Abstract
Cloud computing enables users to use shared system resources in an efficient pay-as-you-go manner. However, the reliability of cloud computing is a challenging proposition. Cloud users cannot improve the reliability of their cloud environment from the hardware and system level. On the other hand, due to the cost and complexity of the system, improving the reliability of specific users using practical methods is not straightforward for the operators of cloud systems. In this paper, we attempt to optimize the reliability of the cloud system by using the correlation between cost and reliability. We conduct a comprehensive and detailed analysis of the reliability of clouds, extract vital features that can be used to improve system reliability and consider cost constraints. We propose the reliability model and virtual machine (VM) provisioning/request model; based on this model, we propose an SLA-oriented reliability assurance scheme to continuously optimize the reliability of clouds. The experimental results not only indicate the validity of the model and schemes proposed in this paper but also provide a new perspective for the continuous optimization of cloud system reliability.
Highlights
The significant growth in cloud applications has caused a boom in cloud infrastructures
Existing reliability models for clouds is limited to its applicability
Many users are reluctant to pay more to improve the reliability of the cloud environment they use
Summary
The significant growth in cloud applications has caused a boom in cloud infrastructures. In [19], [20], some existing reliability mechanisms can guarantee the reliability of cloud services to 99% These methods require additional backup and storage hardware resources to store system and app logs and checkpoints to restore the system state caused by failures or interruptions. Due to cost constraints, service providers, or cloud data center operators cannot improve the reliability of each user via redundancy. Hot standby nodes and related applications, services, and software components are running but do not process data or requests. To better model and analyze the reliability of VMs, the running state of VMs can be divided into two stages: in stage 1, the VMs are reliable enough, that is, the reliability of the VMs is higher than the threshold This stage only focuses on the reliability of the main components and hot spare parts of the cloud without considering the cold spare parts. When the replacement is completed, the reliability of the system is equivalent to the initial state with the HSP redundancy strategy, and the VM system is restored to Phase 1
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