The increasing tendency of network service users to use cloud computing encourages web service vendors to supply services that have different functional and nonfunctional (quality of service) features and provide them in a service pool. Based on supply and demand rules and because of the exuberant growth of the services that are offered, cloud service brokers face tough competition against each other in providing quality of service enhancements. Such competition leads to a difficult and complicated process to provide simple service selection and composition in supplying composite services in the cloud, which should be considered an NP-hard problem. How to select appropriate services from the service pool, overcome composition restrictions, determine the importance of different quality of service parameters, focus on the dynamic characteristics of the problem, and address rapid changes in the properties of the services and network appear to be among the most important issues that must be investigated and addressed. In this paper, utilizing a systematic literature review, important questions that can be raised about the research performed in addressing the above-mentioned problem have been extracted and put forth. Then, by dividing the research into four main groups based on the problem-solving approaches and identifying the investigated quality of service parameters, intended objectives, and developing environments, beneficial results and statistics are obtained that can contribute to future research.

http://romisatriawahono.net/lecture/rm/survey/network%20security/Jula%20-%20Cloud%20Computing%20-%202014.pdf

Review: Cloud computing service composition: A systematic literature review

A systematic literature review on QoS-aware service composition and selection in cloud environment

A combinatorial optimization algorithm for multiple cloud service composition

Cloud computing is currently emerging as an ever-changing, growing paradigm that models “everything-as-a-service.” Virtualised physical resources, infrastructure, and applications are supplied by service provisioning in the cloud. The evolution in the adoption of cloud computing is driven by clear and distinct promising features for both cloud users and cloud providers. However, the increasing number of cloud providers and the variety of service offerings have made it difficult for the customers to choose the best services. By employing successful service provisioning, the essential services required by customers, such as agility and availability, pricing, security and trust, and user metrics can be guaranteed by service provisioning. Hence, continuous service provisioning that satisfies the user requirements is a mandatory feature for the cloud user and vitally important in cloud computing service offerings. Therefore, we aim to review the state-of-the-art service provisioning objectives, essential services, topologies, user requirements, necessary metrics, and pricing mechanisms. We synthesize and summarize different provision techniques, approaches, and models through a comprehensive literature review. A thematic taxonomy of cloud service provisioning is presented after the systematic review. Finally, future research directions and open research issues are identified.

/pdf/a-study-on-strategic-provisioning-of-cloud-computing-3cn5txbgth.pdf

A Study on Strategic Provisioning of Cloud Computing Services

Cloud service composition builds new value-added services by combining existing single services. However, because of the exuberant growth of cloud services and the varying quality of service (QoS), discovering required services and creating a service composition with certain quality guarantees becomes a significant technical issue and attracts much concern. Computational intelligence techniques are considered to be effective in solving such problems, and researchers have made substantial efforts in this area. Nevertheless, to the best of our knowledge, there is not any systematic research about this issue with a particular focus on computing intelligence. Thus, the current study aims to create a panoramic view of QoS-aware cloud service composition from the perspective of computational intelligence. The objectives of this paper are to (1) investigate the relevant studies on this field; (2) make a comprehensive examination of the literature from different aspects: active researchers, research motivations, QoS parameters, algorithms, datasets, optimization strategies and could layers; (3) identify the areas which need further research. For this, a search protocol has been well defined, and 105 articles from 2009 to 2018 were selected. This study classified these articles into three groups, including non-heuristic, heuristic and meta-heuristic, and then examined the research works from several aspects. The results indicate that reducing response time is the most important motivation for researchers, and meta-heuristic algorithms, especially genetic algorithms, are the most widely used computational intelligence techniques. Besides, the most widely used QoS attributes and datasets are also revealed. Additionally, the study points out there are still some research challenges in this area, such as QoS evaluation in a dynamic environment and inter-service correlations. In general, this study classified and compared the existing computational intelligence techniques; analyzed the research status and identified future research directions. It can provide a basis for both researchers and practitioners who are interested in this area. More significantly, in the field of expert and intelligent systems, this study can assist in the design and development of expert and intelligent systems in enterprises, it can efficiently assist enterprises in business decisions and risk reduction.

QoS-aware cloud service composition: A systematic mapping study from the perspective of computational intelligence

Many recent studies have been addressing the service selection problem based on non-functional aspects due to the ever-increasing number of web services. However, most existing works about QoS-based service composition treat the services referred in service composition as independent ones from each other, and their correlations are usually ignored. In reality, the services supplied by service providers in cloud environment are not segregate and irrelevant with each other. In view of this challenging problem, we use Finite State Machine (FSM) to prescribe the legal invocation orders of these web services, also an improved Tree-pruning-based algorithm is proposed to create the Web Service Composition Tree (WSCT). After generating all of the feasible execution paths, a Simple Additive Weighting (SAW) technique is used to select an optimal one. At last, an experiment is presented for validating the performance of the method.

Huihui Bao

Papers

A QoS-Aware Service Selection Method for Cloud Service Composition