Fast and Dynamic Resource Provisioning for Quality Critical Cloud Applications

Author(s):  
Huan Zhou ◽  
Yang Hu ◽  
Junchao Wang ◽  
Paul Martin ◽  
Cees De Laat ◽  
...  
Author(s):  
Salini Suresh ◽  
L. Manjunatha Rao

Cloud-based research collaboration platforms render scalable, secure and inventive environments that enabled academic and scientific researchers to share research data, applications and provide access to high- performance computing resources. Dynamic allocation of resources according to the unpredictable needs of applications used by researchers is a key challenge in collaborative research environments. We propose the design of Cloud Container based Collaborative Research (CCCORE) framework to address dynamic resource provisioning according to the variable workload of compute and data-intensive applications or analysis tools used by researchers. Our proposed approach relies on–demand, customized containerization and comprehensive assessment of resource requirements to achieve optimal resource allocation in a dynamic collaborative research environment. We propose algorithms for dynamic resource allocation problem in a collaborative research environment, which aim to minimize finish time, improve throughput and achieve optimal resource utilization by employing the underutilized residual resources.


2016 ◽  
Vol 15 (9) ◽  
pp. 7035-7040
Author(s):  
Sakshi Grover ◽  
Mr. Navtej Singh Ghumman

Although cloud computing is now becoming more advanced and matured as many companies have released their own computing platforms to provide services to public, but the research on cloud computing is still in its infancy. Apart from many other challenges of cloud computing, efficient management of energy is one of the most challenging research issues. In this paper we review the existing algorithm of dynamic resource provisioning and allocation algorithms and holistically work to boost data center energy efficiency and performance. This particular paper purposes a) heterogeneous workload and its implication on data centers energy efficiency b) solving the problem of VM resource scheduling to cloud applications


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