Power saving of IP over WDM: Coherent taxonomy, mechanism and technique: A review

Cloud computing combines the advantages of several computing paradigms and introduces ubiquity in the provisioning of services such as software, platform, and infrastructure. Data centers, as the main hosts of cloud computing services, accommodate thousands of high performance servers and high capacity storage units. Offloading the local resources increases the energy consumption of the transport network and the data centers although it is advantageous in terms of energy consumption of the end hosts. This chapter presents a detailed survey of the existing mechanisms that aim at designing the Internet backbone with data centers and the objective of energy-efficient delivery of the cloud services. The survey is followed by a case study where Mixed Integer Linear Programming (MILP)-based provisioning models and heuristics are used to guarantee either minimum delayed or maximum power saving cloud services where high performance data centers are assumed to be located at the core nodes of an IP-over-WDM network. The chapter is concluded by summarizing the surveyed schemes with a taxonomy including the cons and pros. The summary is followed by a discussion focusing on the research challenges and opportunities.

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A Quantitative Survey of the Power Saving Potential in IP-Over-WDM Backbone Networks

IEEE Communications Surveys & Tutorials ◽

10.1109/comst.2014.2364312 ◽

2016 ◽

Vol 18 (1) ◽

pp. 706-731 ◽

Cited By ~ 12

Author(s):

Ward Van Heddeghem ◽

Bart Lannoo ◽

Didier Colle ◽

Mario Pickavet ◽

Piet Demeester

Keyword(s):

Power Saving ◽

Quantitative Survey ◽

Ip Over Wdm ◽

Backbone Networks

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Energy-Efficiency in a Cloud Computing Backbone

Cloud Technology ◽

10.4018/978-1-4666-6539-2.ch012 ◽

2015 ◽

pp. 266-288

Author(s):

Burak Kantarci ◽

Hussein T. Mouftah

Keyword(s):

Cloud Computing ◽

Energy Consumption ◽

High Performance ◽

Data Centers ◽

High Capacity ◽

Power Saving ◽

Cloud Services ◽

Mixed Integer ◽

Ip Over Wdm ◽

Challenges And Opportunities

Cloud computing combines the advantages of several computing paradigms and introduces ubiquity in the provisioning of services such as software, platform, and infrastructure. Data centers, as the main hosts of cloud computing services, accommodate thousands of high performance servers and high capacity storage units. Offloading the local resources increases the energy consumption of the transport network and the data centers although it is advantageous in terms of energy consumption of the end hosts. This chapter presents a detailed survey of the existing mechanisms that aim at designing the Internet backbone with data centers and the objective of energy-efficient delivery of the cloud services. The survey is followed by a case study where Mixed Integer Linear Programming (MILP)-based provisioning models and heuristics are used to guarantee either minimum delayed or maximum power saving cloud services where high performance data centers are assumed to be located at the core nodes of an IP-over-WDM network. The chapter is concluded by summarizing the surveyed schemes with a taxonomy including the cons and pros. The summary is followed by a discussion focusing on the research challenges and opportunities.

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Power Efficient Port Assignment for Connection Provision in IP-over-WDM Optical Networks

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.701-702.1093 ◽

2014 ◽

Vol 701-702 ◽

pp. 1093-1097

Author(s):

Shu Du ◽

Ze Hui Xu ◽

Hai Tao Wang ◽

Wei Fu Peng

Keyword(s):

Electric Power ◽

Optical Networks ◽

Power Saving ◽

Wdm Networks ◽

Wdm Optical Networks ◽

Power Efficient ◽

Ip Over Wdm ◽

Connection Request ◽

State Transmission ◽

Time Aware

In the IP-over-WDM networks, electric power is more consumed at IP layer. This letter proposes two power-saving dynamic connection provision algorithms, called Most Used First (MUF) and State Transmission Time Aware (STTA) respectively, which can direct the incoming connection request to already provisioned router line cards and chassis, and hence reduce the number of active IP devices so to save electric power. For a typical network, MUF and STTA can save over 3% and 7% power respectively comparing with conventional power-unaware approach.

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