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Resource allocation and consolidation in a multi-core server cluster using a Markov decision process model

Yanzhi Wang, Shuang Chen, H. Goudarzi, M. Pedram
2013 International Symposium on Quality Electronic Design (ISQED)  
Each core in the cluster is modeled using a continuous-time Markov decision process (CTMDP).  ...  In this paper, an SLA-based resource allocation problem in a server cluster is considered.  ...  Each core in the server cluster is modeled using a continuous-time Markov decision process (CTMDP) [17] [18] , in which actions are execution frequencies (and supply voltages) for processing the service  ... 
doi:10.1109/isqed.2013.6523677 dblp:conf/isqed/WangCGP13 fatcat:sbdv3den2rhwva3rciqi3tci4q

An Intelligent and Cost-Efficient Resource Consolidation Algorithm in Nanoscale Computing Environments

MeSuk Kim, ALam Han, TaeYoung Kim, JongBeom Lim
2020 Applied Sciences  
Because of the large number of nanoscale devices in the system, we developed an efficient resource consolidation algorithm in terms of complexity and employed the hidden Markov model to predict the devices  ...  The performance evaluation shows that our resource consolidation algorithm is effective for predicting the devices' scheduling decisions and efficiency in terms of overhead cost and complexity.  ...  Acknowledgments: We thank the anonymous reviewers for their careful reading and insightful suggestions to help improve the manuscript.  ... 
doi:10.3390/app10186494 doaj:563c03ed8f514848be99e066b8e03a3f fatcat:ssjpi3iwdjbgvfe562uzhee3em

A comparison of resource allocation process in grid and cloud technologies

Huda Hallawi, Jörn Mehnen, Hongmei He
2018 Journal of Physics, Conference Series  
This paper is addressing a comprehensive study of the resources allocation processes in both technologies.  ...  Cloud Resource allocation suffers from extra challenges abbreviated by achieving good load balancing and making right consolidation decision.  ...  Acknowledgment This work has been funded by the Ministry of Higher Education and Scientific Research of Iraq. The authors gratefully acknowledge this support.  ... 
doi:10.1088/1742-6596/1032/1/012048 fatcat:4yi4nydbh5gbfmw3mbdxszr6vi

Stochastic Markov Model Approach for Efficient Virtual Machines Scheduling on Private Cloud

Hsu Mon Kyi, Thinn Thu Naing
2011 International Journal on Cloud Computing Services and Architecture  
To analyze the performance of this scheduling and allocation on cloud infrastructure, an analytical performance model approach using Stochastic Markov model is proposed to measure the scalability and tractability  ...  Cloud computing is deployed a large set of virtualized computing resources in different infrastructures and various development platforms.  ...  Resource Allocation Decision Model To calculate the resource allocation decision process, we design a continuous time Markov chain (CTMC) shown on Figure Figure 3 .  ... 
doi:10.5121/ijccsa.2011.1301 fatcat:kek7wkrjwbamnh4qelbyexhtui

An Intelligent Approach to Resource Allocation on Heterogeneous Cloud Infrastructures

Jack Marquez, Oscar H. Mondragon, Juan D. Gonzalez
2021 Applied Sciences  
Cloud service providers are widely offering different types of storage infrastructures and multi-NUMA architecture servers.  ...  In this study, we present a novel approach comprised of a hierarchical framework based on genetic programming to solve problems related to data placement and virtual machine allocation for analytics applications  ...  Acknowledgments: Results presented in this paper were obtained using the Chameleon and Cloud-Lab testbed supported by the US National Science Foundation.  ... 
doi:10.3390/app11219940 fatcat:amovakfsuvh3xgdh2wrr3euwxe

Energy-Efficient Datacenters

Massoud Pedram
2012 IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems  
Furthermore, provisioning resources in a cost-optimal manner so as to meet different performance criteria such as throughput or response time has become a critical challenge.  ...  Pervasive use of cloud computing and the resulting rise in the number of datacenters and hosting centers (which provide platform or software services to clients who do not have the means to set up and  ...  Acknowledgement-I would like to thank my Ph.D. student, Hadi Goudarzi, who contributed heavily to the extensive prior work review provided in this paper, and anonymous reviewers for their valuable suggestions  ... 
doi:10.1109/tcad.2012.2212898 fatcat:evaz3gc7mjdrphuq2v75g2dona

Machine Learning Methods for Reliable Resource Provisioning in Edge-Cloud Computing

Thang Le Duc, Rafael García Leiva, Paolo Casari, Per-Olov Östberg
2019 ACM Computing Surveys  
and server side.  ...  consolidation, and application elasticity and remediation.  ...  -88749-R) and the Comunidad de Madrid grant EdgeData-CM (P2018/TSC-4499).  ... 
doi:10.1145/3341145 fatcat:vkzofhgipfhqtm2z2w5swivksy

Self-adaptive provisioning of virtualized resources in cloud computing

Jia Rao, Xiangping Bu, Kun Wang, Cheng-Zhong Xu
2011 Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems - SIGMETRICS '11  
We treat cloud resource allocation as a distributed learning task, in which each VM being a highly autonomous agent submits resource requests according to its own benefit.  ...  In this paper, we propose a distributed learning mechanism that facilitates self-adaptive virtual machines resource provisioning.  ...  This work was supported in part by U.S. NSF grants CNS-0702488, CRI-0708232, CNS-0914330, and CCF-1016966.  ... 
doi:10.1145/1993744.1993790 dblp:conf/sigmetrics/RaoBWX11 fatcat:ijrx33ycjbawbbvxbvegfhoywm

