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

Service composition in multi-Cloud environments must coordinate self-interested participants, automate service selection, (re)configure distributed services, and deal with incomplete information about Cloud providers and their services. This work proposes an agent-based approach to compose services in multi-Cloud environments for different types of Cloud services: one-time virtualized services, e.g., processing a rendering job, persistent virtualized services, e.g., infrastructure-as-a-service scenarios, vertical services, e.g., integrating homogenous services, and horizontal services, e.g., integrating heterogeneous services. Agents are endowed with a semi-recursive contract net protocol and service capability tables (information catalogs about Cloud participants) to compose services based on consumer requirements. Empirical results obtained from an agent-based testbed show that agents in this work can: successfully compose services to satisfy service requirements, autonomously select services based on dynamic fees, effectively cope with constantly changing consumers' service needs that trigger updates, and compose services in multiple Clouds even with incomplete information about Cloud participants.

/pdf/agent-based-cloud-service-composition-43fmm3ken7.pdf

Agent-based Cloud service composition

In Cloud service composition, collaboration between brokers and service providers is essential to promptly satisfy incoming Cloud consumer requirements. These requirements should be mapped to Cloud resources, which are accessed via web services, in an automated manner. However, distributed and constantly changing Cloud-computing environments pose new challenges to automated service composition such as: (i) dynamically contracting service providers, which set service fees on a supply-and-demand basis, and (ii) dealing with incomplete information regarding Cloud resources (e.g., location and providers). To address these issues, in this work, an agent-based Cloud service composition approach is presented. Cloud participants and resources are implemented and instantiated by agents. These agents sustain a three-layered self-organizing multi-agent system that establishes a Cloud service composition framework and an experimental test bed. The self-organizing agents make use of acquaintance networks and the contract net protocol to evolve and adapt Cloud service compositions. The experimental results indicate that service composition is efficiently achieved despite dealing with incomplete information as well as coping with dynamic service fees.

Self-Organizing Agents for Service Composition in Cloud Computing

The popularity of cloud computing and IaaS has spawned numerous cloud service providers which offer various cloud services, including IaaS, to cloud users. These services vary considerably in terms of their performance and cost and the selection of a suitable cloud service becomes a complex decision making issue for a cloud service user. Furthermore, the cloud services have several attributes all of which are the criteria that have to be taken into account when making a service selection decision. In the presence of these multiple criteria, a compromise has to be made because in most real-world situations, no single service exceeds all other services in all criteria but one service may be better in terms of some of the criteria while other services may outperform it if judged on the basis of the remaining criteria. Multi-criteria decision-making is a sub-field in operations research that deals with the techniques to solve such multi-criteria problems. There are several methods of multicriteria decision-making. In this paper, we use key multi-criteria decision-making methods for IaaS cloud service selection in a case study which contains five basic performance measurements of thirteen cloud services by a third party monitoring service. We demonstrate the use of these multi-criteria methods for cloud service selection and compare the results obtained by using each method to find out how the choice of a particular MCDM method affects the outcome of the decision-making process for IaaS cloud service selection.

Iaas Cloud Selection using MCDM Methods

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

In this paper, we put forward a matching algorithm SMA between cloud computing services of multiple input/output parameters, which considers the semantic similarity of concepts in parameters based on WordNet. Moreover, a highly efficacious service composition algorithm Fast-EP and the improved FastB+-EP are presented. Then QoS information is utilized to rank the search results. At last, we show through experiment that our approach has better efficiency of service composition than traditional approaches.

Cloud Computing Service Composition and Search Based on Semantic

As the applications become more and more complicated, the requirement of Web service composition will be more urgent. In this paper, we put forward a new storage strategy for web services which can be flexibly extended in relational database. We also present a matching algorithm SMA between web services of multiple input/output parameters, which considers the semantic similarity of concepts in parameters based on WordNet. Moreover, a service composition algorithm Fast-EP based on the above storage strategy is presented. Because utilizing the characteristic and using index mechanism in relational database, we obtain highly efficient web service composition. We extract the feature vector of each web service or composite service, and create dynamic linear hash index on these vectors so that the results of each search could be hierarchical classified. QoS and service price are utilized to rank the result set. At last, we develop a Web services search engine WSIS and show through experiment that our approach in this system has better efficiency of service composition and higher recall ratio of service search than traditional approaches.

Efficient Web Service Composition and Intelligent Search Based on Relational Database

Current wrapper approaches break down in extracting data from differently structured and frequently changing Web pages. To tackle this challenge, this paper defines domain-specific ontology, captures the semantic hierarchy in Web pages automatically by exploiting both structural information and common formatting information, and recognizes and extracts data by using ontology-based semantic matching without relying on page-specific formatting. It is adaptive to differently structured and frequently changing Web pages for a domain of interest.

Weijie Ou

Papers

Cloud Computing Service Composition and Search Based on Semantic

Efficient Web Service Composition and Intelligent Search Based on Relational Database

Ontology-based HTML to XML conversion