2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical A 2013
DOI: 10.1109/greencom-ithings-cpscom.2013.51
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Robust Redundancy Elimination for Energy-Aware Routing

Abstract: Many studies have shown that energy-aware routing (EAR) can significantly reduce energy consumption of a backbone network. Redundancy Elimination (RE) techniques provide a complementary approach to reduce the amount of traffic in the network. In particular, the GreenRE model combines both techniques, offering potentially significant energy savings.We propose a concept for respecting uncertain rates of redundant traffic within the GreenRE model, closing the gap between theoretical modeling and drawn-from life d… Show more

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Cited by 8 publications
(12 citation statements)
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References 28 publications
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“…As there is a duality gap between the primal and dual models due to the integrality of the primal model, we cannot simply get the optimal solution using the compact formulation based on Bertsimas and Sim methodology like in existing works [30,18]. In other words, the result obtained from the compact formulation is a lower bound on energy savings.…”
Section: Constraint Generation (Exact Algorithm)mentioning
confidence: 94%
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“…As there is a duality gap between the primal and dual models due to the integrality of the primal model, we cannot simply get the optimal solution using the compact formulation based on Bertsimas and Sim methodology like in existing works [30,18]. In other words, the result obtained from the compact formulation is a lower bound on energy savings.…”
Section: Constraint Generation (Exact Algorithm)mentioning
confidence: 94%
“…energy cost mentioned in this paper). Previous studies have considered robustness either on traffic volumes [30] or on redundancy rates [18]. To the best of our knowledge, this is the first work combining uncertainties in both traffic demand volumes and compression rates.…”
Section: Introductionmentioning
confidence: 97%
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“…Another important aspect concerns the intrinsic uncertainty which affects traffic demands [54,55]. Classic techniques for Robust Optimization in ILP flow problems can be naturally adapted to account for traffic variation in the energy-aware network management scenario.…”
Section: Robustnessmentioning
confidence: 99%
“…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 [102] x x x Approximated shared and dedicated protection [103] x x x x [104] x x Failure probabilities x New power state [110] x x [111] x ECMP and robustness [53] Fully splittable [112] free splitting ratio [113,114] [ 115,116] x x Traffic unaware because only link loads considered [117,118] x x OSPF is modified [119] x OSPF is mo...…”
Section: Literature Classificationmentioning
confidence: 99%