Modeling and performance analysis of large scale IaaS Clouds

Ghosh, Rahul; Longo, Francesco; Naik, Vijay K.; Trivedi, Kishor S.

doi:10.1016/j.future.2012.06.005

Cited by 112 publications

(70 citation statements)

References 36 publications

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“…VMs are deployed on PMs that may host multiple VMs. The deployed VMs are provisioned with request specific CPU, RAM, and disk capacity [1][2][3][4]. In this paper, we assume that a single VM takes the responsibility of a single job.…”

Section: System Modelmentioning

confidence: 99%

“…Users submit their work requests to the cloud, to be processed and the results are delivered. Typically, the rapid growth in demand for computational power driven by modern service-oriented applications has led to the establishment of large-scale virtualized data centers [1][2][3][4]. However, data centers consume a huge amount of energy resulting in high operating costs and resulting contribution to greenhouse gas (GHG) emissions.…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, our analysis is based on the VM provisioning model for the cloud [1,2], where a VM is deployed on a physical machine (PM) upon arrival of a user request, and each request (job) has work requirement which is represented by the computation time on a failure-free environment. The actual job completion time may become longer than the given work requirement because of occurrences of VM or PM failures and subsequent recovery process with or without replication.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Virtual Machine Replication on Achieving Energy-Efficiency in a Cloud

Mondal

Muppala

Machida³

2016

Electronics

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Abstract:The rapid growth in cloud service demand has led to the establishment of large-scale virtualized data centers in which virtual machines (VMs) are used to handle user requests for service. A user's request cannot be completed if the VM fails. Replication mechanisms can be used to mitigate the impact of failures. Further, data centers consume a large amount of energy resulting in high operating costs and contributing to significant greenhouse gas (GHG) emissions. In this paper, we focus on Infrastructure as a Service (IaaS) cloud where user job requests are processed by VMs and analyze the effectiveness of VM replications in terms of job completion time performance as well as energy consumption. Three different schemes: cold, warm, and hot replications are considered. The trade-offs between job completion time and energy consumption in different replication schemes are characterized through comprehensive analytical models which capture VM state transitions and associated power consumption patterns. The effectiveness of replication schemes are demonstrated through experimental results. To verify the validity of the proposed analytical models, we extend the widely used cloud simulator CloudSim and compare the simulation results with analytical solutions.

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Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Virtual Machine Replication on Achieving Energy-Efficiency in a Cloud

Mondal

Muppala

Machida³

2016

Electronics

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“…Bruneo, D. et al propose a technique to model and evaluate the VMM aging process and to investigate the optimal rejuvenation policy that maximizes the VMM availability under variable workload conditions [10]. Ghosha et al [11] develop a scalable stochastic analytic model for performance quantification of Infrastructure-as-a-Service (IaaS) Cloud. Reference [12] presents a framework called E-mc2 for modelling the energy consumption in cloud computing system.…”

Section: Related Workmentioning

confidence: 99%

Modeling and analyzing cost-aware fault tolerant strategy for cloud application

Chen¹,

Fan²,

Liu³

2016

International Conferences on Software Engineering and Knowledge Engineering

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1 Abstract-In this paper, we propose a method to model and analyze cost-aware fault tolerant strategy for cloud computing. First, Petri nets are used to describe the structure of cloud computing, including component, cloud service and cloud application, thus forming the fault tolerant model of cloud computing. Second, a dynamic fault tolerant strategy is proposed, which can dynamically make fault tolerant strategy with the lowest cost based on the current state and failed component. Third, we present operational semantics and related theories of Petri nets for establishing the correctness of our proposed method. We have also performed a series of simulations to evaluate our proposed approach. Results show that it can help reveal the structural and behavioral characteristics of cloud computing, and reduce the fault tolerant cost.

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“…[ Considering the performance dependency of IaaS clouds on a large set of parameters, e.g., workload, system characteristics and management policies [29] proposed a scalable stochastic analytic model for performance quantification of Infrastructure-as-a-Service (IaaS) Cloud. Specifically, a class of IaaS Clouds that offer tiered services by configuring physical machines into three pools with different provisioning delay and power consumption characteristics.…”

Section: B Study On Performance Toolsmentioning

confidence: 99%

Study of Response Time in Cloud Computing

Singh¹

2014

IJIEEB

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Abstract-Performance of a cloud is a critical issue and dependent on various factors that include load balancing used to distribute the load at data center. Proliferation of the cloud paradigm is profoundly dependent on the performance of the cloud. Therefore, to examine the cloud performance, it is significant to identify the factors that govern cloud performance. This work is focused to identify the factors that may have significant impact on the cloud performance. To identify the performance factors, we have reviewed the major publications of the last five years as well as the major real time cloud performance tools offered. Study revealed that response time is the major factor that has the significant impact on cloud computing performance. Finally, we have conducted an experiment to establish the dependency of response time on various load balancing techniques and number of data center. Experiment revealed that the round robin is directly proportional to the number of data center

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Modeling and performance analysis of large scale IaaS Clouds

Cited by 112 publications

References 36 publications

Virtual Machine Replication on Achieving Energy-Efficiency in a Cloud

Virtual Machine Replication on Achieving Energy-Efficiency in a Cloud

Modeling and analyzing cost-aware fault tolerant strategy for cloud application

Study of Response Time in Cloud Computing

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