Energy aware network operations
INFOCOM'09 Proceedings of the 28th IEEE international conference on Computer Communications Workshops
Green networking for major components of information communication technology systems
EURASIP Journal on Wireless Communications and Networking
Proceedings of the ACM SIGCOMM 2010 conference
Small-time scale network traffic prediction based on flexible neural tree
Applied Soft Computing
Real-time network traffic prediction based on a multiscale decomposition
ICN'05 Proceedings of the 4th international conference on Networking - Volume Part I
A study on micro level traffic prediction for energy-aware routers
ACM SIGOPS Operating Systems Review
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Recently, as significant increase of Internet traffic, power consumption of ICT devices is growing dramatically. Energy-saving of routers is one of important problems in future networks. There are some studies to reduce the power consumption by adjusting routers' performance according to the volume of incoming/outgoing traffic. In such routers high-grained and accurate prediction of future traffic is very important for controlling power savings. In this paper, we propose a traffic prediction method suitable for performance adjustable routers which achieves accurate traffic prediction in short-term. We discuss about the impacts of prediction parameters and their tuning methods, for accurate of prediction. Through trace-driven simulations with real traffic, we show that our prediction method can reduce up to 95% of power consumption without any packet loss.