Reliability and high availability have always been a major concern in distributed systems. Providing highly available and reliable services in cloud computing is essential for maintaining customer confidence and satisfaction and preventing revenue losses. Although various solutions have been proposed for cloud availability and reliability, but there are no comprehensive studies that completely cover all different aspects in the problem. This paper presented a ‘Reference Roadmap’ of reliability and high availability in cloud computing environments. A big picture was proposed which was divided into four steps specifying through four pivotal questions starting with ‘Where?’, ‘Which?’, ‘When?’ and ‘How?’ keywords. The desirable result of having a highly available and reliable cloud system could be gained by answering these questions. Each step of this reference roadmap proposed a specific concern of a special portion of the issue. Two main research gaps were proposed by this reference roadmap.

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Reliability and high availability in cloud computing environments: a reference roadmap

Despite the wide utilization of cloud computing (e.g., services, applications, and resources), some of the services, applications, and smart devices are not able to fully benefit from this attractive cloud computing paradigm due to the following issues: (1) smart devices might be lacking in their capacity (e.g., processing, memory, storage, battery, and resource allocation), (2) they might be lacking in their network resources, and (3) the high network latency to centralized server in cloud might not be efficient for delay-sensitive application, services, and resource allocations requests. Fog computing is promising paradigm that can extend cloud resources to edge of network, solving the abovementioned issue. As a result, in this work, we propose an architecture of IoT service delegation and resource allocation based on collaboration between fog and cloud computing. We provide new algorithm that is decision rules of linearized decision tree based on three conditions (services size, completion time, and VMs capacity) for managing and delegating user request in order to balance workload. Moreover, we propose algorithm to allocate resources to meet service level agreement (SLA) and quality of services (QoS) as well as optimizing big data distribution in fog and cloud computing. Our simulation result shows that our proposed approach can efficiently balance workload, improve resource allocation efficiently, optimize big data distribution, and show better performance than other existing methods.

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An Architecture of IoT Service Delegation and Resource Allocation Based on Collaboration between Fog and Cloud Computing

Highly reliable architecture using the 80/20 rule in cloud computing datacenters

Service reliability modeling and evaluation of active-active cloud data center based on the IT infrastructure

Hyper-scale data centers are used to host cloud computing interfaces to support the increasing demand for storage and computational resources. For achieving specific service level agreements (SLA), this infrastructure demands highly available cloud computing systems. It is necessary to analyze the server failure incidents to determine the way of improving the reliability of the system since the computational interruption causes financial losses for the data center owners. Regarding the reliability analysis, it is important to characterize the time to failure and time to repair of the servers. In this paper, a publicly available data set from Google cloud-cluster data center will be analyzed to find the distribution function for the time to failure and the time to repair for the servers in a cloud based data centers.

Characterizing Failure and Repair Time of Servers in a Hyper-scale Data Center

With the continuous growth of application requirements and a significant advance in the research of cloud computing systems, a large number of cloud computing systems nowadays based on different structures and virtualization technologies are still being developed. However, dependability of cloud computing system is always a critical issue for all the cloud service providers, brokers, carriers and consumers around the world. How to ensure the dependability of cloud computing systems is still not well solved by former researchers. This paper first introduces the infrastructure of a cloud computing system and its major actors. Based on the research of the running mode of a cloud computing system, main influencing factors of cloud computing dependability and its normal failure modes are given. It provides a generic definition of cloud computing system dependability, which including availability, performability, security, recoverability and so on. We also discuss some methods to establish cloud computing dependability models, such as analytic method, state space method and simulating method. In order to evaluate the validity of the cloud dependability measurement method, a novel simulating approach is proposed with well-designed framework and procedure. Through reasonable simulating and analysis, proper solutions can be promoted to find and solve the problem related to cloud computing systems dependability. Our future work will focus on an integrated software platform for cloud computing system dependability simulating and verification.

Ning Hu

Papers

Research on dependability of cloud computing systems