scholarly journals Cloud Service Selection using DEA based on SMI Attributes

2020 ◽  
Vol 9 (4) ◽  
pp. 849-855
Keyword(s):  
Service Selection ◽  
Multicriteria Decision Making ◽  
Cloud Service ◽  
Cloud Services ◽  
Cloud Provider ◽  
Data Envelopment ◽  
Ranking Methods ◽  
Network Connection ◽  
Fast Network ◽  
Cloud Users

Cloud computing allows on-demand access and fast network connection to a shared resource pool. Most companies are switching to Cloud due to the popularity and benefits of using Cloud Services. So finding a suitable and best cloud provider is a challenge for all users. Several ranking methods, such as AHP, TOPSIS, had been suggested to solve this problem by multicriteria decision making techniques. But, many of the works focused on a subset of the main QoS attributes for ranking. Cloud Services Measurement Initiatives Consortium (CSMIC) has released Service Measurement Index attributes for effectively comparing the Cloud services. The comparison of services provided by cloud based on SMI attributes which are qualitative as well as quantitative in nature is studied in this paper by one of the non-parametric methods called Data Envelopment Analysis (DEA) and ranked the cloud services based on the efficiency scores obtained by DEA. The cloud users can select the best suitable Cloud service using the proposed approach that best suit their QoS requirements.

scholarly journals Qualitative SMI based Cloud Service Selection using Intuitionistic Fuzzy TOPSIS

2020 ◽  
Vol 9 (1) ◽  
pp. 1289-1296
Keyword(s):  
Service Providers ◽  
Service Selection ◽  
Multicriteria Decision Making ◽  
Cloud Service ◽  
Fuzzy Topsis ◽  
Cloud Services ◽  
Cloud Provider ◽  
Intuitionistic Fuzzy ◽  
Network Connection ◽  
Intuitionistic Fuzzy Topsis

Cloud Computing allows access to a public resource pool on demand and easy network connection for the same. Due to the popularity and profits of using Cloud Services, many organizations are moving to Cloud .So selecting a suitable and best Cloud Provider is a challenge for all the users. Many ranking approaches had been proposed for solving this multicriteria decision making problem like AHP, TOPSIS etc. But many of the works focused on quantitative QoS attributes .But qualitative attributes are also important in the case of many application scenarios where the user may be more concerned about the qualitative attributes. CSMIC has released Service Measurement Index attributes for effectively comparing the Cloud services. The comparison of Cloud Service providers based on SMI attributes which are qualitative in nature by using a ranking approach that handles fuzziness in the dataset is the objective of this paper. The proposed approach uses the MCDM algorithm called Technique for Order Preference by Similarity to ideal Solution and uncertainty is handled by Intuitionistic fuzzy values. The qualitative SMI attributes are used as criteria for ranking the Cloud Services.

scholarly journals Networking for Cloud Robotics: The DewROS Platform and Its Application

2021 ◽  
Vol 10 (2) ◽  
pp. 34
Author(s):  
Alessio Botta ◽  
Jonathan Cacace ◽  
Riccardo De Vivo ◽  
Bruno Siciliano ◽  
Giorgio Ventre
Keyword(s):  
Response Time ◽  
Large Data ◽  
Cloud Services ◽  
Cloud Provider ◽  
Human Beings ◽  
Minimal Impact ◽  
Network Connection ◽  
Cloud Robotics ◽  
Networking Technologies ◽  
The Impact

With the advances in networking technologies, robots can use the almost unlimited resources of large data centers, overcoming the severe limitations imposed by onboard resources: this is the vision of Cloud Robotics. In this context, we present DewROS, a framework based on the Robot Operating System (ROS) which embodies the three-layer, Dew-Robotics architecture, where computation and storage can be distributed among the robot, the network devices close to it, and the Cloud. After presenting the design and implementation of DewROS, we show its application in a real use-case called SHERPA, which foresees a mixed ground and aerial robotic platform for search and rescue in an alpine environment. We used DewROS to analyze the video acquired by the drones in the Cloud and quickly spot signs of human beings in danger. We perform a wide experimental evaluation using different network technologies and Cloud services from Google and Amazon. We evaluated the impact of several variables on the performance of the system. Our results show that, for example, the video length has a minimal impact on the response time with respect to the video size. In addition, we show that the response time depends on the Round Trip Time (RTT) of the network connection when the video is already loaded into the Cloud provider side. Finally, we present a model of the annotation time that considers the RTT of the connection used to reach the Cloud, discussing results and insights into how to improve current Cloud Robotics applications.

