Randomized rounding: a technique for provably good algorithms and algorithmic proofs
Combinatorica - Theory of Computing
Reducing network energy consumption via sleeping and rate-adaptation
NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
Routing for energy minimization in the speed scaling model
INFOCOM'10 Proceedings of the 29th conference on Information communications
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The current networks are often designed with redundancy in order to deal with unexpected failures, but this makes a large amount of energy consumption and bandwidth waste. In the real networks, the performance is limited by the link's capacity which gives an upper bound of the traffic amount conveying through the links. In order to explore energy saving methods in the networks, we consider a model with the link capacity constraints and study the globally energy-saving routing strategy under the capacity assumption. In many related studies, the traffic demands are considered to be scheduled simultaneously in one round, which provides us the lower bound of the demands routing, but the lower bound of one-time scheduling method is too relaxed and results in unnecessary link idleness and extra energy consumption. This paper focuses on a time-slot globally energy-saving routing strategy based on the capacity limited network model. In order to increase the bandwidth utility ratio a new scheduling model with capacity constraint is proposed and a scheduling strategy is developed that can decrease the energy consumption as well as meet the performance requirement. The scheduling strategy is a time-slot energy-efficient algorithm. It splits the scheduling demands time window into more than one time slot and allocates all the demands into this two time slots with the goal of minimizing energy consumption. Experiment results show that the time-slot globally routing algorithm effectively reduces energy consumption compared with existing methods.