A power efficient genetic algorithm for resource allocation in cloud computing data centers

Portaluri, Giuseppe; Giordano, Stefano; Kliazovich, Dzmitry; Dorronsoro, Bernabè

doi:10.1109/cloudnet.2014.6968969

Cited by 39 publications

(18 citation statements)

References 11 publications

(9 reference statements)

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“…For each test, 110 VM allocation requests are generated, each of them characterized by three parameters: (%CPU, %RAM, %Disk) uniformly distributed in the range [10,25]. We compared the effectiveness of the following five different algorithms introduced in the previous sections: 1) MODA-R; 2) MODA-A; 3) A-ITRA; 4) Fuzzy Mamdani; 5) Fuzzy Sugeno.…”

Section: Resultsmentioning

confidence: 99%

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A Fuzzy Logic Approach for Resources Allocation in Cloud Data Center

Adami

Gabbrielli

Giordano

et al. 2015

2015 IEEE Globecom Workshops (GC Wkshps)

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The rapidly increasing demand of Cloud services, asking for a flexible and dynamic design of the Cloud, has become a major challenge in DC deployment. Classical Traffic Engineering approaches are no longer enough to deal with the efficient use of IT and network resources in this highly distributed scenario. To cope with this issue, we propose two Fuzzy logic controllers for DC resource allocation based on Mamdani and Sugeno inference processes, that are able to take advantage of simple heuristic rules for efficient virtual machines allocation. To test the effectiveness of the proposed controllers we compare their performance with two variants of Multi-objective allocators as well as a simple Mono-dimensional algorithm. Preliminary simulation tests validate our proposal in terms of number of allocated requests and average server resource utilization.

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Section: Resultsmentioning

confidence: 99%

“…For this reason we introduce the concept of Pareto-optimal solutions [10]. Considering two different solutions x and y associated to a set of objective functions f 1 , f 2 , .…”

Section: A It Resource Allocatormentioning

confidence: 99%

A Fuzzy Logic Approach for Resources Allocation in Cloud Data Center

Adami

Gabbrielli

Giordano

et al. 2015

2015 IEEE Globecom Workshops (GC Wkshps)

Self Cite

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“…In starting the reliability of any virtual machine is full means 100% and if any machine produces the result within time limit then its reliability increases but in other case if it fails to produce the result within time then its reliability decreases and when any machine's reliability goes below the threshold then it is removed. Giuseppe Portaluri, Stefano Giordano, Dzmitry Kliazovich, Bernab´e Dorronsoro [11] proposes a power efficient resource allocation algorithm for user submitted tasks. The algorithm is based on the Genetic algorithm.…”

Section: Literature Surveymentioning

confidence: 99%

A New Enhanced Mechanism for Fault Tolerance using Resource Optimization

Kaur¹,

Kaur²

2016

IJCA

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In these days there is a very little fraction of peoples who does not know about the cloud. Cloud offers various services to its users on demand. In Cloud Computing one of the major problem areas is Fault Tolerance. In cloud there is a term named virtualization that is very important and common. In virtualization that there is a dynamic number of virtual machines having different operating systems run on a single physical machine. In this paper a fault tolerance technique i.e. Enhanced Energy Aware Fault Tolerance Resource Optimization (EEAFTRO) technique is proposed. The purpose of this proposed technique is to optimize the resources efficiently so that the possibility of fault becomes less. If after effecient resource optimization or resource allocation fault occurs, then by using effective fault tolerance technique it can be handled. The proposed algorithm helps to minimize the execution time of tasks.

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“…In [51], the authors introduced a power efficient resource allocation algorithm for jobs in cloud computing data centers. The developed approach was also based on GA. Resource allocation was performed to optimize job completion time and data center power consumption.…”

Section: ) Predicting the Upcoming Number Of The (Vm)mentioning

confidence: 99%

Power management in virtualized data centers: state of the art

et al. 2016

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Cloud computing is an emerging technology in the field of computing that provides access to a wide range of shared resources. The rapid growth of cloud computing has led to establishing numerous data centers around the world. As data centers consume huge amounts of power, enhancing their power efficiency has become a major challenge in cloud computing. This paper surveys previous studies and researches that aimed to improve power efficiency of virtualized data centers. This survey is a valuable guide for researchers in the field of power efficiency in virtualized data centers following the cloud computing model.

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A power efficient genetic algorithm for resource allocation in cloud computing data centers

Cited by 39 publications

References 11 publications

A Fuzzy Logic Approach for Resources Allocation in Cloud Data Center

A Fuzzy Logic Approach for Resources Allocation in Cloud Data Center

A New Enhanced Mechanism for Fault Tolerance using Resource Optimization

Power management in virtualized data centers: state of the art

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