Cost-Effective Routing for a Greener Internet

Bergler, Bernd; Preschern, Christopher; Reiter, Andreas; Kraxberger, Stefan

doi:10.1109/greencom-cpscom.2010.112

Cited by 4 publications

(5 citation statements)

References 12 publications

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“…A number of strategies have been developed to determine the best strategy for transferring data center jobs to locations where the electricity is cheaper [1,4,5]. This has been aided by the fast live VM migration that is possible with very short downtimes, on the order of a few seconds [28].…”

Section: Related Workmentioning

confidence: 99%

Benefits of green energy and proportionality in high speed wide area networks connecting data centers

Aksanli

Rosing

Monga

2012

2012 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE)

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Many companies deploy multiple data centers across the globe to satisfy the dramatically increased computational demand. Wide area connectivity between such geographically distributed data centers has an important role to ensure both the quality of service, and, as bandwidths increase to 100Gbps and beyond, as an efficient way to dynamically distribute the computation. The energy cost of data transmission is dominated by the router power consumption, which is unfortunately not energy proportional. In this paper we not only quantify the performance benefits of leveraging the network to run more jobs, but also analyze its energy impact. We compare the benefits of redesigning routers to be more energy efficient to those obtained by leveraging locally available green energy as a complement to the brown energy supply. Furthermore, we design novel green energy aware routing policies for wide area traffic and compare to state-of-the-art shortest path routing algorithm. Our results indicate that using energy proportional routers powered in part by green energy along with our new routing algorithm results in 10x improvement in per router energy efficiency with 36% average increase in the number of jobs completed.

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Section: Related Workmentioning

confidence: 99%

Benefits of green energy and proportionality in high speed wide area networks connecting data centers

Aksanli

Rosing

Monga

2012

2012 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE)

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“…This assumption is reasonable for small datacenter networks that own the WAN and incur low network costs. Consequently, related work has WANs used to increase system performance via load balancing [51], [36], [34] or improve energy efficiency by migrating jobs [8], [33], [3]. However, these arguments are not applicable for large WAN costs and datacenters that lease the network.…”

Section: Introductionmentioning

confidence: 99%

“…Previous publications concerned with energy costs primarily propose a follow the sun cost-management strategy [19], [29], [32], [8], [33], [3] and generally neglect the cost of wide area net-working (WAN) incurred by job migration between datacenters. This assumption is reasonable for small datacenter networks that own the WAN and incur low network costs.…”

Section: Introductionmentioning

confidence: 99%

Renewable Energy Prediction for Improved Utilization and Efficiency in Datacenters and Backbone Networks

Akşanlı

Venkatesh

Monga

et al. 2016

Computational Sustainability

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Datacenters are one of the important global energy consumers and carbon producers. However, their tight service level requirements prevent easy integration with highly variable renewable energy sources. Short-term green energy prediction can mitigate this variability. In this work, we first explore the existing short-term solar and wind energy prediction methods, and then leverage prediction to allocate and migrate workloads across geographically distributed datacenters to reduce brown energy consumption costs. Unlike previous works, we also study the impact of wide area networks (WAN) on datacenters, and investigate the use of green energy prediction to power WANs. Finally, we present two different studies connecting datacenters and WANs: the case where datacenter operators own and manage their WAN and the case where datacenters lease networks from WAN providers. The results show that prediction enables up to 90% green energy utilization, a 3x improvement over the existing methods. The cost minimization algorithm reduces expenses by up to 16% and increases performance by 27% when migrating workloads across datacenters. Furthermore, the savings increase up to 30% compared with no migration when servers are made energy-proportional. Finally, in the case of leasing the WAN, energy proportionality in routers can in-crease the profit of network providers by 1.6x.

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“…They use WAN to increase system performance via load balancing [6], [7] improve energy efficiency by migrating jobs [3], [4], [5], or to determine new datacenter locations [8]. But, these studies do not model the energy cost of WAN, the long-term datacenter power contracts or the benefits of local renewable energy sources.…”

Section: Introductionmentioning

confidence: 99%

“…Previous publications focused on geographically separated datacenters, employed "follow the sun" or cheaper cost of brown energy strategies, [3], [4], [5]. They use WAN to increase system performance via load balancing [6], [7] improve energy efficiency by migrating jobs [3], [4], [5], or to determine new datacenter locations [8].…”

Section: Introductionmentioning

confidence: 99%

A comprehensive approach to reduce the energy cost of network of datacenters

Akşanlı

Venkatesh

Rosing

et al. 2013

2013 IEEE Symposium on Computers and Communications (ISCC)

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Abstract-Several studies have proposed job migration over the wide area network (WAN) to reduce the energy of networks of datacenters by taking advantage of different electricity prices and load demands. Each study focuses on only a small subset of network parameters and thus their results may have large errors. For example, datacenters usually have long-term power contracts instead of paying market prices. However, previous work neglects these contracts, thus overestimating the energy savings by 2.3x. We present a comprehensive approach to minimize the energy cost of networks of datacenters by modeling performance of the workloads, power contracts, local renewable energy sources, different routing options for WAN and future router technologies. Our method can reduce the energy cost of datacenters by up to 28%, while reducing the error in the energy cost estimation by 2.6x.

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Cost-Effective Routing for a Greener Internet

Cited by 4 publications

References 12 publications

Benefits of green energy and proportionality in high speed wide area networks connecting data centers

Benefits of green energy and proportionality in high speed wide area networks connecting data centers

Renewable Energy Prediction for Improved Utilization and Efficiency in Datacenters and Backbone Networks

A comprehensive approach to reduce the energy cost of network of datacenters

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