Harnessing renewable energy in cloud datacenters: opportunities and challenges

Deng, Wei; Liu, Fangming; Jin, Hai; Li, Bo; Li, Dan

doi:10.1109/mnet.2014.6724106

Cited by 137 publications

(55 citation statements)

References 10 publications

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“…Taxonomy of recent research and challenges in managing and applying renewable energy in data center is provided by W. Deng et al in [12]. When, where and why to migrate from grid to renewable energy to power up data centers to result energy efficiency and minimum operational cost.…”

Section: Energy Efficiencymentioning

confidence: 99%

“…Green Grid and Green cloud computing are the innovations to ensure optimal utilization of resources and reduce the energy consumption. To measure carbon emissions from datacenters, carbon usage effectiveness (CUE) metric is proposed [12] which is the ratio of total carbon emissions by a datacenter to the power consumed by it. The overall power utilized by a datacenter depends on energy requirements of CPU, memory, Disk, routers and other network devices.…”

mentioning

confidence: 99%

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Optimization Techniques for Resource Provisioning and Load Balancing in Cloud Environment: A Review

Kaur¹,

Kaur²,

Singh³

2017

IJIEEB

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Abstract-Cloud computing is an emerging technology which provides unlimited access of versatile resources to users. The multifaceted and dynamic aspects of cloud computing require efficient and optimized techniques for resource provisioning and load balancing. Cloud monitoring is required identifying overutilized and underutilized of physical machines which hosting Virtual Machines (VMs). Load balancing is necessary for efficient and effective utilization of resources. Most of the authors have taken the objective to reduce the makespan for executing requests on multiple VMs. In this paper, a thorough review on scheduling and load balancing techniques has been done and different techniques have been analyzed on the basis of SLA Violations, CPU utilization, energy consumption and cost parameters.

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Section: Energy Efficiencymentioning

confidence: 99%

mentioning

confidence: 99%

Optimization Techniques for Resource Provisioning and Load Balancing in Cloud Environment: A Review

Kaur¹,

Kaur²,

Singh³

2017

IJIEEB

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“…The reason for this is that these data centres are typically embedded in buildings that also hold other functions, for example, office and meeting spaces, laboratories and lecture rooms in the case of universities. A major issue in this is also the lack of interoperability of generation, storage and heat recovery and current installation and maintenance costs versus payback [9]. By and large, data centre operators, who want to be green and use renewable energy, buy electricity that has been given a green label by their respective supplier without often being able to fully verify this.…”

Section: Ict -Energy Concepts For Energy Efficiency and Sustainabilitymentioning

confidence: 99%

Globally Optimised Energy-Efficient Data Centres

Pesch¹,

Rea²,

Torrens³

et al. 2017

ICT - Energy Concepts for Energy Efficiency and Sustainability

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Data centres are part of today's critical information and communication infrastructure, and the majority of business transactions as well as much of our digital life now depend on them. At the same time, data centres are large primary energy consumers, with energy consumed by IT and server room air conditioning equipment and also by general building facilities. In many data centres, IT equipment energy and cooling energy requirements are not always coordinated, so energy consumption is not optimised. Most data centres lack an integrated energy management system that jointly optimises and controls all its energy consuming equipments in order to reduce energy consumption and increase the usage of local renewable energy sources. In this chapter, the authors discuss the challenges of coordinated energy management in data centres and present a novel scalable, integrated energy management system architecture for data centre wide optimisation. A prototype of the system has been implemented, including joint workload and thermal management algorithms. The control algorithms are evaluated in an accurate simulationbased model of a real data centre. Results show significant energy savings potential, in some cases up to 40%, by integrating workload and thermal management.

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“…Deng et al [17] presented five aspects of applying renewable energy in the DCs: the renewable energy generation model, the renewable energy prediction model, the planning of green DCs (i.e., various renewable options, avalabity of energy sources, different energy storage devices), the intra-DC work loads scheduling, and the inter-DC load balancing. They also discussed the research challenges of powering DCs with renewable energy.…”

Section: Related Workmentioning

confidence: 99%

Renewable Energy-Aware Inter-Datacenter Virtual Machine Migration over Elastic Optical Networks

Zhang

Ansari

2015

2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom)

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Datacenters (DCs) are deployed in a large scale to support the ever increasing demand for data processing to support various applications. The energy consumption of DCs becomes a critical issue.Powering DCs with renewable energy can effectively reduce the brown energy consumption and thus alleviates the energy consumption problem. Owing to geographical deployments of DCs, the renewable energy generation and the data processing demands usually vary in different DCs. Migrating virtual machines (VMs) among DCs according to the availability of renewable energy helps match the energy demands and the renewable energy generation in DCs, and thus maximizes the utilization of renewable energy. Since migrating VMs incurs additional traffic in the network, the VM migration is constrained by the network capacity. The inter-datacenter (inter-DC) VM migration with network capacity constraints is an NP-hard problem. In this paper, we propose two heuristic algorithms that approximate the optimal VM migration solution. Through extensive simulations, we show that the proposed algorithms, by migrating VM among DCs, can reduce up to 31% of brown energy consumption.

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Harnessing renewable energy in cloud datacenters: opportunities and challenges

Cited by 137 publications

References 10 publications

Optimization Techniques for Resource Provisioning and Load Balancing in Cloud Environment: A Review

Optimization Techniques for Resource Provisioning and Load Balancing in Cloud Environment: A Review

Globally Optimised Energy-Efficient Data Centres

Renewable Energy-Aware Inter-Datacenter Virtual Machine Migration over Elastic Optical Networks

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