The Experts below are selected from a list of 9657 Experts worldwide ranked by ideXlab platform

Zalinda Othman - One of the best experts on this subject based on the ideXlab platform.

  • review Cloud Computing Service composition a systematic literature review
    Expert Systems With Applications, 2014
    Co-Authors: Amin Jula, Elankovan A Sundararajan, Zalinda Othman
    Abstract:

    The increasing tendency of network Service users to use Cloud Computing encourages web Service vendors to supply Services that have different functional and nonfunctional (quality of Service) features and provide them in a Service pool. Based on supply and demand rules and because of the exuberant growth of the Services that are offered, Cloud Service brokers face tough competition against each other in providing quality of Service enhancements. Such competition leads to a difficult and complicated process to provide simple Service selection and composition in supplying composite Services in the Cloud, which should be considered an NP-hard problem. How to select appropriate Services from the Service pool, overcome composition restrictions, determine the importance of different quality of Service parameters, focus on the dynamic characteristics of the problem, and address rapid changes in the properties of the Services and network appear to be among the most important issues that must be investigated and addressed. In this paper, utilizing a systematic literature review, important questions that can be raised about the research performed in addressing the above-mentioned problem have been extracted and put forth. Then, by dividing the research into four main groups based on the problem-solving approaches and identifying the investigated quality of Service parameters, intended objectives, and developing environments, beneficial results and statistics are obtained that can contribute to future research.

  • Cloud Computing Service composition: A systematic literature review
    Expert Systems with Applications, 2014
    Co-Authors: Amin Jula, Elankovan Sundararajan, Zalinda Othman
    Abstract:

    The increasing tendency of network Service users to use Cloud Computing encourages web Service vendors to supply Services that have different functional and nonfunctional (quality of Service) features and provide them in a Service pool. Based on supply and demand rules and because of the exuberant growth of the Services that are offered, Cloud Service brokers face tough competition against each other in providing quality of Service enhancements. Such competition leads to a difficult and complicated process to provide simple Service selection and composition in supplying composite Services in the Cloud, which should be considered an NP-hard problem. How to select appropriate Services from the Service pool, overcome composition restrictions, determine the importance of different quality of Service parameters, focus on the dynamic characteristics of the problem, and address rapid changes in the properties of the Services and network appear to be among the most important issues that must be investigated and addressed. In this paper, utilizing a systematic literature review, important questions that can be raised about the research performed in addressing the above-mentioned problem have been extracted and put forth. Then, by dividing the research into four main groups based on the problem-solving approaches and identifying the investigated quality of Service parameters, intended objectives, and developing environments, beneficial results and statistics are obtained that can contribute to future research. © 2013 Elsevier Ltd. All rights reserved.

  • A New Dataset and Benchmark for Cloud Computing Service Composition
    2014 5th International Conference on Intelligent Systems Modelling and Simulation, 2014
    Co-Authors: Amin Jula, Elankovan Sundararajan, Hamid Nilsaz, Zalinda Othman
    Abstract:

    Cloud Computing as an effective Computing approach is attracting increasingly the attention of heavy processing applicants to its capabilities. Cloud suppliers try to prevent any Service-request unanswered utilizing a large number of Service providers. Selecting optimal unique-Services in Cloud Computing Service composition (CCSC) is a noteworthy problem that must be addressed extremely accurate and scrupulously. Recently, considerable studies have been done for solving CCSC, however lack of widely accepted and reliable CCSC problems for fair and equitable comparison of proposing methods, is a blind spot and should be considered as a high-priority problem. In this paper, a reliable set of ten CCSC problems is introduced (CCSC_Benchmark) which is prepared to be used as a "standard test" in future works. To complete the usability of the problem set, the best solutions of the generated problems are also found and presented to provide a facility for calculating error rate of the proposed methods.

Jie Xu - One of the best experts on this subject based on the ideXlab platform.

  • An Economic Analysis of Cloud Computing Service Using Reclaimed Resources
    2019 IEEE 12th International Conference on Cloud Computing (CLOUD), 2019
    Co-Authors: Haiying Shen, Jie Xu
    Abstract:

    Resource under-utilization is prevalent in data centers as a result of substantial stochastic workload variations and resource provision guarantee for the requirements to provide high-level Service availability. To avoid resource under-utilization, recently, the Economy Cloud Computing Service class (Economy class in short) is proposed that sells allocated but unused (i.e., reclaimed) physical resources with long-term Service level objectives (SLOs). Though the Economy class would lead to revenue benefit, how much of the reclaimed resources should be used as the Economy class (i.e., capacity planning) and how to set its price and SLAs to maximize revenue benefit have not been studied. To address this problem, in this paper, we propose a multi-level SLA for Economy class, which has multiple levels of SLOs and penalty. We then present a rigorous theoretical analysis on the capacity planning and pricing of the new Economy class with an objective to maximize the revenue of the Cloud Computing Service provider. Theoretical results are validated using resource utilization data derived from a publicly available Google cluster workload trace dataset.

