Energy-efficient resource-provisioning algorithms for optical clouds

Rising energy costs and climate change have led to an increased concern for energy efficiency (EE). As information and communication technology is responsible for about 4% of total energy consumption worldwide, it is essential to devise policies aimed at reducing it. In this paper, we propose a rout...

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Bibliographic Details
Published in:Journal of optical communications and networking 2013-03, Vol.5 (3), p.226-239
Main Authors: Buysse, J., Georgakilas, K., Tzanakaki, A., De Leenheer, M., Dhoedt, B., Develder, C.
Format: Article
Language:English
Subjects:
Algorithms
Cloud computing
Clouds
Computer networks
Energy consumption
Energy efficiency
Information technology
Mathematical models
Optical fiber amplifiers
Optical fiber networks
Optical switches
Power demand
Resource provisioning
Routing
Routing (telecommunications)
Scheduling
Servers
WDM networks
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Summary:Rising energy costs and climate change have led to an increased concern for energy efficiency (EE). As information and communication technology is responsible for about 4% of total energy consumption worldwide, it is essential to devise policies aimed at reducing it. In this paper, we propose a routing and scheduling algorithm for a cloud architecture that targets minimal total energy consumption by enabling switching off unused network and/or information technology (IT) resources, exploiting the cloud-specific anycast principle. A detailed energy model for the entire cloud infrastructure comprising a wide-area optical network and IT resources is provided. This model is used to make a single-step decision on which IT end points to use for a given request, including the routing of the network connection toward these end points. Our simulations quantitatively assess the EE algorithm's potential energy savings but also assess the influence this may have on traditional quality-of-service parameters such as service blocking. Furthermore, we compare the one-step scheduling with traditional scheduling and routing schemes, which calculate the resource provisioning in a two-step approach (selecting first the destination IT end point and subsequently using unicast routing toward it). We show that depending on the offered infrastructure load, our proposed one-step calculation considerably lowers the total energy consumption (reduction up to 50%) compared to the traditional iterative scheduling and routing, especially in low- to medium-load scenarios, without any significant increase in the service blocking.
ISSN:1943-0620
1943-0639
DOI:10.1364/JOCN.5.000226