scholarly journals Evaluating the QoS Cognizance in Composition of Cloud Services: A Systematic Literature Review

2018 ◽  
Vol 7 (4.6) ◽  
pp. 141
Author(s):  
A V L N Sujith ◽  
Dr. A Rama Mohan Reddy ◽  
Dr. K Madhavi
Keyword(s):  
Service Composition ◽  
Service Discovery ◽  
Service Providers ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Future Research ◽  
Promising Area ◽  
Cloud Service Composition ◽  
Rapid Deployment

Enterprise level computing constantly investigates novel approaches that maximize their profits and minimize their expenses. With the rapid growth of cloud computing XaaS – ‘anything as a service’, service providers are enabled with the rapid deployment of virtual services to service requestors. Because of the enormous growth in the variety of the services and based on the demand of the virtualized resources, cloud service providers are facing tough competition to facilitate the composite service requests made by the service requestors. QoS (Quality of Service)  is considered to be a preliminary factor while composing a new cloud service out of heterogeneous and distributed atomic services. Therefore service composition is promising area that focuses on the design and development of the automated approaches to deal with diverse phases of service composition techniques that include service discovery, negotiation, service selection and optimization of the atomic services. This paper provides anatomy of  existing studies addressing the problem of cloud service composition that enable to identify intended objectives of the technique along with diverse QoS aware problem solving approaches. Furthermore, the key areas of the improvement in cloud service composition are identified for future research. 

Client-Centric Cloud Service Composition

2017 ◽  
pp. 144-166
Author(s):  
Vivek Gaur ◽  
Praveen Dhyani ◽  
Om Prakash Rishi
Keyword(s):  
Service Composition ◽  
Large Scale ◽  
Business Processes ◽  
Service Providers ◽  
Service Selection ◽  
Cloud Service ◽  
Quality Parameters ◽  
End User ◽  
Cloud Service Composition ◽  
Tabu Search Methods

Recent computing world has seen rapid growth of the number of middle and large scale enterprises that deploy business processes sharing variety of services available over cloud environment. Due to the advantage of reduced cost and increased availability, the cloud technology has been gaining unbound popularity. However, because of existence of multiple cloud service providers on one hand and varying user requirements on the other hand, the task of appropriate service composition becomes challenging. The conception of this chapter is to consider the fact that different quality parameters related to various services might bear varied importance for different user. This chapter introduces a framework for QoS-based Cloud service selection to satisfy the end user needs. A hybrid algorithm based on genetic algorithm (GA) and Tabu Search methods has been developed, and its efficacy is analysed. Finally, this chapter includes the experimental analysis to present the performance of the algorithm.

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 Dynamic mutual manufacturing and transportation routing service selection for cloud manufacturing with multi-period service-demand matching

2021 ◽  
Vol 7 ◽  
pp. e461
Author(s):  
Seyed Ali Sadeghi Aghili ◽  
Omid Fatahi Valilai ◽  
Alireza Haji ◽  
Mohammad Khalilzadeh
Keyword(s):  
Service Composition ◽  
Large Scale ◽  
Business Models ◽  
Service Providers ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Manufacturing ◽  
Architecture Model ◽  
Logistics Service ◽  
Composition Problem

Recently, manufacturing firms and logistics service providers have been encouraged to deploy the most recent features of Information Technology (IT) to prevail in the competitive circumstances of manufacturing industries. Industry 4.0 and Cloud manufacturing (CMfg), accompanied by a service-oriented architecture model, have been regarded as renowned approaches to enable and facilitate the transition of conventional manufacturing business models into more efficient and productive ones. Furthermore, there is an aptness among the manufacturing and logistics businesses as service providers to synergize and cut down the investment and operational costs via sharing logistics fleet and production facilities in the form of outsourcing and consequently increase their profitability. Therefore, due to the Everything as a Service (XaaS) paradigm, efficient service composition is known to be a remarkable issue in the cloud manufacturing paradigm. This issue is challenging due to the service composition problem’s large size and complicated computational characteristics. This paper has focused on the considerable number of continually received service requests, which must be prioritized and handled in the minimum possible time while fulfilling the Quality of Service (QoS) parameters. Considering the NP-hard nature and dynamicity of the allocation problem in the Cloud composition problem, heuristic and metaheuristic solving approaches are strongly preferred to obtain optimal or nearly optimal solutions. This study has presented an innovative, time-efficient approach for mutual manufacturing and logistical service composition with the QoS considerations. The method presented in this paper is highly competent in solving large-scale service composition problems time-efficiently while satisfying the optimality gap. A sample dataset has been synthesized to evaluate the outcomes of the developed model compared to earlier research studies. The results show the proposed algorithm can be applied to fulfill the dynamic behavior of manufacturing and logistics service composition due to its efficiency in solving time. The paper has embedded the relation of task and logistic services for cloud service composition in solving algorithm and enhanced the efficiency of resulted matched services. Moreover, considering the possibility of arrival of new services and demands into cloud, the proposed algorithm adapts the service composition algorithm.