  • Cloud - An Economic Analysis of Cloud Computing Service Using Reclaimed Resources
    2019 IEEE 12th International Conference on Cloud Computing (CLOUD), 2019
    Co-Authors: Haiying Shen, Jie Xu
    Abstract:

    Resource under-utilization is prevalent in data centers as a result of substantial stochastic workload variations and resource provision guarantee for the requirements to provide high-level Service availability. To avoid resource under-utilization, recently, the Economy Cloud Computing Service class (Economy class in short) is proposed that sells allocated but unused (i.e., reclaimed) physical resources with long-term Service level objectives (SLOs). Though the Economy class would lead to revenue benefit, how much of the reclaimed resources should be used as the Economy class (i.e., capacity planning) and how to set its price and SLAs to maximize revenue benefit have not been studied. To address this problem, in this paper, we propose a multi-level SLA for Economy class, which has multiple levels of SLOs and penalty. We then present a rigorous theoretical analysis on the capacity planning and pricing of the new Economy class with an objective to maximize the revenue of the Cloud Computing Service provider. Theoretical results are validated using resource utilization data derived from a publicly available Google cluster workload trace dataset.

  • Optimal Pricing and Capacity Planning of a New Economy Cloud Computing Service Class
    2015 International Conference on Cloud and Autonomic Computing, 2015
    Co-Authors: Jie Xu, Chenbo Zhu
    Abstract:

    Resource under-utilization in Cloud Computing systems is widespread due to workload fluctuations and drives up the cost of Cloud Computing Service. Offering Service using slack resources in an opportunistic way improves the utilization of resources and the economics of Cloud Service providers. But Opportunistic Service class comes with virtually no Service level objectives (SLO) and thus is of limited use. In a recent study, a new Economy class was introduced to provide long-term SLOs using reclaimed Cloud Computing resources. Analysis based on the workload collected on six production Cloud Computing clusters at Google demonstrated the potential of the Economy class. This paper presents an analytic study on the optimal pricing and capacity planning of this new Economy class. We show that depending on the terms of the Service level agreements and the characteristics of the Cloud Computing workloads, a Cloud Service provider may either choose a penalty averse or penalty preference strategy when allocating reclaimed Computing resources to the Economy class Cloud Computing Service. We also derive conditions under which the new Economy class will be profitable.

Amin Jula - One of the best experts on this subject based on the ideXlab platform.

  • review Cloud Computing Service composition a systematic literature review
    Expert Systems With Applications, 2014
    Co-Authors: Amin Jula, Elankovan A Sundararajan, Zalinda Othman
    Abstract:

    The increasing tendency of network Service users to use Cloud Computing encourages web Service vendors to supply Services that have different functional and nonfunctional (quality of Service) features and provide them in a Service pool. Based on supply and demand rules and because of the exuberant growth of the Services that are offered, Cloud Service brokers face tough competition against each other in providing quality of Service enhancements. Such competition leads to a difficult and complicated process to provide simple Service selection and composition in supplying composite Services in the Cloud, which should be considered an NP-hard problem. How to select appropriate Services from the Service pool, overcome composition restrictions, determine the importance of different quality of Service parameters, focus on the dynamic characteristics of the problem, and address rapid changes in the properties of the Services and network appear to be among the most important issues that must be investigated and addressed. In this paper, utilizing a systematic literature review, important questions that can be raised about the research performed in addressing the above-mentioned problem have been extracted and put forth. Then, by dividing the research into four main groups based on the problem-solving approaches and identifying the investigated quality of Service parameters, intended objectives, and developing environments, beneficial results and statistics are obtained that can contribute to future research.

  • Cloud Computing Service composition: A systematic literature review
    Expert Systems with Applications, 2014
    Co-Authors: Amin Jula, Elankovan Sundararajan, Zalinda Othman
    Abstract:

    The increasing tendency of network Service users to use Cloud Computing encourages web Service vendors to supply Services that have different functional and nonfunctional (quality of Service) features and provide them in a Service pool. Based on supply and demand rules and because of the exuberant growth of the Services that are offered, Cloud Service brokers face tough competition against each other in providing quality of Service enhancements. Such competition leads to a difficult and complicated process to provide simple Service selection and composition in supplying composite Services in the Cloud, which should be considered an NP-hard problem. How to select appropriate Services from the Service pool, overcome composition restrictions, determine the importance of different quality of Service parameters, focus on the dynamic characteristics of the problem, and address rapid changes in the properties of the Services and network appear to be among the most important issues that must be investigated and addressed. In this paper, utilizing a systematic literature review, important questions that can be raised about the research performed in addressing the above-mentioned problem have been extracted and put forth. Then, by dividing the research into four main groups based on the problem-solving approaches and identifying the investigated quality of Service parameters, intended objectives, and developing environments, beneficial results and statistics are obtained that can contribute to future research. © 2013 Elsevier Ltd. All rights reserved.

