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.

scholarly journals Context-Aware Cloud Service Selection Model for Mobile Cloud Computing Environments

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xu Wu
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Relational Degree ◽  
Computing Environments ◽  
Traditional Approaches ◽  
Trustworthy Service

Mobile cloud computing (MCC) has attracted extensive attention in recent years. With the prevalence of MCC, how to select trustworthy and high quality mobile cloud services becomes one of the most urgent problems. Therefore, this paper focuses on the trustworthy service selection and recommendation in mobile cloud computing environments. We propose a novel service selection and recommendation model (SSRM), where user similarity is calculated based on user context information and interest. In addition, the relational degree among services is calculated based on PropFlow algorithm and we utilize it to improve the accuracy of ranking results. SSRM supports a personalized and trusted selection of cloud services through taking into account mobile user’s trust expectation. Simulation experiments are conducted on ns3 simulator to study the prediction performance of SSRM compared with other two traditional approaches. The experimental results show the effectiveness of SSRM.

scholarly journals Cloud Service Selection Using Multicriteria Decision Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Md Whaiduzzaman ◽  
Abdullah Gani ◽  
Nor Badrul Anuar ◽  
Muhammad Shiraz ◽  
Mohammad Nazmul Haque ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Decision Analysis ◽  
State Of The Art ◽  
Service Selection ◽  
Cloud Service ◽  
Multicriteria Decision Analysis ◽  
Cloud Services ◽  
Extensive Literature ◽  
Multicriteria Decision ◽  
Cloud Computing Service

Cloud computing (CC) has recently been receiving tremendous attention from the IT industry and academic researchers. CC leverages its unique services to cloud customers in a pay-as-you-go, anytime, anywhere manner. Cloud services provide dynamically scalable services through the Internet on demand. Therefore, service provisioning plays a key role in CC. The cloud customer must be able to select appropriate services according to his or her needs. Several approaches have been proposed to solve the service selection problem, including multicriteria decision analysis (MCDA). MCDA enables the user to choose from among a number of available choices. In this paper, we analyze the application of MCDA to service selection in CC. We identify and synthesize several MCDA techniques and provide a comprehensive analysis of this technology for general readers. In addition, we present a taxonomy derived from a survey of the current literature. Finally, we highlight several state-of-the-art practical aspects of MCDA implementation in cloud computing service selection. The contributions of this study are four-fold: (a) focusing on the state-of-the-art MCDA techniques, (b) highlighting the comparative analysis and suitability of several MCDA methods, (c) presenting a taxonomy through extensive literature review, and (d) analyzing and summarizing the cloud computing service selections in different scenarios.

A Service Schedule Model in Green Cloud Computing

2014 ◽  
Vol 687-691 ◽  
pp. 3040-3043
Author(s):  
Jing Li ◽  
Qi Yun Han
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Energy Saving ◽  
Mathematic Model ◽  
Optimal Point ◽  
Green Cloud Computing ◽  
Computing Paradigm ◽  
Efficient Resource ◽  
Numeric Calculation ◽  
Green Cloud

With the development of cloud computing paradigm, energy consumption becomes a big problem. Green cloud computing requires efficient resource management for the purpose of energy saving. Service schedule is an important part of the resource management to ensure the quality of service. A mathematic model is proposed which can determine service schedule quantity. In this model, taking energy saving and reputation index of service supplier into account, an optimization problem of two targets is simplified under hypothesis in reason. Through numeric calculation and analysis, this paper show there is an optimal point for the advance schedule of service.

Rationale for Use of Cloud Computing

2015 ◽  
pp. 2166-2197
Author(s):  
Amir Zeid ◽  
Ahmed Shawish ◽  
Maria Salama
Keyword(s):  
Cloud Computing ◽  
Cost Benefit Analysis ◽  
Service Selection ◽  
Cost Benefit ◽  
Quality Parameters ◽  
Cloud Services ◽  
Computing Paradigm ◽  
Model Combining ◽  
Quality Aspects ◽  
And Performance

Cloud Computing is the most promising computing paradigm that provides flexible resource allocation on demand with the promise of realizing elastic, Internet-accessible, computing on a pay-as-you-go basis. With the growth and expansion of the Cloud services and participation of various services providers, the description of quality parameters and measurement units start to diversify and sometime contradict. Such ambiguity does not only result in the rise of various Quality of Service (QoS) interoperability problems but also in the distraction of the services consumers who find themselves unable to match quality requirements with the providers' offerings. Yet, employing the available QoS models that cover certain quality aspects while neglecting others drive consumers to perform their service selection based only on cost-benefit analysis and performance evaluation, without being able to perform subjective selection based on a comprehensive set of well-defined quality aspects. This chapter presents a novel QoS ontology that combines and defines all of the existing quality aspects in a unified way to efficiently overcome all existing diversities. Using such an ontology, a comprehensive broad QoS model combining all quality-related parameters of both service providers and consumers for different Cloud platforms is presented. The chapter also provides a mathematical model that formulates the Cloud Computing service provider selection optimization problem based on QoS guarantees. The validation of the provided model is addressed in the chapter through extensive simulation studies conducted on benchmark data of Content Delivery Network providers. The studies report the efficient matching of the model with the market-oriented different platform characteristics.

scholarly journals Unified Ontology Implementation of Cloud Computing for Distributed Systems

2020 ◽  
pp. 82-97
Author(s):  
Zainab Salih Ageed ◽  
Rowaida Khalil Ibrahim ◽  
Mohammed A. M. Sadeeq
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Massive Data ◽  
Discovery Service ◽  
Different Types ◽  
Multi Agent ◽  
High Level

The ability to provide massive data storage, applications, platforms plus many other services leads to make the number of clouds services providers been increased. Providing different types of services and resources by various providers implies to get a high level of complexity. This complexity leads to face many challenges related to security, reliability, discovery, service selection, and interoperability. In this review, we focus on the use of many technologies and methods for utilizing the semantic web and ontology in cloud computing and distributed system as a solution for these challenges. Cloud computing does not have an own search engine to satisfy the needs of the providers of the cloud service. Using ontology enhances the cloud computing self-motivated via an intelligent framework of SaaS and consolidating the security by providing resources access control. The use RDF and OWL semantic technologies in the modeling of a multi-agent system are very effective in increases coordination the interoperability. One of the most efficient proposed frameworks is building cloud computing marketplace that collects the consumer's requirements of cloud services provider and managing these needs and resources to provide quick and reliable services.

