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One of the key promises of IT strategic outsourcing is to deliver greater IT service management through better quality and lower cost. However, this raises a critical question on how to model highly variable services for diverse customers with heterogeneous infrastructure and service demands. In this paper we propose the use of statistical learning approaches for service operation variability modeling...
An algorithm for predicting the quality of video received by a client from a shared server is presented. A statistical model for this client-server system, in the presence of other clients, is proposed. Our contribution is that we explicitly account for the interfering clients, namely the load. Once the load on the system is understood, accurate client-server predictions are possible with an accuracy...
Cloud infrastructures have seen increasing popularity for addressing the growing computational needs of today's scientific and engineering applications. However, resource management challenges exist in the elastic cloud environment, such as resource provisioning and task allocation, especially when data movement between multiple domains plays an important role. In this work, we study the impact of...
Combining enterprise architecture and operational data is complex (especially when considering the actual 'matching' of data with enterprise architecture objects), and little has been written on how to do this. Therefore, in this paper we aim to fill this gap and propose a method to combine operational data with enterprise architecture to better support decision-making. Using such a method may result...
In modern IT systems, data backup and restore operations are essential for providing protection against data loss from both natural and man-made incidents. On the other hand, data backup and restore operations can be resource-intensive and lead to performance degradation, or may require the system to be offline entirely. Therefore, it is important to properly choose backup and restore techniques and...
Providing high availability in a diverse client demand scenario is a key challenge of cloud computing providers. A possible approach to protect cloud systems from natural disasters corresponds to the utilization of redundant data centers located far enough apart. The time to migrate a virtual machine (VM) from a data center to another increases due to distance. As this time impacts the overall system...
Virtual machine (VM) live migration, the key problem of modern virtualized data centers, is a challenging task since 1) Frequent traffic across data center between coupling VMs limits the efficiency of current methods. 2) Most existing approaches suffered from poor scalability issues as multi-objective optimization is still an open question in these designs. To address these problems, in this paper,...
The capability to analyze systems and applications is commonly needed in data centers to address diverse problems such as root cause analysis of performance problems and failures, investigation of security attack propagation, and problem determination for predictive maintenance. Such analysis is typically facilitated by a hodgepodge of procedural code and scripts representing heuristics to be applied,...
Common data center energy efficiency metrics only work on a high abstraction level and require actually measured values. With these metrics, it is not possible to identify the sources of shortcomings in efficiency or to explore possible changes in configuration or architecture, respectively. In this paper, an alternative metric addressing these drawbacks is introduced. The metric makes use of pre-characterized...
Monitoring and predicting resource consumption is a fundamental need when running a virtualized system. Predicting resources is necessary because cloud infrastructures use virtual resources on demand. Current monitoring tools are insufficient to predict resource usage of virtualized systems so, without proper monitoring, virtualized systems can suffer down time, which can directly affect cloud infrastructure...
MapReduce has gained in popularity as a distributed data analysis paradigm, particularly in the cloud, where MapReduce jobs are run on virtual clusters. The provisioning of MapReduce jobs in the cloud is an important problem for optimizing several user as well as provider-side metrics, such as runtime, cost, throughput, energy, and load. In this paper, we present an intelligent provisioning framework...
Configuration management is a complex task, even for experienced system administrators, which makes self-managing systems a desirable solution. Self-management implies the need for a model based on which configuration changes may be decided. In previous work, we described a method for constructing a state-transition model of application behavior, by observing the application in simulation. This method...
Designing data centers with adequate performance and at the right scale is a difficult task. The load in terms of network and CPU utilization is hard to estimate without appropriate tools. In this paper we introduce a data center performance estimation system which can support planning data centers and application deployments. The tool takes data center topologies and applications and calculates the...
With the repaid development of multi-media and network, information are generated and spread quickly than before. New application such as search engine, video share depends on the scale and access speed of huge data set. Data-intensive computing became a hot point of computer science. In Data-intensive environments, data access ability is the bottleneck instead of computing ability. In this paper,...
As computers become more and more networked, and more bandwidth will be consumed by network flow because customers will be connected through networks which will transfer files and data, such as video files (MPEGn, AVI, WMV, etc.) to be watched at a customer's computer. The main purpose of this paper is exploring more researches that were developed before for low bandwidth and less storage space where...
This paper describes an approach for designing a power management plan that matches the supply of power with the demand for power in data centers. Power may come from the grid, from local renewable sources, and possibly from energy storage subsystems. The supply of renewable power is often time-varying in a manner that depends on the source that provides the power, the location of power generators,...
Today's data centers consume vast amounts of energy, leading to high operational costs, excessive water consumption, and significant greenhouse gas emissions. With the approach of micro grids, an opportunity exists to reduce the environmental impact and cost of power in data centers. To realize this, demand side power consumption needs to be understood and co-managed from the perspectives of both...
Performance model interchange formats are common representations for data that can be used to move models among modeling tools. The Experiment Schema Extension (Ex-SE) provides a means of specifying performance studies (model runs and output). PN-Ex is an extended instantiation of the Ex-SE for Petri nets. This paper presents an experimental framework for PIPE2. A case study demonstrates the use of...
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