Resource allocation decision model for dependable and cost-effective grid applications based on Grid Bank
Distributed and parallel computing systems such as grid- or cloud-computing have been widely applied, studied and developed for various large-scale computing requirements in cross-administrative domains. However, two important issues, the economy of computation and the dependability of service-orien...
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| Vydané v: | Future generation computer systems Ročník 77; s. 12 - 28 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier B.V
01.12.2017
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| ISSN: | 0167-739X, 1872-7115 |
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| Abstract | Distributed and parallel computing systems such as grid- or cloud-computing have been widely applied, studied and developed for various large-scale computing requirements in cross-administrative domains. However, two important issues, the economy of computation and the dependability of service-oriented computing, have not been thoroughly deliberated. In this regard, we formulate a grid resource allocation decision model that includes (1) a service reliability assessment, which derives the computing dependability from the universal generating function methodology (UGFM), and (2) a virtual payment assessment, which appraises the service expense for the contribution of each resource based on the expense function. For the near-optimal (or optimal) non-dominant solutions (service expense and service reliability), this paper presents two bi-objective soft-computing techniques, PC-GA (genetic algorithm) and PC-PSO (particle swarm optimization), where the Pareto-set cluster (PC) contains elite-selected and reborn mechanisms to generate new non-dominant solutions and strengthen the optimization effectiveness of the Pareto frontier. Finally, a virtual grid system is provided as a case study to illustrate the performance of two optimization methodologies and to analyze the pros and cons in terms of different resource allocation decisions.
•A resource allocation decision model is proposed for dependable and cost-effective reciprocal transactions based on Grid Bank.•The UGFM derives the joint PMF of execution time and the service expense for the completion probability of the grid-computing service.•The virtual payment assessment appraises the service expense regarding the contribution of each resource.•A satisfactory resource allocation is derived by the PC-GA for decision makers in terms of different SLA scenarios. |
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| AbstractList | Distributed and parallel computing systems such as grid- or cloud-computing have been widely applied, studied and developed for various large-scale computing requirements in cross-administrative domains. However, two important issues, the economy of computation and the dependability of service-oriented computing, have not been thoroughly deliberated. In this regard, we formulate a grid resource allocation decision model that includes (1) a service reliability assessment, which derives the computing dependability from the universal generating function methodology (UGFM), and (2) a virtual payment assessment, which appraises the service expense for the contribution of each resource based on the expense function. For the near-optimal (or optimal) non-dominant solutions (service expense and service reliability), this paper presents two bi-objective soft-computing techniques, PC-GA (genetic algorithm) and PC-PSO (particle swarm optimization), where the Pareto-set cluster (PC) contains elite-selected and reborn mechanisms to generate new non-dominant solutions and strengthen the optimization effectiveness of the Pareto frontier. Finally, a virtual grid system is provided as a case study to illustrate the performance of two optimization methodologies and to analyze the pros and cons in terms of different resource allocation decisions.
•A resource allocation decision model is proposed for dependable and cost-effective reciprocal transactions based on Grid Bank.•The UGFM derives the joint PMF of execution time and the service expense for the completion probability of the grid-computing service.•The virtual payment assessment appraises the service expense regarding the contribution of each resource.•A satisfactory resource allocation is derived by the PC-GA for decision makers in terms of different SLA scenarios. |
| Author | Yeh, Wei-Chang Wei, Shang-Chia |
| Author_xml | – sequence: 1 givenname: Shang-Chia surname: Wei fullname: Wei, Shang-Chia email: wsc@tgic.org.tw, waisunga@gmail.com organization: Planning & Training Division, Taiwan Geographic Information Center, Taiwan – sequence: 2 givenname: Wei-Chang surname: Yeh fullname: Yeh, Wei-Chang email: yeh@ieee.org organization: Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Taiwan |
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