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Resource Scheduling Techniques in Utility Computing: A Survey

Resource Scheduling Techniques in Utility Computing: A Survey

Inderveer Chana, Tarandeep Kaur
Copyright: © 2016 |Pages: 21
ISBN13: 9781466695627|ISBN10: 1466695625|EISBN13: 9781466695634
DOI: 10.4018/978-1-4666-9562-7.ch059
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MLA

Chana, Inderveer, and Tarandeep Kaur. "Resource Scheduling Techniques in Utility Computing: A Survey." Business Intelligence: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2016, pp. 1159-1179. https://doi.org/10.4018/978-1-4666-9562-7.ch059

APA

Chana, I. & Kaur, T. (2016). Resource Scheduling Techniques in Utility Computing: A Survey. In I. Management Association (Ed.), Business Intelligence: Concepts, Methodologies, Tools, and Applications (pp. 1159-1179). IGI Global. https://doi.org/10.4018/978-1-4666-9562-7.ch059

Chicago

Chana, Inderveer, and Tarandeep Kaur. "Resource Scheduling Techniques in Utility Computing: A Survey." In Business Intelligence: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1159-1179. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-4666-9562-7.ch059

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Abstract

Utility Computing offers on-demand services from a shared pool of resources and can be envisaged to be a benchmark in the IT development. The capability to provide on-demand services involves management of large number of resources that are geographically dispersed and thus poses a number of resource management and scheduling challenges in the domain of resource heterogeneity, dynamic resource locations and load balancing. Proficient resource allocations and efficient scheduling helps in achieving optimal resource utilization and hence enhances the performance of the system. This paper evaluates existing resource management systems, listing their key characteristic features and highlighting the factors that make the existing systems excel upon each other. It also discusses various resource scheduling techniques currently available and characterizes the techniques based on Quality of Service (QoS) parameters supported by them along with the classification on basis of their operating environment and further extends towards load balancing and energy efficiency support if available.

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