Efficient resource management for Cloud computing environments

Younge, Andrew J; Laszewski, Gregor von; Wang, Lizhe; Lopez-Alarcon, Sonia; Carithers, Warren

doi:10.1109/greencomp.2010.5598294

Cited by 226 publications

(116 citation statements)

References 21 publications

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“…Other advantages of cloud computing include convenient data access points, flexible and expandable (elastic) storage locations [10] , multi-tenancy resource allocation, reduced overall infrastructure costs and maintenance, and ease of use.…”

Section: Brief Background On Cloud Computingmentioning

confidence: 99%

Competencies for international nursing research in a wikinomics future

Schultz

Yeung

Hook

2012

JNEP

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Conducting nursing research in the international arena provides unique challenges previously unseen in the pre-Web 2.0 world. Facilitated by the combined use of cloud and tablet computing, the means to address such challenges are identified by the authors, based on their experiences as international consultants in informatics, multinational research, and strategy in China and Southeast Asia. Using a framework on Wikinomics by Tapscott and Williams, the authors discuss how a new approach to research is made possible using the "weapons of mass collaboration" modeled by Wikipedia®, Facebook®, and YouTube. Research tools such as Skype®, Tape-a-Talk®, Google Cloud® and voice-to-text applications are described.

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Section: Brief Background On Cloud Computingmentioning

confidence: 99%

Competencies for international nursing research in a wikinomics future

Schultz

Yeung

Hook

2012

JNEP

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“…The problem of allocating compute resources, i.e., placing VMs, in a cloud has been extensively studied over the last years (e.g., [30][31][32][33]). The same is true for networking resources in the cloud environment (e.g., [34][35][36]).…”

Section: Related Workmentioning

confidence: 99%

Allocating Compute and Network Resources Under Management Objectives in Large-Scale Clouds

2013

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We consider the problem of jointly allocating compute and network resources in a large Infrastructure-as-a-Service (IaaS) cloud. We formulate the problem of optimally allocating resources to virtual data centers (VDCs) for four well-known management objectives: balanced load, energy efficiency, fair allocation, and service differentiation. Then, we outline an architecture for resource allocation, which centers around a set of cooperating controllers, each solving a problem related to the chosen management objective. We illustrate how a global management objective is mapped onto objectives that govern the execution of these controllers. For a key controller, the Dynamic Placement Controller, we give a detailed distributed design, which is based on a gossip protocol that can switch between management objectives. The design is applicable to a broad class of management objectives, which we characterize through a property of the objective function. The property ensures the applicability of an iterative descent method that the gossip protocol implements. We evaluate, through simulation, the dynamic placement of VDCs for a large cloud under changing load and VDC churn. Simulation results show that this controller is effective and highly scalable, up to 100'000 nodes, for the management objectives considered.

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“…The data centers consist of thousands of heterogeneous servers that consume lots of power and produce large amounts of heat [13]. Green scheduling systems for Data a.…”

Section: Research Motivationmentioning

confidence: 99%

Performance Evaluation of Power Aware VM Consolidation using Live Migration

Sehdev¹,

Kumar²

2015

IJCNIS

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Abstract-PowerEfficiency is the efficient use of power and is a crucial come forth in cloud computing environment. Green Computing is nothing but is a cloud computing with efficient use of power and green refers to make the environment friendly to the user by saving heat and power. Data centre power efficiency in cloud environment will be reduced when virtualization is used as contrary to physical resource deployment to book adequate to grant all application requests. Nevertheless, in any case of the resource provisioning approximation, occasion remains in the way in which they are made attainable and workload is scheduled. The objective of this research work is therefore to pack workload into servers, selected as a function of their cost to operate, to achieve (or as close to) the utmost endorsed employment in a cost-efficient manner, avoiding occurrences where devices are under-utilized and management cost is acquired inefficiently. This work has enhanced the existing work by introducing the dynamic wake up calls either to shut down the active servers or restart the passive server. The wakeup calls has been initiated dynamically. The overall objective is to decrease the response time of users which will be increased during wakeup time in existing research work.

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Efficient resource management for Cloud computing environments

Cited by 226 publications

References 21 publications

Competencies for international nursing research in a wikinomics future

Competencies for international nursing research in a wikinomics future

Allocating Compute and Network Resources Under Management Objectives in Large-Scale Clouds

Performance Evaluation of Power Aware VM Consolidation using Live Migration

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