Journal ArticleDOI
Reinforcement learning-based controller for adaptive workflow scheduling in multi-tenant cloud computing:
TLDR
This research presents a novel and scalable solution to achieve scalability and energy-efficient solution to gain high level of economic benefits through multi-tenancy in the cloud.Abstract:
Multi-tenancy is an essential feature in cloud computing and is a major component to achieve scalability and energy-efficient solution to gain high level of economic benefits. As the cloud, computi...read more
Citations
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Journal ArticleDOI
Multi-objective heuristics algorithm for dynamic resource scheduling in the cloud computing environment
K. Lalitha Devi,S. Valli +1 more
TL;DR: A cost-optimized resource scheduling strategy in cloud computing environment is proposed aiming at minimizing the total cost of rental virtual machines from the central cloud and the effective of workload prediction algorithm based on SES and cost- optimization strategy is verified by simulation.
Book ChapterDOI
Enhanced Security and Privacy Issue in Multi-Tenant Environment of Green Computing Using Blockchain Technology
Journal ArticleDOI
Weighted double deep Q-network based reinforcement learning for bi-objective multi-workflow scheduling in the cloud
Journal ArticleDOI
Intelligent grading system based on deep learning
Meng Xiao,Haibo Yi +1 more
TL;DR: According to the survey, off-line examination is still the main examination method in universities, primary and secondary schools and the grading processing of off-LINE examination is time-consuming.
Journal ArticleDOI
Adaptive Cloud Bundle Provisioning and Multi-Workflow Scheduling via Coalition Reinforcement Learning
TL;DR: An adaptive cloud bundle provisioning and multi-work flow scheduling model to dynamically perform both the horizontal and vertical cloud resource scaling on multi-type VM instances for the execution of complex workflows is proposed.
References
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Journal ArticleDOI
Performance-effective and low-complexity task scheduling for heterogeneous computing
TL;DR: Two novel scheduling algorithms for a bounded number of heterogeneous processors with an objective to simultaneously meet high performance and fast scheduling time are presented, called the Heterogeneous Earliest-Finish-Time (HEFT) algorithm and the Critical-Path-on-a-Processor (CPOP) algorithm.
Journal ArticleDOI
A break in the clouds: towards a cloud definition
TL;DR: The concept of Cloud Computing is discussed to achieve a complete definition of what a Cloud is, using the main characteristics typically associated with this paradigm in the literature.
Proceedings ArticleDOI
Towards predictable datacenter networks
TL;DR: The case for extending the tenant-provider interface to explicitly account for the network is made, and the design of virtual network abstractions that capture the trade-off between the performance guarantees offered to tenants, their costs and the provider revenue are proposed.
Journal ArticleDOI
Examining the Challenges of Scientific Workflows
Yolanda Gil,Ewa Deelman,Mark H. Ellisman,Thomas Fahringer,Geoffrey C. Fox,Dennis Gannon,Carole Goble,Miron Livny,Luc Moreau,James D. Myers +9 more
TL;DR: A recent National Science Foundation workshop brought together domain, computer, and social scientists to discuss requirements of future scientific applications and the challenges they present to current workflow technologies.
Journal ArticleDOI
Allocating modules to processors in a distributed system
TL;DR: The author shows that unless P=NP, there can be no polynomial-time epsilon -approximate algorithm for the module allocation problem, nor can there exist a local search algorithm that requiresPolynomial time per iteration and yields an optimum assignment.
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