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 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.

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. 

scholarly journals Service Association Factor (SAF) for Cloud Service Selection and Recommendation

2020 ◽  
Vol 49 (1) ◽  
pp. 113-126
Author(s):  
Imran Mujaddid Rabbani ◽  
Muhammad Aslam ◽  
Ana Maria Martinez Enriquez ◽  
Zeeshan Qudeer
Keyword(s):  
Recommendation System ◽  
Service Providers ◽  
Service Selection ◽  
Cloud Service ◽  
Base System ◽  
End User ◽  
Cloud Models ◽  
Science Domain ◽  
Quality Of Service Parameters

Cloud computing is one of the leading technology in IT and computer science domain. Business IT infrastructures are equipping themselves with modern regime of clouds. In the presence of several opportunities, selection criteria decision becomes vital when there is no supporting information available. Global clouds also need evaluation and assessment from its users that what they think about and how new ones could make their selection as per their needs. Recommended systems were built to propose best services using customer's feedback, applying quality of service parameters, assigning scores, trust worthiness and clustering in different forms and models. These techniques did not record and use interrelationships between the services that is true impact of service utilization. In the proposed approach, service association factor calculates value of interrelations among services used by the end user. An intelligent leaning based recommendation system is developed for assisting users to select services on their respective preferences. This technique is evaluated on leading service providers and results show that learning base system performs well on all types of cloud models.

Automatic Manufacturing Cloud Service Composition Based on AI Plan

2014 ◽  
Vol 513-517 ◽  
pp. 990-993 ◽  
Author(s):  
Pei Si Zhong ◽  
Shao Qi Zhu ◽  
De Jie Huang ◽  
Hai Liang Xin
Keyword(s):  
Service Composition ◽  
Large Scale ◽  
Cloud Service ◽  
Cloud Manufacturing ◽  
Search Method ◽  
Added Value ◽  
Service Environment ◽  
Manufacturing Resources ◽  
Cloud Service Composition ◽  
Automatic Manufacturing

Manufacturing cloud service composition is the key way to improve the utilization of manufacturing resources and manufacturing capabilities, realize added value and efficiency of manufacturing resources and manufacturing capabilities. It has great significance on cloud manufacturing implementation and carry. Therefore, the paper presents automatic forwarding search method called AMCSC-HFS for manufacturing cloud service composition based on AI plan. The main purpose is to support meeting the actual need of large-scale and dynamic cloud manufacturing cloud service environment.

scholarly journals Service Outsourcing Character Oriented Privacy Conflict Detection Method in Cloud Computing

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Changbo Ke ◽  
Zhiqiu Huang ◽  
Weiwei Li ◽  
Yi Sun ◽  
Fangxiong Xiao
Keyword(s):  
Cloud Computing ◽  
Service Composition ◽  
Description Logic ◽  
Service Providers ◽  
Cloud Service ◽  
User Privacy ◽  
Service Outsourcing ◽  
Privacy Preference ◽  
Cloud Service Composition

Cloud computing has provided services for users as a software paradigm. However, it is difficult to ensure privacy information security because of its opening, virtualization, and service outsourcing features. Therefore how to protect user privacy information has become a research focus. In this paper, firstly, we model service privacy policy and user privacy preference with description logic. Secondly, we use the pellet reasonor to verify the consistency and satisfiability, so as to detect the privacy conflict between services and user. Thirdly, we present the algorithm of detecting privacy conflict in the process of cloud service composition and prove the correctness and feasibility of this method by case study and experiment analysis. Our method can reduce the risk of user sensitive privacy information being illegally used and propagated by outsourcing services. In the meantime, the method avoids the exception in the process of service composition by the privacy conflict, and improves the trust degree of cloud service providers.

SECURITY IN CLOUD COMPUTING IN INDIAN GOVERNMENT

2021 ◽  
Vol 12 (3) ◽  
Author(s):  
Nitin Vishnu Choudhari ◽  
Dr. Ashish B Sasankar
Keyword(s):  
Cloud Computing ◽  
Service Delivery ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Security ◽  
End Users ◽  
Security Architecture ◽  
Security Measures ◽  
End User ◽  
Cloud Service Providers

Abstract –Today Security issue is the topmost problem in the cloud computing environment. It leads to serious discomfort to the Governance and end-users. Numerous security solutions and policies are available however practically ineffective in use. Most of the security solutions are centered towards cloud technology and cloud service providers only and no consideration has been given to the Network, accessing, and device securities at the end-user level. The discomfort at the end-user level was left untreated. The security of the various public, private networks, variety of devices used by end-users, accessibility, and capacity of end-users is left untreated. This leads towards the strong need for the possible modification of the security architecture for data security at all levels and secured service delivery. This leads towards the strong need for the possible adaption of modified security measures and provisions, which shall provide secured hosting and service delivery at all levels and reduce the security gap between the cloud service providers and end-users. This paper investigates the study and analyze the security architecture in the Cloud environment of Govt. of India and suggest the modifications in the security architecture as per the changing scenario and to fulfill the future needs for the secured service delivery from central up to the end-user level. Keywords: Cloud Security, Security in GI Cloud, Cloud Security measures, Security Assessment in GI Cloud, Proposed Security for GI cloud

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