Performance evaluation of cloud service considering fault recovery

Yang, Bo; Tan, Feng; Dai, Yuanshun

doi:10.1007/s11227-011-0551-2

Cited by 111 publications

(103 citation statements)

References 27 publications

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“…In contrast, other works such as [5] [6] [3] and [4] do not overlook the probability of VM or communication link failure. In [4], Javadi et al studied on a problem that is comparatively similar to ours, however, they consider the probability of failure in the private Cloud only.…”

Section: Related Workmentioning

confidence: 95%

Fault-Tolerant Resource Provisioning with Deadline-Driven Optimization in Hybrid Clouds

Ahene¹,

Acheampong²,

Xu³

2016

ijacsa

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Abstract-Resource provisioning remains as one of the challenging research problems in cloud computing, more importantly when considered together with service reliability. Fault-tolerance techniques such as fault-recovery is one of the techniques that can be employed to improve on service reliability. Technically, fault-recovery has obvious impact on service performance. Such impact requires detailed studies. Only few works on hybrid cloud resource provisioning address fault recovery and its impact. In this paper, we investigate the problem of resource provisioning in hybrid Clouds, considering the probability of hybrid cloud resource failure during job execution. We formulate this problem as an optimization model with operational cost as an objective function subject to the deadline constraint of jobs. Based on our proposed optimization model, we design a heuristic-based algorithm called dynamic resource provisioning algorithm (DRPA). We then perform extensive experiments to evaluate performance of the proposed algorithm based on a real world set of data. The results confirm the obvious impact of fault recovery on the performance metrics (operational cost and deadline violation rate) and also confirms that DRPA can be useful in minimizing operational cost.

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Section: Related Workmentioning

confidence: 95%

Fault-Tolerant Resource Provisioning with Deadline-Driven Optimization in Hybrid Clouds

Ahene¹,

Acheampong²,

Xu³

2016

ijacsa

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“…There is a serious gap in cloud computing fault tolerance research area, that is, the mutual impact of cloud performance overhead [52,[114][115][116][117] and HA solutions.…”

Section: Task Resubmissionmentioning

confidence: 99%

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

Mesbahi

Rahmani

Hosseinzadeh

2018

Hum. Cent. Comput. Inf. Sci.

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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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“…Furthermore, there are some interesting research papers in terms of cloud hardware, cloud service, mobile clouds and cloud performance evaluation [13,16,17]. However, most of them have focused on case studies of cloud service and cloud data storage technologies.…”

Section: Related Researchmentioning

confidence: 99%

Reliability Analysis Based on a Jump Diffusion Model with Two Wiener Processes for Cloud Computing with Big Data

Tamura

Yamada

2015

Entropy

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At present, many cloud services are managed by using open source software, such as OpenStack and Eucalyptus, because of the unification management of data, cost reduction, quick delivery and work savings. The operation phase of cloud computing has a unique feature, such as the provisioning processes, the network-based operation and the diversity of data, because the operation phase of cloud computing changes depending on many external factors. We propose a jump diffusion model with two-dimensional Wiener processes in order to consider the interesting aspects of the network traffic and big data on cloud computing. In particular, we assess the stability of cloud software by using the sample paths obtained from the jump diffusion model with two-dimensional Wiener processes. Moreover, we discuss the optimal maintenance problem based on the proposed jump diffusion model. Furthermore, we analyze actual data to show numerical examples of dependability optimization based on the software maintenance cost considering big data on cloud computing.

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Performance evaluation of cloud service considering fault recovery

Cited by 111 publications

References 27 publications

Fault-Tolerant Resource Provisioning with Deadline-Driven Optimization in Hybrid Clouds

Fault-Tolerant Resource Provisioning with Deadline-Driven Optimization in Hybrid Clouds

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

Reliability Analysis Based on a Jump Diffusion Model with Two Wiener Processes for Cloud Computing with Big Data

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