Pattern-Based Cloud Migration

2021 ◽  
pp. 1346-1372
Author(s):  
Zhitao Wan
Keyword(s):  
Service Composition ◽  
Service Selection ◽  
Cloud Service ◽  
Pattern Generation ◽  
Migration Pattern ◽  
Cloud Services ◽  
Legacy Systems ◽  
Cloud Environment ◽  
Business Systems ◽  
Cloud Migration

To migrate on-premises business systems to the cloud environment faces challenges: the complexity, diversity of the legacy systems, cloud, and cloud migration services. Consequently, the cloud migration faces two major problems. The first one is how to select cloud services for the legacy systems, and the second one is how to move the corresponding workload from legacy systems to cloud. This chapter presents a total cloud migration solution including cloud service selection and optimization, cloud migration pattern generation, and cloud migration pattern enforcement. It takes the pattern as the core, and unifies the cloud migration request, the cloud migration service pattern, and the cloud migration service composition. A cloud migration example of blockchain system shows that the proposed approach improves the cloud service selection, cloud migration service composition generation efficiency, migration process parallelization, and enables long transaction support by means of pattern reuse.

Pattern-Based Cloud Migration

2019 ◽  
pp. 216-249
Author(s):  
Zhitao Wan
Keyword(s):  
Service Composition ◽  
Service Selection ◽  
Cloud Service ◽  
Pattern Generation ◽  
Migration Pattern ◽  
Cloud Services ◽  
Legacy Systems ◽  
Cloud Environment ◽  
Business Systems ◽  
Cloud Migration

To migrate on-premises business systems to the cloud environment faces challenges: the complexity, diversity of the legacy systems, cloud, and cloud migration services. Consequently, the cloud migration faces two major problems. The first one is how to select cloud services for the legacy systems, and the second one is how to move the corresponding workload from legacy systems to cloud. This chapter presents a total cloud migration solution including cloud service selection and optimization, cloud migration pattern generation, and cloud migration pattern enforcement. It takes the pattern as the core, and unifies the cloud migration request, the cloud migration service pattern, and the cloud migration service composition. A cloud migration example of blockchain system shows that the proposed approach improves the cloud service selection, cloud migration service composition generation efficiency, migration process parallelization, and enables long transaction support by means of pattern reuse.

Dynamic service composition in enterprise cloud bus architecture

2019 ◽  
Vol 15 (5) ◽  
pp. 550-576
Author(s):  
Gitosree Khan ◽  
Sabnam Sengupta ◽  
Anirban Sarkar
Keyword(s):  
Service Composition ◽  
Service Discovery ◽  
Scheduling Algorithm ◽  
Hybrid Approach ◽  
Cloud Service ◽  
Cloud Services ◽  
Content Type ◽  
Dynamic Service Composition ◽  
Functional Aspects ◽  
Heterogeneous Service

Purpose Service composition phenomenon based on non-scenario aspects are become the latest issues in enterprise software applications of the multi-cloud environment due to the phenomenal increase in a number of Web services. The traditional service composition patterns are hard to support the dynamic, flexible and autonomous service composition in the inter-cloud platform. To address this problem, this paper aims to describe a dynamic service composition framework (SCF) that is enriched with various structural and functional aspects of composition patterns in a cloud computing environment. The proposed methodology helps to integrate various heterogeneous cloud services dynamically to acquire an optimal and novel enterprise solution for delivering the service to the end-users automatically. Design/methodology/approach SCF and different composition patterns have been used to compose the services present in the inter-cloud architecture of the multi-agent-based system. Further, the proposed dynamic service composition algorithm is illustrated using a hybrid approach, where service are chosen according to various needs of quality of service parameters. Besides, a priority-based service scheduling algorithm is proposed that facilitates the automation of delivering cloud service optimally. Findings The proposed framework is capable of composing the heterogeneous service and facilitate the structural and functional aspects of service composition process in enterprise cloud-based applications in terms of flexibility, scalability, integrity and dynamicity of the cloud bus. The advantage of the proposed algorithm is that it helps to minimize the execution cost, processing time and get better success rate in delivering the service as per customer’s need. Originality/value The novelty of the proposed architecture coordinates cloud participants, automate service discovery pattern, reconfigure scheduled services and focus on aggregating a composite services in inter-cloud environments. Besides, the proposed framework supported several non-functional characteristics such as robustness, flexibility, dynamicity, scalability and reliability of the system.

Combined Preference Ranking Algorithm for Comparing and Initial Ranking of Cloud Services

2020 ◽  
Vol 13 (2) ◽  
pp. 260-275
Author(s):  
Abdul Qadir Md ◽  
Varadarajan Vijayakumar
Keyword(s):  
Trust Management ◽  
Service Providers ◽  
Service Level Agreement ◽  
Service Selection ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Preference Ranking ◽  
Ranking Algorithm ◽  
Management Architecture

Background: With the immense significance of cloud computing over the decade, different IT companies offer varieties of cloud services. Objective: The selection of cloud services from the expanding range of Cloud Service Providers (CSPs) makes it difficult for the Cloud Consumers (CCs) to choose a CSP based on their preferences. Methods: In this context, this paper proposes an efficient trust management architecture for cloud service selection and put forward Combined Preference Ranking Algorithm (CPRA) for initial ranking of CSPs and their services before doing any transaction in the past based on CCs requirements. Results: The proposed trust management architecture prompts the CSPs to improve the Quality of Service (QoS) by adhering to Service Level Agreement (SLA). Conclusion: The experimental results show that compared with other ranking approaches CPRA generates the accurate ranking list of CSPs with minimal execution time.

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