An Intelligent Economic Approach for Dynamic Resource Allocation in Cloud Services

Wang, Xingwei; Wang, Xueyi; Che, Hao; Li, Keqin; Huang, Min; Gao, Chengxi

doi:10.1109/tcc.2015.2415776

Cited by 60 publications

(20 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Meng et al 23 developed a scheduling strategy for multiple workflows with different QoS requirements. In addition, several studies [24][25][26][27] proposed some task scheduling algorithms from the view of economic principle. Recently, some related work on clouds [28][29][30][31][32][33][34] is done.…”

Section: Related Workmentioning

confidence: 99%

A non‐cooperative game model for reliability‐based task scheduling in cloud computing

Wang

Liu

2020

Int J Communication

View full text Add to dashboard Cite

Summary Cloud computing is a newly emerging distributed system. Task scheduling is the core research of cloud computing which studies how to allocate the tasks among the physical nodes, so that the tasks can get a balanced allocation or each task's execution cost decreases to the minimum, or the overall system performance is optimal. Unlike task scheduling based on time or cost before, aiming at the special reliability requirements in cloud computing, we propose a non‐cooperative game model for reliability‐based task scheduling approach. This model takes the steady‐state availability that computing nodes provide as the target, takes the task slicing strategy of the schedulers as the game strategy, then finds the Nash equilibrium solution. We also design a task scheduling algorithm based on this model. It can be seen from the experiments that our task scheduling algorithm is better than the so‐called balanced scheduling algorithm.

show abstract

Section: Related Workmentioning

confidence: 99%

A non‐cooperative game model for reliability‐based task scheduling in cloud computing

Wang

Liu

2020

Int J Communication

View full text Add to dashboard Cite

show abstract

“…For cloud provider, this mechanism is achieved high revenue for the cloud providers and it implements a prototype allocation system in cloud computing with experimental solution and examine the performance of that mechanism. Xingwei Wang et al [23] researched a smart financial strategy for bidding on dynamic resource allocation (IEDA) and asked for a sensible auction round and a full qualified transaction relationship with suppliers and clients. The proposed algorithm is a cost prediction algorithm based on the neural back propagation network (BPNN) and a price matching algorithm, which is superior to market-level economic efficiency and confidence.…”

Section: Literature Surveymentioning

confidence: 99%

Resource Allocation in Cloud Computing for Energy Efficiency

R*,

2019

IJEAT

View full text Add to dashboard Cite

Cloud computing is a paradigm in which we have virtualized computer systems that deliver services, processing, storage, network, and other fundamental computing resources. Cloud computing enables low cost, device location independence, high reliability, scalability and sustainability. This paper describes the present state of cloud computing research by examining literature, identifying current study trends. We have analyzed the resource allocation method and concluded. It typically designs for high performance that supports the peak resource requirements. After several analyses the power consumption of data center and cloud systems as increased almost several times. There is a lack of research that addresses challenges of managing multiple resources with objective of allocating enough resources for each work load to optimizing power consumption. These papers survey various types of resource allocation algorithms that improve the cloud Infrastructure.

show abstract

“…Several researchers have studied different issues related to the adoption, challenges, and various business aspects for adoption of cloud services in an organization. Some researchers, including Gens, Leukel et al, Pearson and Benameur, Lindner et al, Cheung et al, Morgan and Conboy, Hsu and Yang, Huang et al, Wang et al, Misra et al, and Khan have given a comprehensive overview of cloud services and cloud computing.…”

Section: Background and Motivationmentioning

confidence: 99%

“…Zhang et al showed that there are several privacy protocols that need to be taken care of before adopting cloud computing. Wang et al proposed a modified model with resource allocation in the cloud adoption in organization.…”

Section: Background and Motivationmentioning

confidence: 99%

Identifying the moderating effect of trust on the adoption of cloud‐based services

Rahi

Bisui

Misra

2017

Int J Communication

View full text Add to dashboard Cite

Cloud computing provides a way to coordinate and share relevant information and data on real-time basis over an organization. The adoption of cloud services is one of the most emerging technological advances in the practice of current competitive business environment. The research done in this article is based on the analysis of the data obtained from the semiconductor sector. Cloud adoption would most likely be the best answer for them. However, because of various types of complexities, semiconductor industries may have to confront with a few trust issues while receiving cloud services. This article aims to identify the trust factors in the adoption of cloud services in semiconductor industries. Further, the moderating effect of these trust elements related to the technological, organizational, and environmental success factors has been discussed here. On the basis of literature survey, a hypothetical model has been developed, and the relationships among the latent variables have been studied by using structural equations. The study reveals that while trust factors moderate the technology and environment-related success factors, there is not much moderating effect of the trust issues on the organization-related success factors in the adoption of cloud services in semiconductor industries.

show abstract

An Intelligent Economic Approach for Dynamic Resource Allocation in Cloud Services

Cited by 60 publications

References 34 publications

A non‐cooperative game model for reliability‐based task scheduling in cloud computing

A non‐cooperative game model for reliability‐based task scheduling in cloud computing

Resource Allocation in Cloud Computing for Energy Efficiency

Identifying the moderating effect of trust on the adoption of cloud‐based services

Contact Info

Product

Resources

About