Towards Reliability Evaluation and Integration in Cloud Resource Management

In partnership with

Team Members

Mohammad Zulkernine
Mohammad Zulkernine PI
Dr. Anwar Haque
Dr. Anwar Haque CO-PI
A Alam
A Alam PhD student


In this research, the goal is to propose a reliability evaluation model and integrate the developed model in cloud resource management such as Virtual Machine (VM) allocation, VM migration, and cloud federation formation in order to increase the cloud service reliability. In this research, firstly a cloud reliability evaluation model is proposed. Some types of failures from different domains of the cloud environment are considered to evaluate cloud reliability. To propose the evaluation model, a classification strategy for cloud failures is also outlined. Secondly, to show the impact of the integration of the proposed model, a multi-objective placement model for interdependent VMs in cloud is proposed while considering both reliability and some quality of service. A multi-objective genetic algorithm is used to solve the placement problem heuristically. Thirdly, a Markov-based failure prediction model is proposed to anticipate the failures of cloud servers. The proposed prediction model is then integrated into a VM migration model in a multi-cloud setting to maximize cloud reliability while reducing VM communication delay. The VM migration problem is solved optimally and heuristically using the Artificial Bee Colony (ABC) algorithm. Finally, a reliability-based cloud federation model is proposed using a hedonic coalition formation game based on a reliability-driven utility function. All proposed models will serve as a guide to both customers and cloud service providers towards the achievement of reliable resource allocation, migration, and federation formation. The effectiveness of all the models has been demonstrated through experiments. The evaluation shows that the models are computationally efficient and achieve higher cloud reliability.


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