Resource failures risk assessment modelling in distributed environments

Service providers offer access to resources and services in distributed environments such as Grids and Clouds through formal Service level Agreements (SLA), and need well-balanced infrastructures so that they can maximise the Quality of Service (QoS) they offer and minimise the number of SLA violations. We propose a mathematical model to predict the risk of failure of resources in such environments using a discrete-time analytical model driven by reliability functions fitted to observed data. The model relies on the resource historical data so as to predict the risk of failure for a given time interval. The model is evaluated by comparing the predicted risk of failure with the observed risk of failure, and is shown to accurately predict the resources risk of failure, allowing a service provider to selectively choose which SLA request to accept

Risk assessment models for resource failure in grid computing

Service Level Agreements (SLAs) are introduced in order to overcome the limitations associated with the best-effort approach in Grid computing, and to accordingly make Grid computing more attractive for commercial uses. However, commercial Grid providers are not keen to adopt SLAs since there is a risk of SLA violation as a result of resource failure, which will result in a penalty fee; therefore, the need to model the resources risk of failure is critical to Grid resource providers. Essentially, moving from the best-effort approach for accepting SLAs to a risk-aware approach assists the Grid resource provider to provide a high-level Quality of Service (QoS). Moreover, risk is an important factor in establishing the resource price and penalty fee in the case of resource failure. In light of this, we propose a mathematical model to predict the risk of failure of a Grid resource using a discrete-time analytical model driven by reliability functions fitted to observed data. The model relies on the resource historical information so as to predict the probability of the resource failure (risk of failure) for a given time interval. The model was evaluated by comparing the predicted risk of failure with the observed risk of failure using availability data gathered from Grids resources. The risk of failure is an important property of a Grid resource, especially when scheduling jobs optimally in relation to resources so as to achieve a business objective. However, in Grid computing, user-centric scheduling algorithms ignore the risk factor and mostly address the minimisation of the cost of the resource allocation, or the overall deadline by which the job must be executed completely. Therefore, we propose a novel user-centric scheduling algorithm for scheduling Bag of Tasks (BoT) applications. The algorithm, which aims to meet user requirements, takes into account the risk of failure, the cost of resources and the job deadline. With this in mind, through simulation, we demonstrate that the algorithm provides a near-optimal solution for minimizing the cost of executing BoT jobs. Also, we show that the execution time of the proposed algorithm is very low, and is therefore suitable for solving scheduling problems in real-time. Risk assessment benefits the resource provider by providing methods to either support accepting or rejecting an SLA. Moreover, it will enable the resource provider to understand the capacity of the infrastructure and to thereby plan future investment. Scheduling algorithms will benefit the resource provider by providing methods to meet user requirements and the better utilisation of resources. The ability to adopt a risk assessment method and user-centric algorithms makes the exploitation of Grid systems more realistic

Risk assessment models for resonance failure in grid computing

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The Relationship between 25 (OH) D Levels (Vitamin D) and Bone Mineral Density (BMD) in a Saudi Population in a Community-Based Setting

<div><p>Background</p><p>Vitamin D deficiency has been linked to an increased risk of osteoporosis. Vitamin D deficiency has reached high levels in the Saudi population, but there is conflicting evidence both in the Saudi population, and worldwide, regarding the existence of a correlation between these low vitamin D levels and reduced BMD (bone mineral density), or osteoporosis.</p><p>Objective</p><p>The objective of this study was primarily to determine whether there was a correlation between vitamin D deficiency and osteoporosis in the Saudi population. We aimed to investigate whether the high levels of vitamin D deficiency and insufficiency would translate to higher prevalence of osteoporosis, and whether there is a correlation between vitamin D levels and bone mineral density.</p><p>Materials and methods</p><p>This was a community based cross sectional study conducted in the Family Medicine Clinics at King Faisal Specialist Hospital and Research Centre in Riyadh, Saudi Arabia. Electronic records of 1723 patients were reviewed. Laboratory and radiology results were collected, including vitamin D levels, calcium levels, and bone mineral density scan results.</p><p>Results</p><p>Among the whole population, 61.5% had moderate to severe vitamin D deficiency with levels less than 50nmol/L. 9.1% of the population had osteoporosis, and 38.6% had osteopenia. Among the whole population, there was no significant correlation between spine or total femoral BMD and serum 25(OH) D.</p><p>Conclusion</p><p>Vitamin D deficiency is prevalent in the Saudi population. However, no correlation has been found between vitamin D deficiency and reduced bone mineral density in any age group, in males or females, Saudis or Non-Saudis, in our population in Riyadh, Saudi Arabia.</p></div

Overview of study population.

<p>Overview of study population.</p

Gender analysis.

<p>Gender analysis.</p