Performance evaluation and resource management in enterprise systems
Xue, James Wen Jun (2009) Performance evaluation and resource management in enterprise systems. PhD thesis, University of Warwick.Full text not available from this repository.
Official URL: http://webcat.warwick.ac.uk/record=b2283140~S9
This thesis documents research conducted as part of an EPSRC (EP/C53 8277/01) project whose aim was to understand, capture and dene the service requirements of cluster-supported enterprise systems. This research includes developing techniques to verify that the infrastructure is delivering on its agreed service requirements and a means of dynamically adjusting the operating policies if the service requirements are not being met. The research in this thesis falls into three broad categories: 1) the performance evaluation of data persistence in distributed enterprise applications; 2) Internet workload management and request scheduling; 3) dynamic resource allocation in server farms. Techniques for request scheduling and dynamic resource allocation are developed, with the aim of maximising the total revenue from dierent applications run in an Internet service hosting centre. Given that data is one of the most important assets of a company, it is essential that enterprise systems should be able to create, retrieve, update and delete data eectively. Web-based applications require application data and session data, and the persistence of these data is critical to the success of the business. However, data persistence comes at a cost as it introduces a performance overhead to the system. This thesis reports on research using state-of-the-art enterprise computing architectures to study the performance overheads of data persistence. Internet service providers (ISPs) are bound by quality of service (QoS) agreements with their clients. Since dierent applications serve various types of request, each with an associated value, some requests are more important than others in terms of revenue contribution. This thesis reports on the development of a priority, queue-based request scheduling scheme, which positions waiting requests in their relevant queues based on their priorities. In so doing, more important requests are processed sooner even though they may arrive in the system later than others. An experimental evaluation of this approach is conducted using an eventdriven simulator; the results demonstrate promising results over a number of existing methods in terms of revenue contribution. Due to the bursty nature of web-based workload, it is very diffcult to manage server resources in an Internet hosting centre. Static approaches such as resource provisioning either result in wasted resource (i.e., underutilisation in light loaded situations) or oer no help if resources are overutilised. Therefore, dynamic approaches to resource management are needed. This thesis proposes a bottleneck-aware, dynamic server switching policy, which is used in combination with an admission control scheme. The objective this scheme is to optimise the total revenue in the system, while maintaining the QoS agreed across all server pools in the hosting centre. A performance evaluation is conducted via extensive simulation, and the results show a considerable improvement from the bottleneck-aware server switching policy over a proportional allocation policy and a system that implements no dynamic server switching.
|Item Type:||Thesis or Dissertation (PhD)|
|Subjects:||Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software|
|Library of Congress Subject Headings (LCSH):||Application software -- Research, Application software -- Development, Enterprise application integration (Computer systems), Computer networks -- Workload, Computer networks -- Management|
|Institution:||University of Warwick|
|Theses Department:||Department of Computer Science|
|Supervisor(s)/Advisor:||Jarvis, Stephen A., 1970-|
|Sponsors:||Engineering and Physical Sciences Research Council (Great Britain) (EPSRC) (EP/C53 8277/01)|
|Extent:||204 leaves : ill., charts|
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