دانلود رایگان مقاله انگلیسی واسطه گری در محاسبات ابر محیطی مرتبط: نظرسنجی - الزویر 2018

Abstract

Cloud computing provides computing platforms and facilitates to optimize utilization of infrastructure resources, reduces deployment time and increases flexibility. The popularity of cloud computing led to development of interconnected cloud computing environments(ICCE) such as hybrid cloud, inter-cloud, multicloud, and federated cloud, enabling the possibilities to share resources among individual clouds. However, individual proprietary technologies and access interfaces employed by cloud service providers made it difficult to share resources. Interoperability and portability are two of the major challenges to be addressee to ensure seamless access and sharing of resources and services. Many cloud service providers have similar service offerings but different access patterns. It is difficult and time consuming for a cloud user to select an appropriate cloud service as per the applications requirement. Cloud user has to gather information from various cloud service providers and analyze them. Cloud broker has been proposed to address the challenge of cloud users to get best out of cloud provider. Cloud broker is an entity which works as an independent third party between cloud users and cloud providers. Cloud broker negotiates with several cloud providers as per users requirements and tries to select the best services. Cloud broker coordinates the sharing of resources and provides interoperability and portability with other cloud providers. In this paper, a comprehensive survey of cloud brokering in interconnected cloud computing environments has been provided. The need and importance of cloud broker has been discussed. The existing architectures and frameworks of Cloud Brokering are reviewed. A comprehensive literature survey of various Cloud Brokering techniques is presented. A taxonomy of Cloud Brokering techniques has been presented and analyzed on the basis of their strengths and weaknesses/limitations. The taxonomy includes pricing, multi-criteria, quality of services, optimization and trust techniques. The techniques are analyzed on various performance metrics. Research challenges and open problems are identified from reviewed techniques. A model for cloud broker is proposed to address identified challenges. We hope that our work will enable researchers to launch and dive deep into Cloud Brokering challenges in interconnected cloud computing environments.

Conclusion and Future Directions

Brokering is an essential part for providing aggregated services to cloud users. Broker helps CSPs to provide aggregate services on three levels i.e. IaaS, SaaS and PaaS. It also helps CSUs to get all types of services under one roof. A comprehensive survey of cloud brokering in interconnected cloud computing environment (ICCE) has been presented. Existing frameworks of ICCE, having cloud broker as one of the components, are discussed. Cloud brokering techniques are classified in different categories such as pricing, multi-criteria, optimization, QoS and trust based on the attributes. The strength and weaknesses/limitations of all surveyed techniques have been analyzed. Specific research directions and the various issues, challenges and open problems are explained. A model for cloud broker has been proposed. The cloud broker model proposed in section 2.2 will be designed and developed for our future work. The model will efficiently address research problems of cloud service management. Efficient techniques for service discovery in ICCE will be proposed. ICCE consists of similar types of service offered by various CSPs. Techniques to efficiently address QoS parameters in ranking of various services will be proposed. Techniques effectively addressing QoS parameters in service selection will be proposed. Service allocation on desired platform so that it can fulfill QoS requirement is one of important research issue. It will be addressed by competent techniques. Cloud brokering inherently a multi-criteria optimization problem. QoS parameters such as price, availability, reliability, response time, execution time, etc are important in designing optimization techniques for service management. CSUs are interested in trusted CSPs and various security parameters such as authentication, authorization, data integrity & privacy, identity management, etc. Techniques based on multi-agent and machine learning algorithms to address above problems will be proposed. Machine-learning-as-service is getting attention in cloud platforms. Monitoring various SLA parameters is also challenging task in ICCE. The proposed cloud broker will include monitoring as-a-service component to address monitoring issues.