Self-adaptive provisioning of virtualized resources in cloud computing

Jia Rao, Xiangping Bu, Kun Wang, Cheng-Zhong Xu
2011 Performance Evaluation Review  
We treat cloud resource allocation as a distributed learning task, in which each VM being a highly autonomous agent submits resource requests according to its own benefit.  ...  In this paper, we propose a distributed learning mechanism that facilitates self-adaptive virtual machines resource provisioning.  ...  This work was supported in part by U.S. NSF grants CNS-0702488, CRI-0708232, CNS-0914330, and CCF-1016966.  ... 
doi:10.1145/2007116.2007157 fatcat:czupn76wbzf3jkxyf6553lufza

A Combination of Host Overloading Detection and Virtual Machine Selection in Cloud Server Consolidation based on Learning Method [article]

Li Huixi, Xiao Yinhao, Shen Yongluo
2022 arXiv   pre-print
In server consolidation, the traditional solution is to divide the problem into multiple small problems such as host overloading detection, virtual machine (VM) selection and VM placement and solve them  ...  In cloud data center (CDC), reducing energy consumption while maintaining performance has always been a hot issue.  ...  Problem Description and Proposed Methodology In this section, we first describe the energy consumption model, then model VM migration and consolidation as a Markov Decision Process (MDP) and formulate  ... 
arXiv:2206.13717v1 fatcat:os7l5yvpcjf7hexi5fth2ljtri

Consolidation of multi-tier workloads with performance and reliability constraints

Andrea Sansottera, Davide Zoni, Paolo Cremonesi, William Fornaciari
2012 2012 International Conference on High Performance Computing & Simulation (HPCS)  
This work proposes a consolidation model that considers power, performance and reliability aspects simultaneously.  ...  There are two main innovative contributions in the model, focused on performance and reliability requirements.  ...  In active/active clusters, in the event of a server failure, the workload can be still processed by the surviving server in the cluster, but the load on this server increases [6] .  ... 
doi:10.1109/hpcsim.2012.6266893 dblp:conf/ieeehpcs/SansotteraZCF12 fatcat:nlikm3if3jfhdoeirwsqk7e6cm

Managing Overloaded Hosts for Dynamic Consolidation of Virtual Machines in Cloud Data Centers under Quality of Service Constraints

Anton Beloglazov, Rajkumar Buyya
2013 IEEE Transactions on Parallel and Distributed Systems  
the specified QoS goal based on a Markov chain model.  ...  Dynamic consolidation of Virtual Machines (VMs) is an effective way to improve the utilization of resources and energy efficiency in Cloud data centers.  ...  Calheiros, Saurabh Garg, Sivaram Yoganathan, and Andrey Kan from the University of Melbourne, and Egor Gladkikh from G-SCOP Laboratory of Grenoble for their input and constructive comments on improvements  ... 
doi:10.1109/tpds.2012.240 fatcat:647jnop3xzatxdzyp3px6oevuq

SECURE RESILIENT EDGE CLOUD DESIGNED NETWORK

Tarek Saadawi, Akira Kawaguchi, Myung Lee, Abbe Mowshowitz
2019 IEICE transactions on communications  
This paper focuses on three main aspects of the CPS: a) resource management in mobile cloud computing; b) information management in dynamic distributed databases; and c) biological-inspired intrusion detection  ...  and connectivity, and the scalability to support massive numbers of end devices in a variety of applications.  ...  We also model the resource allocation problem for partitioned mobile applications as a semi-Markov Decision Process (SMDP) [10] .  ... 
doi:10.1587/transcom.2019nri0002 fatcat:4tztlpsa6be63ncstuyn7b2r5m

A Novel Resource Scheduling Model for Cloud Data Center based on Game Analysis and Optimization Theory

2017 Revista Técnica de la Facultad de Ingeniería Universidad del Zulia  
In this paper, we propose the novel resource scheduling model for the cloud data center based on game analysis and optimization theory.  ...  Considering that the data center to collect all the key data, and the effective integration of all kinds of the data resources, structures open information resources sharing platform, the decision-making  ...  ACKNOWLEDGEMENT This paper is financially supported by the project named: Research and application design of the energyefficient and the efficient multi-service aggregation cloud (NO. 2014BAH02F02).  ... 
doi:10.21311/001.39.12.06 fatcat:jmwk2m5asvhcndu7ieg43lwdkq

Multi-Objective Biogeography-Based Method to Optimize Virtual Machine Consolidation

Kai Shi, Huiqun Yu, Fei Luo, Guisheng Fan
2016 Proceedings of the 28th International Conference on Software Engineering and Knowledge Engineering  
 Abstract-Virtual machine consolidation (VMC) is an important issue in cloud computing, which can be used to reduce power consumption and achieve reasonable resource allocation.  ...  Meanwhile, three optimization objectives for server power consumption, load balancing and migration resource overhead are mainly addressed.  ...  Haiping Ma and Dan Simon [22] discussed migration models using markov theory and blended BBO for constrained optimization.  ... 
doi:10.18293/seke2016-151 dblp:conf/seke/ShiYLF16 fatcat:vcyo6y34rbfaxnvuu3ginifehy
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