User-side cloud service management: State-of-the-art and future directions
TL;DR: This paper presents a comprehensive state-of-the-art discussion on the existing approaches to cloud service management, critically evaluates them against the factors required for the user to manage the cloud service and presents a framework that assists theCloud service user in making cloud service Management decisions.
About: This article is published in Journal of Network and Computer Applications.The article was published on 2015-09-01. It has received 31 citations till now. The article focuses on the topics: Cloud testing & Cloud computing security.
Citations
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TL;DR: A systematic literature review based on Evaluation Theory, a theory that generalizes six evaluation components, target, criteria, yardstick, data gathering techniques, synthesis techniques, and evaluation process, provides the relative strengths and weaknesses of the different CSEMs and offers a basis for researchers and decision makers to develop improvedCSEMs.
52 citations
TL;DR: A time-aware approach to predict the trustworthiness ranking of cloud services, with the tradeoffs between performance-cost and potential risks in multiple periods is proposed, and an improved ELECTRE method is developed to solve the problem.
Abstract: The imprecise quality of service (QoS) evaluations from consumers may lead to the inappropriate prediction for the trustworthiness of cloud services in an uncertain cloud environment. The service ranking prediction is a promising idea to overcome this deficiency of values prediction approaches by probing the ordering relations between cloud services concealed in the imprecise evaluations. To address the challenges for trustworthy service selection resulting from fluctuating QoS, flexible service pricing and complicated potential risks, this paper proposes a time-aware approach to predict the trustworthiness ranking of cloud services, with the tradeoffs between performance-cost and potential risks in multiple periods. In this approach, the interval neutrosophic set (INS) theory is utilized to describe and assess the performance-costs and potential risks of cloud services: (1) the original evaluation data about cloud services are preprocessed into the trustworthiness interval neutrosophic numbers (INNs); (2) the new INS operators are proposed with the theoretical proofs to calculate the possibility degree and the ranking values of trustworthiness INNs, contributing to the identification of the neighboring users based on the Kendall rank correlation coefficient (KRCC). The problem of time-aware trustworthiness ranking prediction is formulated as a multi-criterion decision-making (MCDM) problem of creating a ranked services list using INS, and an improved ELECTRE method is developed to solve it. The proposed approach is verified by experiments based on an appropriate baseline for comparative analysis. The experimental results demonstrate that the proposed approach can achieve a better prediction quality than the existing approach. The results also show that our approach works effectively in the risk-sensitive and performance-cost-sensitive application scenarios and prevent the malignant price competition launched by low-quality services.
44 citations
TL;DR: The TOPSIS method is extended by using the Minkowski distance and the applicability of the proposed E-TOPSIS approach is presented in a case study for CSPs evaluation and ranking in relation to a set of Service Measurement Index SMI criteria.
Abstract: There are many Cloud Service Providers (CSPs) in the global cloud computing market and customers may need to use scientific decision making methods for evaluating and ranking the CSPs according to their own requirements. Among the several approaches that have been proposed to solve the CSPs evaluation and ranking problem, there are Multi Attribute Decision Making (MADM) methods. One of the most commonly used MADM method is Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). In this paper, we extend the TOPSIS method by using the Minkowski distance. We propose an Extended TOPSIS (E-TOPSIS) approach by varying the parameter p in the Minkowski distance. The applicability of the proposed E-TOPSIS approach is presented in a case study for CSPs evaluation and ranking in relation to a set of Service Measurement Index SMI criteria. An analysis of E-TOPSIS solutions and the CSPs order change relative to parameter p variation is realized. A comparison of the E-TOPSIS solutions with TOPSIS solution is presented.
35 citations
Cites background or methods from "User-side cloud service management:..."
...The stationary solution and the CSPs ranks of E-TOPSIS and TOPSIS methods by varying the parameter p in the interval [1;10] with step=0....
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...There are several cloud management platforms with cloud management software, specifically designed for users, which consider multiple CSPs. Examples of these services include Rightscale, Red Hat Cloud forms, Servicemesh Agility Platform and ElasticBox [10]....
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...The solutions obtained by varying the parameter p in the interval [1;10] When p has small values many variations in the order of alternatives can be observed....
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...Examples of these services include Rightscale, Red Hat Cloud forms, Servicemesh Agility Platform and ElasticBox [10]....
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...By varying the parameter p in the interval [1;10] with step=0....
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Posted Content•
01 Mar 2018TL;DR: A new vector comparison method combining the orientation similarity and dimension similarity to improve the precision of similarity calculation is presented, which can provide high accuracy of collaborative QoS prediction for multi-valued evaluations in the cloud computing paradigm.
Abstract: Aiming at the diversity of user features, the uncertainty and the variation characteristics of quality of service (QoS), by exploiting the continuous monitoring data of cloud services, this paper proposes a multi-valued collaborative approach to predict the unknown QoS values via time series analysis for potential users. In this approach, the multi-valued QoS evaluations consisting of single-value data and time series data from consumers are transformed into cloud models, and the differences between potential users and other consumers in every period are measured based on these cloud models. Against the deficiency of existing methods of similarity measurement between cloud models, this paper presents a new vector comparison method combining the orientation similarity and dimension similarity to improve the precision of similarity calculation. The fuzzy analytic hierarchy process method is used to help potential users determine the objective weight of every period, and the neighboring users are selected for the potential user according to their comprehensive similarities of QoS evaluations in multiple periods. By incorporating the multi-valued QoS evaluations with the objective weights among multiple periods, the predicted results can remain consistent with the periodic variations of QoS. Finally, the experiments based on a real-world dataset demonstrate that this approach can provide high accuracy of collaborative QoS prediction for multi-valued evaluations in the cloud computing paradigm.
