Server consolidation with migration control for virtualized data centers

Ferreto, Tiago; Netto, Marco A. S.; Calheiros, Rodrigo N.; Rose, César A. F. De

doi:10.1016/j.future.2011.04.016

Cited by 264 publications

(132 citation statements)

References 11 publications

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“…The experimentation yielded the applicability of this approach to effectively determine which virtual machines should be migrated and on which physical machines to host them while minimizing operational and migration costs. In [82], authors proposed a Linear Programming formulation and heuristics to control VM migration that gives priority to the virtual machines with steady capacity. In order to draw comparison between this migration-control approaches with the well-established eager-migration-based solutions, the simulations are implemented using TU-Berlin and Google data center workloads.…”

Section: Scheduling Based On Virtualizationmentioning

confidence: 99%

Resource Scheduling in Cloud Environmet: A Survey

Mangla¹,

Singh²,

Rana³

2016

Adv. Sci. Technol. Res. J.

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Cloud Computing offers the avant-garde services at a stretch that are too attractive for any cloud user to ignore. With its growing application and popularization, IT companies are rapidly deploying distributed data centers globally, posing numerous challenges in terms of scheduling of resources under different administrative domains. This perspective brings out certain vital factors for efficient scheduling of resources providing a wide genre of characteristics, diversity in context of level of service agreements and that too with user-contingent elasticity. In this paper, a comprehensive survey of research related to various aspects of cloud resource scheduling is provided. A comparative analysis of various resource scheduling techniques focusing on key performance parameters like Energy efficiency, Virtual Machine allocation and migration, Cost-effectiveness and Service-Level Agreement is also presented.

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Section: Scheduling Based On Virtualizationmentioning

confidence: 99%

Resource Scheduling in Cloud Environmet: A Survey

Mangla¹,

Singh²,

Rana³

2016

Adv. Sci. Technol. Res. J.

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“…The larger the I is, the longer the duration of the traffic surge. 6 In this subsection, we use the bursty workload generator (with I=100, 400, and 1000) to investigate the non-monotonic response time variations under the condition that the workload of a consolidated system is bursty. Figure 7 shows the response time of Sys_Const with the original RUBBoS workload (constant at WL=2100) consolidated with Sys_Inc which has bursty workload with various I values (also I=1, that is, the case of original RUBBoS workload).…”

Section: Bursty Workloads Increase Performance Interferencementioning

confidence: 99%

“…Thus, in the periods recognized as high workload, the VM is assigned low priority on CPU allocation by the scheduler. 6 The burstiness level of the original RUBBoS workload generator is I=1. Finally, one more result with the Limit=50% configuration (i.e, fifty-fifty CPU splitting) is shown in Figure 8, so as to show the performance interference from bursty workload on a consolidated system is unavoidable even under unsaturated CPU utilization in the disjoint CPU allocation scenario.…”

Section: Bursty Workloads Increase Performance Interferencementioning

confidence: 99%

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Revisiting Performance Interference among Consolidated n-Tier Applications: Sharing is Better Than Isolation

Kanemasa

Wang

et al. 2013

2013 IEEE International Conference on Services Computing

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Abstract-Performance unpredictability is one of the major concerns slowing down the migration of mission-critical applications into cloud computing infrastructures [4]. An example of non-intuitive result is the measured n-tier application performance in a virtualized environment that showed increasing workload caused a competing, co-located constant workload to decrease its response time [12]. In this paper, we investigate the sensitivity of measured performance in relation to two factors: (1) consolidated server specification of virtual machine resource availability, and (2) burstiness of n-tier application workload. Our first and surprising finding is that specifying a complete isolation, e.g., 50-50 even split of CPU between two co-located virtual machines (VMs) results in significantly lower performance compared to a fully-shared allocation, e.g., up to 100% CPU for both co-located VMs. This happens even at relatively modest resource utilization levels (e.g., 40% CPU in the VMs). Second, we found that an increasingly bursty workload also increases the performance loss among the consolidated servers, even at similarly modest utilization levels (e.g., 70% overall). A potential solution to the first problem (performance loss due to resource allocation) is crosstier-priority scheduling (giving higher priority to shorter jobs), which can reduce the performance loss by a factor of two in our experiments. In contrast, bursty workloads are a more difficult problem: our measurements show they affect both the isolation and sharing strategies in virtual machine resource allocation.

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“…There are a number of processes running in the background. These processes consume more memory and energy to reduce this utilization of memory and energy and to make system flexible there arose a concept of OFF [1]. Using these OFF concept switch off the unwanted processes which occupy the memory using Ad-hoc network in distributed environment.…”

Section: Introductionmentioning

confidence: 99%

Survey on Android application for power efficiency in private cloud

Kadam¹

2017

ijecs

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Nowadays distributed systems are used everywhere. In distributed environment as there are numbers of processes running in the environment from which some processes are not required to execute for that specific instance. To schedule that process and balance the energy load in network traffic. We use the OFF concept. In these OFF concept, we close the unwanted process running in the background using the Ad-hoc network. In private cloud it is not possible to administrate all machines at the same instance of time, to overcome this problem propose system gives the notification message to the administrator when particular machine having greater load value. This system also provides the remote operation of processes using an android device. The Administrator can remotely shut down the systems as well as stop the unwanted processes. Also, this provides the single URL for the same task in the absence of android device. An evaluation and comparative study of the proposed approach provides evidence of its merits in terms of elasticity, energy efficiency, and scalability, as well as of its feasibility in the presence of high workload rate.

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Server consolidation with migration control for virtualized data centers

Cited by 264 publications

References 11 publications

Resource Scheduling in Cloud Environmet: A Survey

Resource Scheduling in Cloud Environmet: A Survey

Revisiting Performance Interference among Consolidated n-Tier Applications: Sharing is Better Than Isolation

Survey on Android application for power efficiency in private cloud

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