/pdf/detailed-d-program-d-of-d-the-d-2010-d-ieee-d-international-31a4zt8nud.pdf

Detailed ऀð Program ऀð of ऀð the ऀð 2010 ऀð IEEE ऀð International ऀð Conference ऀð on ऀð Networking, ऀð Architecture ऀð and ऀð Storage ऀð (NAS) ऀð

Web Service Selection AlgorithmBased on Adaptive Framework

In service composition,due to dynamic changes in the environment and reasons for the services itself,the behavior of the Web services involved in service composition may evolve and influence the service composition results.An adaptive service selection framework is proposed to solve the problem.The information from public service registries is captured and recorded locally in the binding repository,then link analysis algorithm is applied to the binding repository to get the highly linked services at the moment for service selection.Simulation experiment results show that the framework and the algorithm can select high-quality services dynamically,and reduce the failure rate of service composition results caused by evolving Quality of Service(QoS).

Web Service Selection Algorithm Based on Adaptive Framework

For those outsourcing data centers hosting different applications or services, blade server is becoming the most popular solution But the deployment of systems in such data centers will be a time-consuming and cumbersome task Moreover, the service provided by the servers in data center changed frequently, which require a flexible service management system to reduce the burden of the system administrator This paper presents the Bladmin (Blade Admin) system to provide dynamic, flexible and quick service and operation system deployment It can build a Virtual Environment (VE) for each service All the nodes in the VE serves for one certain kind of application and some nodes have to be shift from one VE to another to adopt the varying workloads Experiment results demonstrate that system-level performance has been greatly improved and the running of one Paradigm job also show the efficiency of Bladmin framework.

Research and design of deployment framework for blade-based data center

In shared data centres, accurate models of workloads are indispensable in the process of autonomic resource scheduling. Facing the problem of parameterizing the vast space of big MAPs in order to fit the real workload traces with time-varying characteristics, in this paper we propose a MAP fitting approach JAMC with joint approximation of the order moment and the lag correlation. Based on the state-of-the-art fitting method KPC, JAMC uses a similar divide and conquer approach to simplify the fitting problem and uses optimization to explore the best solution. Our experiments show that JAMC is simple and sufficient enough to effectively predict the behavior of the queueing systems, and the fitting time cost of a few minutes is acceptable for shared data center. Through the analysis of the sensitivity to the orders fitted, we deduce that it is not the case that the higher orders have better results. In the case of Bellcore Aug89, the appropriate fitted orders for the moments and autocorrelations should be respectively on a set of 10~20 and 10000~30000.

A MAP Fitting Approach with Joint Approximation Oriented to the Dynamic Resource Provisioning in Shared Data Centres

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Research and design of deployment framework for blade-based data center

A MAP Fitting Approach with Joint Approximation Oriented to the Dynamic Resource Provisioning in Shared Data Centres