33 citations
Cites background from "User-side cloud service management:..."
...On the whole, QoS prediction is still a new direction in cloud computing [27], there are some literatures on the QoS prediction approaches, which are valuable to estimate the unknown QoS values of cloud service for potential users based on the multivalued evaluations....
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TL;DR: Wang et al. as discussed by the authors proposed a multi-valued collaborative approach to predict the unknown QoS values via time series analysis for potential users by exploiting the continuous monitoring data of cloud services.
32 citations
References
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TL;DR: A service-oriented computing promotes the idea of assembling application components into a network of services that can be loosely coupled to create flexible, dynamic business processes and agile applications that span organizations and computing platforms.
Abstract: Service-oriented computing promotes the idea of assembling application components into a network of services that can be loosely coupled to create flexible, dynamic business processes and agile applications that span organizations and computing platforms An SOC research road map provides a context for exploring ongoing research activities
2,030 citations
01 Apr 2011
TL;DR: The strengths, weaknesses, opportunities and threats for the cloud computing industry are identified and some of the key issues facing governmental agencies who will have to become intimately involved in the regulation of cloud computing are outlined.
Abstract: The evolution of cloud computing over the past few years is potentially one of the major advances in the history of computing. However, if cloud computing is to achieve its potential, there needs to be a clear understanding of the various issues involved, both from the perspectives of the providers and the consumers of the technology. While a lot of research is currently taking place in the technology itself, there is an equally urgent need for understanding the business-related issues surrounding cloud computing. In this article, we identify the strengths, weaknesses, opportunities and threats for the cloud computing industry. We then identify the various issues that will affect the different stakeholders of cloud computing. We also issue a set of recommendations for the practitioners who will provide and manage this technology. For IS researchers, we outline the different areas of research that need attention so that we are in a position to advice the industry in the years to come. Finally, we outline some of the key issues facing governmental agencies who, due to the unique nature of the technology, will have to become intimately involved in the regulation of cloud computing.
2,016 citations
Journal Article•
TL;DR: This keynote argues that there is in fact even more profound change that the authors are facing – the programmability aspect that is intimately associated with all IoT systems.
1,171 citations
01 Nov 2010
TL;DR: Applying CloudCmp to four cloud providers that together account for most of the cloud customers today, it is found that their offered services vary widely in performance and costs, underscoring the need for thoughtful provider selection.
Abstract: While many public cloud providers offer pay-as-you-go computing, their varying approaches to infrastructure, virtualization, and software services lead to a problem of plenty. To help customers pick a cloud that fits their needs, we develop CloudCmp, a systematic comparator of the performance and cost of cloud providers. CloudCmp measures the elastic computing, persistent storage, and networking services offered by a cloud along metrics that directly reflect their impact on the performance of customer applications. CloudCmp strives to ensure fairness, representativeness, and compliance of these measurements while limiting measurement cost. Applying CloudCmp to four cloud providers that together account for most of the cloud customers today, we find that their offered services vary widely in performance and costs, underscoring the need for thoughtful provider selection. From case studies on three representative cloud applications, we show that CloudCmp can guide customers in selecting the best-performing provider for their applications.
1,008 citations
"User-side cloud service management:..." refers background in this paper
...…service monitoring (Fatema et al., 2014; de Chaves et al., 2011; Clayman et al., 2010; Baun and Kunze, 2010; Wang et al., 2012; Aceto et al., 2013; Li et al., 2010a,b, 2011; Montes et al., 2013; Kamel et al., 2013; Palhares et al., 2013; Akolkar et al., 2012; Rehman et al., 2012) which have been…...
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TL;DR: This work proposes a framework and a mechanism that measure the quality and prioritize Cloud services and will create healthy competition among Cloud providers to satisfy their Service Level Agreement (SLA) and improve their QoS.
833 citations
"User-side cloud service management:..." refers background in this paper
...…2013; Lecznar and Patig, 2011; Qian et al., 2013; Martens and Teuteberg, 2011; Filepp and Shwartz, 2010; Nie et al., 2011; Siegel and Perdue, 2012; Garg et al., 2011, 2013; Han et al., 2009a,b; Whaiduzzaman et al., 2014; Alabool and Mahmood, 2013; Kang and Sim, 2010, 2011a,b; Chen et al., 2012;…...
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...Garg et al. (2011, 2013) highlighted the need for a framework that can allow users to evaluate cloud offerings on the basis of their ability to meet the user's QoS requirements....
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...The service selection framework by Garg et al. (2011, 2013) also includes a cloud monitoring component to assess the QoS of available cloud services....
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...…2013; Lecznar and Patig, 2011; Qian et al., 2013; Martens and Teuteberg, 2011; Filepp and Shwartz, 2010; Nie et al., 2011; Siegel and Perdue, 2012; Garg et al., 2011, 2013; Han et al., 2009a,b; 1 Generalized Pareto Distribution (GPD) is a probability distribution which is used to model extreme…...
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