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Journal ArticleDOI

User-side cloud service management: State-of-the-art and future directions

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TLDR
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.
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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.

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Citations
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Journal ArticleDOI

Cloud service evaluation method-based Multi-Criteria Decision-Making

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.
Journal ArticleDOI

Time-aware trustworthiness ranking prediction for cloud services using interval neutrosophic set and ELECTRE

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.
Journal ArticleDOI

An Extended TOPSIS Approach for Ranking Cloud Service Providers

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.
Posted Content

Multi-Valued Collaborative Qos Prediction for Cloud Service Via Time Series Analysis

TL;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.
Journal ArticleDOI

Multi-valued collaborative QoS prediction for cloud service via time series analysis

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.
References
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Proceedings ArticleDOI

A Business Resolution Engine for Cloud Marketplaces

TL;DR: This paper presents an innovative mechanism for the resolution of the customers' requirements which enhances the process of selecting cloud services from the business point of view.
Book ChapterDOI

Evaluation Index System of Cloud Service and the Purchase Decision- Making Process Based on AHP

TL;DR: Wang et al. as mentioned in this paper proposed a complete cloud service evaluation index system, and solved the sort-order problem of evaluation indexes priorities with analytic hierarchy process (AHP); at last, the quantitative models of qualitative indexes are also developed, which makes the purchase decision of cloud service become more scientific and convincing.
Book ChapterDOI

Clouds’ Infrastructure Taxonomy, Properties, and Management Services

TL;DR: The paper proposes a Cloud taxonomy focusing on infrastructure components interaction and management, provides a real life scenario of a critical application architecture using the proposed taxonomy, and derives the management services using the provided scenario.
Journal ArticleDOI

Levitation characteristics of a squeeze-film air journal bearing at its normal modes

TL;DR: In this paper, a tubular squeeze-film journal bearing was designed such that it flexed its shell at its normal modes producing a triangular modal shape, and the shell motion was created by a single-layer piezoelectric actuator powered at 75 V AC with a 75 V DC offset.
Book ChapterDOI

Survey of Elasticity Management Solutions in Cloud Computing

TL;DR: This chapter provides an overview of the concept of cloud elasticity and proposes a classification of the mechanisms and techniques employed to manage elasticity, using this classification as a common ground to study and compare elasticity management solutions.
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