A computational framework for ranking prediction of cloud services under fuzzy environment

2021 ◽  
pp. 1-21
Author(s):  
Rakesh Ranjan Kumar ◽  
Mohammad Shameem ◽  
Chiranjeev Kumar
Keyword(s):  
Cloud Services ◽  
Computational Framework ◽  
Fuzzy Environment

Optimal Cloud-Path Selection in Mobile Cloud Offloading Systems Based on QoS Criteria

2013 ◽  
Vol 5 (4) ◽  
pp. 30-47 ◽  
Author(s):  
Huaming Wu ◽  
Qiushi Wang ◽  
Katinka Wolter
Keyword(s):  
Historical Data ◽  
Cloud Service ◽  
Fuzzy Topsis ◽  
Path Selection ◽  
Cloud Services ◽  
Analytic Hierarchy ◽  
Fuzzy Environment ◽  
Order Preference ◽  
Hierarchy Process

Recently, there emerge a variety of clouds in sky and thus, several similar cloud services (from different cloud venders) can be provided to a mobile end device. The goal of cloud-path selection is to find an optimal cloud-path pair between the mobile device and a cloud among a certain class of clouds that provide the same service, in order to carry out the offloaded computation tasks. It is easy to choose the optimal cloud-path to save execution time incurred by offloading program to cloud when considering only one factor. However, there are many Quality of Service (QoS)-based criteria such as performance, bandwidth, financial, security and availability that need to be considered when making final decisions. In this paper, a multiple criteria decision analysis approach based on the analytic hierarchy process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS) in a fuzzy environment is proposed to decide which cloud is the most suitable one for offloading. The AHP is used to determine the weights of the criteria for cloud-path selection, while fuzzy TOPSIS is to obtain the final ranking of alternative clouds. The numerical analysis is performed to evaluate the model. Furthermore, a method based on historical data of the mobile device’s experiences is used to evaluate the importance weights of the alternative cloud service, when it is challenge to measure and acquire the parameters of criteria timely in practical systems.

scholarly journals A Heterogeneous QoS-Based Cloud Service Selection Approach Using Entropy Weight and GRA-ELECTRE III

2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Mingming Liu ◽  
Yifan Shao ◽  
Chunxia Yu ◽  
Jiacheng Yu
Keyword(s):  
Service Selection ◽  
Cloud Service ◽  
Heterogeneous Data ◽  
Cloud Services ◽  
Entropy Measure ◽  
Entropy Weight ◽  
Electre Iii ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Selection Approach

With the development of cloud computing, more and more resources are provided in the form of cloud services. Then how to select suitable cloud service for users without professional knowledge has become an important issue. Existing cloud service selection models are usually considered as QoS-aware evaluation focused models. In practice, the QoS attributes have problems like subjectivity, vagueness, and uncertainty, and a range of formats are involved to describe QoS attributes. Therefore, it is necessary to consider the heterogeneous formats of QoS attributes in cloud service selection process. The aim of this paper is to develop a novel cloud service selection approach using entropy weight and GRA-ELECTRE III that can handle heterogeneous QoS attributes simultaneously. In the proposed approach, heterogeneous QoS attributes are handled simultaneously by being transformed into intuitionistic fuzzy numbers; the relative weights of QoS attributes are calculated objectively by the extended entropy measure method under intuitionistic fuzzy environment; and cloud services are evaluated by GRA-ELECTRE III integrated method under intuitionistic fuzzy environment. Experimental results show that the proposed approach has good stability and discrimination in dealing with heterogeneous data and can effectively avoid compensation between attributes.

A generalized fuzzy cost efficiency model

2020 ◽  
Vol 54 (6) ◽  
pp. 1775-1791
Author(s):  
Nazila Aghayi ◽  
Samira Salehpour
Keyword(s):  
Cost Efficiency ◽  
Minimum Cost ◽  
Extensive Literature ◽  
Data Envelopment ◽  
Fuzzy Environment ◽  
Decision Making Unit ◽  
Production Possibility Set ◽  
Fuzzy Cost ◽  
The Cost ◽  
Generalized Cost

The concept of cost efficiency has become tremendously popular in data envelopment analysis (DEA) as it serves to assess a decision-making unit (DMU) in terms of producing minimum-cost outputs. A large variety of precise and imprecise models have been put forward to measure cost efficiency for the DMUs which have a role in constructing the production possibility set; yet, there’s not an extensive literature on the cost efficiency (CE) measurement for sample DMUs (SDMUs). In an effort to remedy the shortcomings of current models, herein is introduced a generalized cost efficiency model that is capable of operating in a fuzzy environment-involving different types of fuzzy numbers-while preserving the Farrell’s decomposition of cost efficiency. Moreover, to the best of our knowledge, the present paper is the first to measure cost efficiency by using vectors. Ultimately, a useful example is provided to confirm the applicability of the proposed methods.

A Survey on Utilizing Cloud Services in the E-learning Process

2015 ◽  
Vol 6 (9) ◽  
pp. 1606-1612
Author(s):  
Zaydoon Mohammad Hatamleh ◽  
Eslam Najim Badran ◽  
Bilal Mohammad Hatamleh
Keyword(s):  
Learning Process ◽  
Cloud Services ◽  
E Learning

Implementaon of digital economy elements in electric power industry

2018 ◽  
Vol 11 (2) ◽  
pp. 94-102 ◽  
Author(s):  
A. G. Filimonov ◽  
N. D. Chichirova ◽  
A. A. Chichirov ◽  
A. A. Filimonovа
Keyword(s):  
Electric Power ◽  
Energy Production ◽  
Predictive Analytics ◽  
Digital Economy ◽  
Digital Transformation ◽  
Cloud Services ◽  
Small Scale ◽  
Economic Activities ◽  
Industrial Enterprises ◽  
Automation Systems

Energy generation, along with other sectors of Russia’s economy, is on the cusp of the era of digital transformation. Modern IT solutions ensure the transition of industrial enterprises from automation and computerization, which used to be the targets of the second half of the last century, to digital enterprise concept 4.0. The international record of technological and structural solutions in digitization may be used in Russia’s energy sector to the full extent. Specifics of implementation of such systems in different countries are only determined by the level of economic development of each particular state and the attitude of public authorities as related to the necessity of creating conditions for implementation of the same. It is shown that a strong legislative framework is created in Russia for transition to the digital economy, with research and applied developments available that are up to the international level. The following digital economy elements may be used today at enterprises for production of electrical and thermal energy: — dealing with large amounts of data (including operations exercised via cloud services and distributed data bases); — development of small scale distributed generation and its dispatching; — implementation of smart elements in both electric power and heat supply networks; — development of production process automation systems, remote monitoring and predictive analytics; 3D-modeling of parts and elements; real time mathematic simulation with feedback in the form of control actions; — creating centres for analytical processing of statistic data and accounting in financial and economic activities with business analytics functions, with expansion of communication networks and computing capacities. Examples are presented for implementation of smart systems in energy production and distribution. It is stated in the paper that state-of art information technologies are currently being implemented in Russia, new unique digital transformation projects are being launched in major energy companies. Yet, what is required is large-scale and thorough digitization and controllable energy production system as a multi-factor business process will provide the optimum combination of efficient economic activities, reliability and safety of power supply.

IMMUNIZATION STRATEGY IN A FUZZY ENVIRONMENT

2007 ◽  
Vol 12 (02) ◽  
Author(s):  
A. Terceño Gómez ◽  
A. Fernández Bariviera ◽  
J. M. Brotons Martí­nez
Keyword(s):  
Immunization Strategy ◽  
Fuzzy Environment
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