher | University of Leeds |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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