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.

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.

A QoS-driven Service Selection Optimization Algorithm for Internet of Things

2020 ◽  
Author(s):  
Xiaofei Zhang ◽  
Juncheng Geng ◽  
Jianwei Ma ◽  
Hao Liu ◽  
Shuangxia Niu
Keyword(s):  
Internet Of Things ◽  
Service Composition ◽  
Large Scale ◽  
Service Selection ◽  
Smart Devices ◽  
Optimization Approach ◽  
Weighting Method ◽  
Composite Service ◽  
Lexicographic Optimization ◽  
Composition Problem

Abstract Currently, the smart devices have been widely deployed in Internet of Things (IoT). With the scale of IoT continues to increase, it brings big challenges for service composition in a large-scale IoT. For solving this problem, a QoS-driven service selection method based on the enhanced Genetic algorithm (EGS ~ QoS) is proposed in this paper. To decrease the scale of service composition, we use the lexicographic optimization approach and QoS constraint relaxation technique to find the candidate service with height QoS. Then, the IoT service composition problem is transformed into a single-objective optimization problem adopting a simple weighting method, and the final composite service meeting the user's QoS needs is found from the candidate service. Compared with the related algorithm, the simulation results show that EGS ~ QoS can efficiently and quickly select a composite service satisfying user's QoS needs, and is more suitable for solving the service composite problem in large-scale IoT services.

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. 

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.

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.

Securing Business IT on the Cloud

2015 ◽  
pp. 2022-2032
Author(s):  
Bina Ramamurthy
Keyword(s):  
Large Scale ◽  
Service Providers ◽  
Cloud Service ◽  
Access Point ◽  
Cloud Provider ◽  
Service Model ◽  
Platform As A Service ◽  
Security Challenges ◽  
Modern Business ◽  
Amazon Web Services

In this chapter, the author examines the various approaches taken by the popular cloud providers Amazon Web Services (AWS), Google App Engine (GAE), and Windows Azure (Azure) to secure the cloud. AWS offers Infrastructure as a Service model, GAE is representative of the Software as a Service, and Azure represents the Platform as a Service model. Irrespective of the model, a cloud provider offers a variety of services from a simple large-scale storage service to a complete infrastructure for supporting the operations of a modern business. The author discusses some of the security aspects that a cloud customer must be aware of in selecting a cloud service provider for their needs. This discussion includes the major threats posed by multi-tenancy in the cloud. Another important aspect to consider in the security context is machine virtualization. Securing these services involves a whole range of measures from access-point protection at the client end to securing virtual co-tenants on the same physical machine hosted by a cloud. In this chapter, the author highlights the major offerings of the three cloud service providers mentioned above. She discusses the details of some important security challenges and solutions and illustrates them using screen shots of representative security configurations.

Cloud-TM

2015 ◽  
pp. 749-781
Author(s):  
João Barreto ◽  
Pierangelo Di Sanzo ◽  
Roberto Palmieri ◽  
Paolo Romano
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Economies Of Scale ◽  
Service Providers ◽  
Cloud Service ◽  
Capital Investments ◽  
Barriers To Entry ◽  
Capital Costs ◽  
Programming Paradigms ◽  
Pricing Schemes

By shifting data and computation away from local servers towards very large scale, world-wide spread data centers, Cloud Computing promises very compelling benefits for both cloud consumers and cloud service providers: freeing corporations from large IT capital investments via usage-based pricing schemes, drastically lowering barriers to entry and capital costs; leveraging the economies of scale for both services providers and users of the cloud; facilitating deployment of services; attaining unprecedented scalability levels. However, the promise of infinite scalability catalyzing much of the recent hype about Cloud Computing is still menaced by one major pitfall: the lack of programming paradigms and abstractions capable of bringing the power of parallel programming into the hands of ordinary programmers. This chapter describes Cloud-TM, a self-optimizing middleware platform aimed at simplifying the development and administration of applications deployed on large scale Cloud Computing infrastructures.

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.

scholarly journals Modelling and simulation of logistics service selection in cloud manufacturing

Procedia CIRP ◽  
2018 ◽  
Vol 72 ◽  
pp. 916-921 ◽  
Author(s):  
Longfei Zhou ◽  
Lin Zhang ◽  
Lei Ren
Keyword(s):  
Service Selection ◽  
Cloud Manufacturing ◽  
Modelling And Simulation ◽  
Logistics Service

Logistics Providers As Integrators of Intelligent Supply Chain Systems: an Innovative Aspect

2020 ◽  
Vol 9 (2) ◽  
pp. 28-34
Author(s):  
E. Kamchatova
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Information And Communication Technologies ◽  
Business Models ◽  
Service Providers ◽  
Response Times ◽  
Consumer Preferences ◽  
Added Value ◽  
Innovative Technologies ◽  
Logistics Service

This article is devoted to determining the role and place of logistics providers in managing international supply chains, analyzing their classifications and transforming business models in supply chains in the context of active e-Commerce development, as well as identifying specific features of system and virtual integrators of supply chains that can significantly increase the level of logistics service. Active use of e-Commerce leads to a significant reduction in response times to demand and encourages supply chain managers to constantly search for new solutions and innovative technologies that enable companies involved in the logistics chain to effectively interact with each other and jointly respond to changing consumer demands. In some cases, we are talking about creating new approaches and replacing existing technologies aimed at achieving the set results in terms of speed and flexibility in choosing options to meet consumer demand. Thus, the analysis allows us to state that logistics mediation as a special sphere of business activity has passed the stage of formation. The prerequisites for its improvement are primarily related to the implementation of the strategy of innovative balanced development of the national economy and further development of the logistics services market. Starting with the 3PL model, all logistics service providers actively use information and communication technologies, work in both retail and e-Commerce formats, and develop on the principle of system outsourcing, creating significant added value for their customers by saving time and resources, sharing responsibilities, and responding quickly to changes in consumer preferences. We can state with confidence that if earlier logistics was considered as a function of providing business, now it determines the system way of doing business and its innovative technologies.

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