  • A New Dataset and Benchmark for Cloud Computing Service Composition
    2014 5th International Conference on Intelligent Systems Modelling and Simulation, 2014
    Co-Authors: Amin Jula, Elankovan Sundararajan, Hamid Nilsaz, Zalinda Othman
    Abstract:

    Cloud Computing as an effective Computing approach is attracting increasingly the attention of heavy processing applicants to its capabilities. Cloud suppliers try to prevent any Service-request unanswered utilizing a large number of Service providers. Selecting optimal unique-Services in Cloud Computing Service composition (CCSC) is a noteworthy problem that must be addressed extremely accurate and scrupulously. Recently, considerable studies have been done for solving CCSC, however lack of widely accepted and reliable CCSC problems for fair and equitable comparison of proposing methods, is a blind spot and should be considered as a high-priority problem. In this paper, a reliable set of ten CCSC problems is introduced (CCSC_Benchmark) which is prepared to be used as a "standard test" in future works. To complete the usability of the problem set, the best solutions of the generated problems are also found and presented to provide a facility for calculating error rate of the proposed methods.

Maria Salama - One of the best experts on this subject based on the ideXlab platform.

  • A Novel QoS-Based Framework for Cloud Computing Service Provider Selection
    International Journal of Cloud Applications and Computing, 2014
    Co-Authors: Maria Salama, C. Yeo, James Broberg, Srikumar Venugopal, Ivona Brandic, Amir Zeid, Ahmed Shawish, Xiaohong Jiang, Rajkumar Buyya, Liu Chunlin
    Abstract:

    Cloud Computing is a promising Computing paradigm that provides flexible, Internet-accessible resources allocation on demand on a pay-as-you-go basis. With the growth and expansion of Cloud Services and participation of various Services providers, the description of quality parameters and measurement units started to diverse and sometimes contradict. Such ambiguity does not only result in the raise of various QoS interoperability problems, but also in the distraction of the Services consumers who find themselves unable to match their quality requirements with the providers' offerings. Influenced by such diversity, the available QoS models are limited to either cost-benefit analysis or performance evaluation, without being able to cover a comprehensive set of well-defined quality aspects. In this paper, we provide a complete framework for such problem. We firstly propose a novel QoS ontology that combine and define all of the existing quality aspects in a unified way to efficiently overcome all existing diversity. Using such ontology, we propose a comprehensive broad QoS model combining all quality parameters of both Service providers and consumers for different Cloud platforms. We then propose a mathematical model addressing the Cloud Computing Service provider selection optimization problem based on QoS-guarantee. The proposed model reports an efficient matching with the market-oriented different platforms characteristics; validated through extensive simulation studies conducted on benchmark data of Content Delivery Network providers.

  • Integrated QoS utility-based model for Cloud Computing Service provider selection
    Proceedings - International Computer Software and Applications Conference, 2012
    Co-Authors: Maria Salama, Amir Zeid, Ahmed Shawish, Mohamed Kouta
    Abstract:

    Cloud Computing is gaining a considerable attention in the past few years. It changes the way people acquire software and hardware as it provides them as Services through internet on-demand following a pay-as-you-go financial model. With the exponential increase of such Service, selecting the optimal provider based on predefined Quality of Service (QoS) requirements becomes crucial. The current techniques are just designed for performance evaluation and cost-benefit analysis; yet optimal Service provider selection based on a group of QoS requirements is still uncovered as it should be. In this paper we propose a mathematical model addressing the Cloud Service provider selection optimization problem based on QoS guarantees. The proposed model efficiently matches with the characteristics of market-oriented platforms covering a wide range of Service provider selection problems. The efficiency of the proposed model is validated through simulation studies.

Liu Chunlin - One of the best experts on this subject based on the ideXlab platform.

  • A Novel QoS-Based Framework for Cloud Computing Service Provider Selection
    International Journal of Cloud Applications and Computing, 2014
    Co-Authors: Maria Salama, C. Yeo, James Broberg, Srikumar Venugopal, Ivona Brandic, Amir Zeid, Ahmed Shawish, Xiaohong Jiang, Rajkumar Buyya, Liu Chunlin
    Abstract:

    Cloud Computing is a promising Computing paradigm that provides flexible, Internet-accessible resources allocation on demand on a pay-as-you-go basis. With the growth and expansion of Cloud Services and participation of various Services providers, the description of quality parameters and measurement units started to diverse and sometimes contradict. Such ambiguity does not only result in the raise of various QoS interoperability problems, but also in the distraction of the Services consumers who find themselves unable to match their quality requirements with the providers' offerings. Influenced by such diversity, the available QoS models are limited to either cost-benefit analysis or performance evaluation, without being able to cover a comprehensive set of well-defined quality aspects. In this paper, we provide a complete framework for such problem. We firstly propose a novel QoS ontology that combine and define all of the existing quality aspects in a unified way to efficiently overcome all existing diversity. Using such ontology, we propose a comprehensive broad QoS model combining all quality parameters of both Service providers and consumers for different Cloud platforms. We then propose a mathematical model addressing the Cloud Computing Service provider selection optimization problem based on QoS-guarantee. The proposed model reports an efficient matching with the market-oriented different platforms characteristics; validated through extensive simulation studies conducted on benchmark data of Content Delivery Network providers.