Rationale for Use of Cloud Computing

2014 ◽  
pp. 24-56
Author(s):  
Amir Zeid ◽  
Ahmed Shawish ◽  
Maria Salama
Keyword(s):  
Cloud Computing ◽  
Cost Benefit Analysis ◽  
Service Selection ◽  
Cost Benefit ◽  
Quality Parameters ◽  
Cloud Services ◽  
Computing Paradigm ◽  
Model Combining ◽  
Quality Aspects ◽  
And Performance

Cloud Computing is the most promising computing paradigm that provides flexible resource allocation on demand with the promise of realizing elastic, Internet-accessible, computing on a pay-as-you-go basis. With the growth and expansion of the Cloud services and participation of various services providers, the description of quality parameters and measurement units start to diversify and sometime contradict. Such ambiguity does not only result in the rise of various Quality of Service (QoS) interoperability problems but also in the distraction of the services consumers who find themselves unable to match quality requirements with the providers’ offerings. Yet, employing the available QoS models that cover certain quality aspects while neglecting others drive consumers to perform their service selection based only on cost-benefit analysis and performance evaluation, without being able to perform subjective selection based on a comprehensive set of well-defined quality aspects. This chapter presents a novel QoS ontology that combines and defines all of the existing quality aspects in a unified way to efficiently overcome all existing diversities. Using such an ontology, a comprehensive broad QoS model combining all quality-related parameters of both service providers and consumers for different Cloud platforms is presented. The chapter also provides a mathematical model that formulates the Cloud Computing service provider selection optimization problem based on QoS guarantees. The validation of the provided model is addressed in the chapter through extensive simulation studies conducted on benchmark data of Content Delivery Network providers. The studies report the efficient matching of the model with the market-oriented different platform characteristics.

An Automatic Recovery Mechanism for Cloud Service Composition

2016 ◽  
Vol 13 (1) ◽  
pp. 23-39 ◽  
Author(s):  
Wenrui Li ◽  
Yan Cheng ◽  
Pengcheng Zhang ◽  
Hareton Leung
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Large Scale ◽  
Cloud Service ◽  
Cloud Services ◽  
Software Failures ◽  
Recovery Mechanism ◽  
Computing Paradigm ◽  
Composite Services ◽  
Cloud Service Composition

Cloud computing, with characteristics of large scale computation, data storage, visualization, high expansibility and elasticity, provides a powerful computing paradigm. Cloud services can be rapidly composed to form on-demand composite service for accomplishing the users' requirements. However, the uncertainty of cloud services has impacted on the correctness and reliability of the composite services. Especially, for unanticipated hardware and software failures, it is very difficult to assure the quality of the composite services. In the complex cloud computing environments, recovery of the composite services from these failures is a challenging issue. The paper first presents a unified fault taxonomy in the three layers of cloud computing and analyze the causes of the faults. The authors then propose a hierarchical recovery mechanism including five different recovery algorithms for various kinds of failures. Finally, through the simulation experiments they validate the proposed approach to be effective and practical.

GOVERNMENT REGULATIONS OF THE USING CLOUD SERVICES

2022 ◽  
Author(s):  
Olexander Melnikov ◽  
◽  
Konstantin Petrov ◽  
Igor Kobzev ◽  
Viktor Kosenko ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Government Agencies ◽  
Remote Work ◽  
Cloud Infrastructure ◽  
Wide Range ◽  
Technological Base

The article considers the development and implementation of cloud services in the work of government agencies. The classification of the choice of cloud service providers is offered, which can serve as a basis for decision making. The basics of cloud computing technology are analyzed. The COVID-19 pandemic has identified the benefits of cloud services in remote work Government agencies at all levels need to move to cloud infrastructure. Analyze the prospects of cloud computing in Ukraine as the basis of e-governance in development. This is necessary for the rapid provision of quality services, flexible, large-scale and economical technological base. The transfer of electronic information interaction in the cloud makes it possible to attract a wide range of users with relatively low material costs. Automation of processes and their transfer to the cloud environment make it possible to speed up the process of providing services, as well as provide citizens with minimal time to obtain certain information. The article also lists the risks that exist in the transition to cloud services and the shortcomings that may arise in the process of using them.

A Study on Cloud Service with Information Resources

2014 ◽  
Vol 513-517 ◽  
pp. 1425-1430
Author(s):  
Xiu Zhen Feng ◽  
Peng Hao
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Cloud Service ◽  
Information Resources ◽  
Information Resource ◽  
Computing Technology ◽  
Service Model ◽  
New Approach ◽  
Resources Management ◽  
Information Resources Management

Cloud computing technology created a brand new approach for further information resources management and utilization. Based on exploring characteristics and applications of cloud computing technology, the study in this paper is focused on cloud service with information resources. The aim of this study is to construct a cloud service model, namely Information Resource as a Service (IRaaS). Our model depicts the components of IRaaS and relationships among those components, which builds up a prime foundation for further studying on both information resource management and service.

Sign in / Sign up

Export Citation Format

Share Document