Slicing, Tokenization, and Encryption Based Combinational Approach to Protect Data-at-Rest in Cloud Using TF-Sec Model

2020 ◽  
Vol 17 (12) ◽  
pp. 5296-5306
Author(s):  
N. Keerthana ◽  
Viji Vinod ◽  
Sudhakar Sengan
Keyword(s):  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Erasure Coding ◽  
Cloud Data ◽  
Data Usage ◽  
Dispersion Technique ◽  
Definition Of ◽  
The Given ◽  
Cloud Users

Data in the Cloud, which applies to data as a cloud service provider (CSP), transmits stores, or manages it. The company will enforce the same definition of data usage while the data is resident within the enterprise and thus extend the required cryptographic security criteria to data collected, exchanged, or handled by CSP. The CSP Service Level Agreements cannot override the cryptographic access measures. When the data is transferred securely to CSP, it can be securely collected, distributed, and interpreted. Data at the rest position applies to data as it is processed internally in organized and in the unstructured ways like databases and file cabinets. The Data at the Rest example includes the use of cryptography for preserving the integrity of valuable data when processed. For cloud services, computing takes multiple forms from recording units, repositories, and many unstructured items. This paper presents a secure model for Data at rest. The TF-Sec model suggested is planned for use with Slicing, Tokenization, and Encryption. The model encrypts the given cloud data using AES 256 encryption, and then the encrypted block is sliced into the chunks of data fragments using HD-Slicer. Then it applies tokenization algorithm TKNZ to each chunk of data, applies erasure coding technique to tokens, applies the data dispersion technique to scramble encrypted data fragments, and allocates to storage nodes of the multiple CSP. In taking the above steps, this study aims to resolve the cloud security problems found and to guarantee the confidentiality of their data to cloud users due to encryption of data fragments would be of little benefit to a CSP.

A Cloud Trusting Mechanism Based on Resource Ranking

2020 ◽  
pp. 130-155
Author(s):  
Ajai K. Daniel
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Storage And Retrieval ◽  
Computing Paradigm ◽  
Efficient Resource ◽  
Software And Hardware ◽  
Cloud User

The cloud-based computing paradigm helps organizations grow exponentially through means of employing an efficient resource management under the budgetary constraints. As an emerging field, cloud computing has a concept of amalgamation of database techniques, programming, network, and internet. The revolutionary advantages over conventional data computing, storage, and retrieval infrastructures result in an increase in the number of organizational services. Cloud services are feasible in all aspects such as cost, operation, infrastructure (software and hardware) and processing. The efficient resource management with cloud computing has great importance of higher scalability, significant energy saving, and cost reduction. Trustworthiness of the provider significantly influences the possible cloud user in his selection of cloud services. This chapter proposes a cloud service selection model (CSSM) for analyzing any cloud service in detail with multidimensional perspectives.

A Robust and Efficient MCDM-Based Framework for Cloud Service Selection Using Modified TOPSIS

2021 ◽  
Vol 11 (1) ◽  
pp. 21-51
Author(s):  
Rohit Kumar Tiwari ◽  
Rakesh Kumar
Keyword(s):  
Service Provider ◽  
Service Providers ◽  
Service Selection ◽  
Cloud Service ◽  
Reversal Problem ◽  
Rank Reversal ◽  
Reversal Phenomenon ◽  
Optimal Service ◽  
Selection Framework ◽  
Cloud Users

