GreenCloud: a packet-level simulator of energy-aware cloud computing data centers

Kliazovich, Dzmitry; Bouvry, Pascal; Khan, Samee U.

doi:10.1007/s11227-010-0504-1

Cited by 478 publications

(263 citation statements)

References 9 publications

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“…Moreover, these show their applicability for the considered scheduling problem, scalability, and good efficiency. We are implementing the proposed heuristics in GreenCloud simulator [20] and in an Opportunistic Computing environment [21], [22].…”

Section: Discussionmentioning

confidence: 99%

Scalable, low complexity, and fast greedy scheduling heuristics for highly heterogeneous distributed computing systems

2013

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Abstract-For heterogeneous distributed computing systems, important design issues are scalability and system optimization. Given such systems, it is crucial to develop low computational complexity algorithms to schedule tasks in a manner that exploits the heterogeneity of the resources and applications. In this paper, we report three scalable, and fast scheduling heuristics for highly heterogeneous distributed computing systems. The heuristics are thoroughly compared with three other heuristics from the literature. The benchmarking outlines the performance of the schedulers, representing scalability, schedule length, computational complexity, and memory utilization. The set of experimental results shows that our heuristics perform as efficiently as the related approaches while featuring lower complexity, lower running time, and lower used memory. The experimental results also detail the various scenarios under which certain algorithms excel and fail.

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Section: Discussionmentioning

confidence: 99%

Scalable, low complexity, and fast greedy scheduling heuristics for highly heterogeneous distributed computing systems

2013

Self Cite

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“…Another simulator, GreenCloud [36], uses a more sophisticated and accurate network model by building on top of a network simulator. The main focus of GreenCloud is the measurement of energy consumption.…”

Section: Cloud Simulatorsmentioning

confidence: 99%

Discrete-event simulation for efficient and stable resource allocation in collaborative mobile cloudlets

Bohez

Verbelen

Simoens

et al. 2015

Simulation Modelling Practice and Theory

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The deployment of highly interactive, media-rich applications on mobile devices is hindered by the inherent limitations on compute power, memory and battery capacity of these hand-held platforms. The cloudlet concept, opportunistically offloading computation to nearby devices, has proven to be a viable solution in offering resourceintensive applications on mobile devices. In this paper, we propose to extend the cloudlet concept with collaborative scenarios, in which not only hardware resources for processing are shared between all cloudlet users, but also the data computed.In a cloudlet, the resource demand should be spread over all available cloudlet nodes. User mobility and fluctuations in wireless bandwidth will cause the optimal resource allocation to vary over time. The cloudlet middleware must continuously balance the performance gain of reallocating components with the operational costs in terms of user experience and management complexity. In this paper, we formulate this optimization problem based on a theoretical cloudlet model capturing the infrastructure, application structure and user behaviour.In order to solve this problem, two heuristic allocation algorithms based on Steepest Descent (SD) and Simulated Annealing (SA) are described. Besides optimality of the found solution, it is also important to limit the number of reallocations at runtime. To evaluate the performance and stability of the algorithms, we propose a discreteevent model for cloudlet simulation. For multiple application scenarios, we observe that SD performs 4 times less reallocations than SA. By introducing hysteresis, the number of reallocations by SA can be nearly halved without any significant degradation of application performance.

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“…More recently Cloud simulators have been proposed which are capable of modelling the tradeoff between not only cost and Quality of Service, but also energy consumption. These include CloudSim [9], GreenCloud [19], and MDCSim [22]. However, these do not allow modelling of multi-use clusters with interactive user workloads, nor do they support checkpointing.…”

Section: Simulationmentioning

confidence: 99%

Energy-efficient Checkpointing in High-throughput Cycle-stealing Distributed Systems

Forshaw

McGough

Thomas

2015

Electronic Notes in Theoretical Computer Science

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(2015) 'Energy-ecient checkpointing in high-throughput cycle-stealing distributed systems.', Electronic notes in theoretical computer science., 310. pp. 65-90. Further information on publisher's website: http://dx. The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that: • a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders. Please consult the full DRO policy for further details. Abstract Checkpointing is a fault-tolerance mechanism commonly used in High Throughput Computing (HTC) environments to allow the execution of long-running computational tasks on compute resources subject to hardware or software failures as well as interruptions from resource owners and more important tasks. Until recently many researchers have focused on the performance gains achieved through checkpointing, but now with growing scrutiny of the energy consumption of IT infrastructures it is increasingly important to understand the energy impact of checkpointing within an HTC environment. In this paper we demonstrate through trace-driven simulation of real-world datasets that existing checkpointing strategies are inadequate at maintaining an acceptable level of energy consumption whilst maintaing the performance gains expected with checkpointing. Furthermore, we identify factors important in deciding whether to exploit checkpointing within an HTC environment, and propose novel strategies to curtail the energy consumption of checkpointing approaches whist maintaining the performance benefits.

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GreenCloud: a packet-level simulator of energy-aware cloud computing data centers

Cited by 478 publications

References 9 publications

Scalable, low complexity, and fast greedy scheduling heuristics for highly heterogeneous distributed computing systems

Scalable, low complexity, and fast greedy scheduling heuristics for highly heterogeneous distributed computing systems

Discrete-event simulation for efficient and stable resource allocation in collaborative mobile cloudlets

Energy-efficient Checkpointing in High-throughput Cycle-stealing Distributed Systems

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