A new optimization algorithm for power saving in backbone networks

Cheung, Catherine; Chu, Hon Wai; Xu, Sean Shensheng

doi:10.1109/icccn.2014.6911767

Cited by 4 publications

(5 citation statements)

References 17 publications

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“…Adaptive link rate is a popular technique to adjust a link capacity based on the ongoing traffic needs. In essence, these techniques alter link transmission rate by monitoring the traffic density , and . Link power modification takes place by (a) switching off links periodically, known as sleeping mode, or (b) modifying links' rate, known as rate switch (reducing or increasing it based on the traffic needs).…”

Section: Related Workmentioning

confidence: 99%

Towards power consumption in optical networks: a cognitive prediction‐based technique

Sarigiannidis

Papadimitriou

Nicopolitidis

et al. 2015

Int J Communication

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Summary Modern backbone, optical networks have developed into large, massive networks, which consist of numerous intermediate and terminal nodes as well as final users. These networks serve uninterruptedly multitude of users at the expense of considerable power consumption. Many research efforts are aimed at reducing energy consumption in large‐scale optical networks; however, this objective is deemed laborious: the operation of such networks has to continuously remain in good levels without disruptions. One of the most compelling techniques to remedy this situation is to switch off redundant links and devices at specific (short) periods. These links and devices remain idle as long as the network can cope with the underlying traffic demands. Hence, a power mechanism is required to manage how and when underutilized network elements may be silent during network operation. Nevertheless, this management entails fast processing and efficient decision making. While many research efforts neglect this serious factor, the problem of reducing the power consumption still threats the development of today's backbone network. In this work, an effective, cognitive power management technique is proposed by enhancing the decision making with traffic prediction. Traffic capacity is estimated in each link within the network supporting, thus, more efficient decisions on switching off underutilized or even idle network elements a priori. The technique introduced succeeds high accuracy levels, while it offers energy savings up to 30% lower than other energy‐aware schemes. Copyright © 2015 John Wiley & Sons, Ltd.

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Section: Related Workmentioning

confidence: 99%

Towards power consumption in optical networks: a cognitive prediction‐based technique

Sarigiannidis

Papadimitriou

Nicopolitidis

et al. 2015

Int J Communication

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“…Some work deal with elastic consumption and surprisingly few consider multi period, survivability or special QoS constraints. [58] x x x x [59,60] x x x x x Smart protection [54] x x x x Robustness [61] x x x x x Robustness, Smart protection [41] x x Elastic traffic [62] x x Bi-objective function [24] x Network design decisions [21] x [22,[63][64][65][66][67] x [23,47] x x x Piece-wise concave energy costs [68] x x Bidirectional link capacity [69] x x [70] [71]…”

Section: Literature Classificationmentioning

confidence: 99%

“…Some work deal with elastic consumption and surprisingly few consider multi period, survivability or special QoS constraints. x x Elastic traffic [62] x x Bi-objective function [24] x Network design decisions [21] x [22,[63][64][65][66][67] x [23,47] x x x Piece-wise concave energy costs [68] x x Bidirectional link capacity [69] x x [70] [71] x [72] x x [73,74] x x [75,76] x x [77] x Multi-topology routing [78,79] x Energy-Levels [80][81][82][83] x Node expansion, Multiple sleeping states [48,84] x x [85] x x x [86] x x [87,88] x x x x x [89] x [90] x x x x [91] x x Bi-objective function for energy and delay [92] x x x x hop-by-hop routing [93,94] x x x x Two macro-periods [95] x x [96] [97] x [55,98,99] x Redundancy elimination [100,101] x x x x…”

Section: Literature Classificationmentioning

confidence: 99%

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Energy management in communication networks: a journey through modeling and optimization glasses

Addis

Capone

Carello

et al. 2016

Computer Communications

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“…RELATED WORK According to [4], there are four main techniques to manage the energy consumed in fixed, wired, backbone networks, namely (i) adaptive link rate; (ii) interface proxying; (iii) energy-aware infrastructures; and (iv) energy-aware application. The adaptive link rate techniques [5][6][7][8][9] aim at adjusting the transmission rate of links based on their utilization. Link power modification takes place by (i) switching off links periodically or (ii) modifying link rate (reducing or increasing it based on the traffic needs).…”

Section: Introductionmentioning

confidence: 99%

An adaptive energy‐efficient framework for time‐constrained optical backbone networks

Sarigiannidis

Kakali

Fragakis³

2015

Int J Communication

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Power management has emerged as a challenge of paramount importance having strong social and financial impact in the community. The rapid growth of information and communication technologies made backbone networks a serious energy consumer. Concurrently, backbone networking is deemed as one of the most promising areas to apply energy efficient frameworks. One of the most popular energy efficient techniques, in the context of backbone networks, is to intentionally switch off nodes and links that are monitored underutilized. Having in mind that optical technology has thoroughly dominated modern backbone networks, the function of switching off techniques entails fast operation and rigorous decision-making because of the tremendous speed of the underlying optical media. This paper addresses this challenge by introducing a novel, adaptive, and efficient power management scheme for large-scale backbone networks. The proposed framework exploits traffic patterns and dynamics in order to effectively switch off the set of network entities in a periodic fashion. An adaptive decision-making algorithm is presented to maximize the network energy gains with respect to time constraints as well as QoS guarantees. The conducted simulation results reveal considerable improvements when applying the proposed framework compared with other inflexible energy efficient schemes. of 26rapid advancement of ICT networks should be accompanied with energy efficient frameworks and paradigms.Backbone networks constitutes the foundation of ICT. They connect end users together by providing access to multitude services such as voice, video, file transfer, and messaging. During the last decade, we have been witnesses of the massive penetration of optical networking in backbone infrastructure. Optical fiber offers huge capacity, scalability, reliability, and cost-effective access solution (e.g., fiber to the home). Undoubtedly, optical technology architectures established an end-game approach; hence, the question is transformed on how optical networking solutions could contribute towards energy conservation.Both academia and industry are in harness with in order to devise effective research solutions regarding energy reduction in optical backbone networks. According to [2], there are four main directions on minimizing energy consumption in ICT networks, which are as follows: (i) development of new environmental-friendly network components; (ii) re-defining physical characteristics regarding the signal transmission and reception; (iii) advancements in application layer; and (iv) allocating network resources in a more efficient way subject to energy consumption. The development of energy efficient components is a feasible task, however the progress of such development is slow. Low-attenuation and low-dispersion fibers are only a few examples of developing energyaware solutions in the physical layer. Even though such a solution is quite interesting, it might increase the transceiver cost and therefore the cost of the whole installation. Improvements in ...

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A new optimization algorithm for power saving in backbone networks

Cited by 4 publications

References 17 publications

Towards power consumption in optical networks: a cognitive prediction‐based technique

Towards power consumption in optical networks: a cognitive prediction‐based technique

Energy management in communication networks: a journey through modeling and optimization glasses

An adaptive energy‐efficient framework for time‐constrained optical backbone networks

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