Cloud computing has become a business model and organizations like Google, Amazon, etc. are investing huge capital on it. The availability of many organizations in the cloud has posed a challenge for cloud users to choose a best cloud service. To assist the cloud users, we have proposed a MCDM-based cloud service selection framework to choose a best service provider based on QoS requirement. The cloud service selection methods based on TOPSIS suffers from rank reversal problem as it ranks optimal service provider to non-optimal on addition or removal of a service provider and deludes the cloud user. Therefore, a robust and efficient TOPSIS (RE-TOPSIS)-based novel framework has been proposed to rank the cloud service providers using QoS provided by them and cloud user's priority for each QoS. The proposed framework is robust to rank reversal problem and its effectiveness has been demonstrated through a case study performed on a real dataset. Sensitivity analysis has also been performed to show the robustness against the rank reversal phenomenon.

A Credible Cloud Service Model based on Behavior Graphs and Tripartite Decision-Making Mechanism

2016 ◽  
Vol 8 (3) ◽  
pp. 38-56 ◽  
Author(s):  
Junfeng Tian ◽  
He Zhang
Keyword(s):  
Decision Making ◽  
Cloud Service ◽  
Cloud Services ◽  
Service Model ◽  
The Past ◽  
Model Based ◽  
Cloud Users ◽  
Cloud User

The credibility of cloud service is the key to the success of the application of cloud services. The dual servers of master server and backup server are applied to cloud services, which can improve the availability of cloud services. In the past, the failures between master server and backup server could be detected by heartbeat algorithm. Because of lacking cloud user's evaluation, the authors put forward a credible cloud service model based on behavior Graphs and tripartite decision-making mechanism. By the quantitative of cloud users' behaviors evidences, the construction of behavior Graphs and the judgment of behavior, they select the most credible cloud user. They combine the master server, the backup server and the selected credible cloud user to determine the credibility of cloud service by the tripartite decision-making mechanism. Finally, according to the result of credible judgment, the authors could decide whether it will be switched from the master server to the backup server.

Dynamic QoS-Aware Cloud Service Selection Using Best-Worst Method and Timeslot Weighted Satisfaction Scores

2020 ◽  
Author(s):  
Falak Nawaz ◽  
Naeem Khalid Janjua
Keyword(s):  
Decision Making ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Satisfaction Score ◽  
Analytic Hierarchy ◽  
Hierarchy Process ◽  
Best Worst Method ◽  
Selection Of

Abstract The number of cloud services has dramatically increased over the past few years. Consequently, finding a service with the most suitable quality of service (QoS) criteria matching the user’s requirements is becoming a challenging task. Although various decision-making methods have been proposed to help users to find their required cloud services, some uncertainties such as dynamic QoS variations hamper the users from employing such methods. Additionally, the current approaches use either static or average QoS values for cloud service selection and do not consider dynamic QoS variations. In this paper, we overcome this drawback by developing a broker-based approach for cloud service selection. In this approach, we use recently monitored QoS values to find a timeslot weighted satisfaction score that represents how well a service satisfies the user’s QoS requirements. The timeslot weighted satisfaction score is then used in Best-Worst Method, which is a multi-criteria decision-making method, to rank the available cloud services. The proposed approach is validated using Amazon’s Elastic Compute Cloud (EC2) cloud services performance data. The results show that the proposed approach leads to the selection of more suitable cloud services and is also efficient in terms of performance compared to the existing analytic hierarchy process-based cloud service selection approaches.

Research on Behavior Trust Evaluation Method of Cloud Services Based on Membership Theory

2013 ◽  
Vol 427-429 ◽  
pp. 2377-2382
Author(s):  
Ying Liu ◽  
Yan Wang ◽  
Xian You Sun
Keyword(s):  
Evaluation System ◽  
Evaluation Method ◽  
Service Providers ◽  
Evaluation Model ◽  
Degree Theory ◽  
Cloud Service ◽  
Cloud Services ◽  
Trust Evaluation ◽  
Wide Range ◽  
Cloud Users

Among the wide range of cloud service providers with different performance characteristics, in order to let the cloud users find cloud services which satisfy its performance preferences and specific trust levels,it needs to establish a reasonable and scientific cloud service trust evaluation system. This paper introduces a membership degree theory into trust evaluation model. First, it designs the trust evaluation system framework of cloud services, and establishes a trust evaluation model of cloud services. Next, it calculates the trust level of cloud services with the comprehensive trust cloud center of gravity evaluation method (CCGE). Finally, the experiment results show that this model can build precise trust relationship between cloud users and cloud services based on users performance demands.

scholarly journals An Improved CoCoSo Method with a Maximum Variance Optimization Model for Cloud Service Provider Selection

2020 ◽  
Vol 31 (4) ◽  
pp. 411-424
Author(s):  
Han Lai ◽  
Huchang Liao ◽  
Zhi Wen ◽  
Edmundas Kazimieras Zavadskas ◽  
Abdullah Al-Barakati
Keyword(s):  
Service Provider ◽  
Optimization Model ◽  
Service Providers ◽  
Service Selection ◽  
Cloud Service ◽  
Careful Analysis ◽  
Cloud Services ◽  
Cloud Service Provider ◽  
Maximum Variance ◽  
Cloud Service Providers

With the rapid growth of available online cloud services and providers for customers, the selection of cloud service providers plays a crucial role in on-demand service selection on a subscription basis. Selecting a suitable cloud service provider requires a careful analysis and a reasonable ranking method. In this study, an improved combined compromise solution (CoCoSo) method is proposed to identify the ranking of cloud service providers. Based on the original CoCoSo method, we analyze the defects of the final aggregation operator in the original CoCoSo method which ignores the equal importance of the three subordinate compromise scores, and employ the operator of “Linear Sum Normalization” to normalize the three subordinate compromise scores so as to make the results reasonable. In addition, we introduce a maximum variance optimization model which can increase the discrimination degree of evaluation results and avoid inconsistent ordering. A numerical example of the trust evaluation of cloud service providers is given to demonstrate the applicability of the proposed method. Furthermore, we perform sensitivity analysis and comparative analysis to justify the accuracy of the decision outcomes derived by the proposed method. Besides, the results of discrimination test also indicate that the proposed method is more effective than the original CoCoSo method in identifying the subtle differences among alternatives.

scholarly journals Design and Implementation of a Framework for Multi-Cloud Service Broker

2021 ◽  
Author(s):  
Md Ahsan Ullah
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Location Awareness ◽  
Performance Measurements ◽  
Positioning Systems ◽  
Network Connection ◽  
Service Broker

Cloud service broker (CSB) as an emerging technology intermediates heterogeneous multiple cloud services for both the providers and consumers. Recently, Cloud computing & mobile cloud computing applications (MCA) have gained an enormous popularity, which has led to an increasing need for the development of platform independent Middleware/CSB to support all types of cloud service consumer applications including x86*x64 based standard OS & ARM based mobile applications, web browsers, etc. Developing Platform Independent Hybrid CSB, however, is not an easy task. Developers have to deal with difficulties inherent from the different cloud controllers, cloud service providers environments, clients’ application types, network connection types (wired, wireless), GPS (Global Positioning Systems) information of cloud resources and clients’ etc. In this thesis, the proposed design of a middleware/CSB that abstracts the real-time resources of various clouds (private, public, home, Local) and stores the resources in its own Database. It will also store clients requests then analyzes the request to find the nearest available servers which is running the appropriate applications. Then the CSB will forward the destination servers information to the clients. Thesis goal is to achieve context awareness, location awareness, platform independence, portability, efficiency, and usability. Portability is achieved by following the J2ME platform specifications. The middleware has been implemented and tested on a real time Openstack cloud using by our newly designed Android Clients and platform independent Mozilla Firefox browser. The performance measurements of the middleware show that it achieves its efficiency requirements. Furthermore, the middleware’s database can be used for resource algorithm, pattern analysis, and for future requirements.

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