Managing power conservation in wireless networks

Authors:
Kongluan Lin;John Debenham;Simeon Simoff
Affiliations:
QCIS, FEIT, University of Technology, Sydney, Australia;QCIS, FEIT, University of Technology, Sydney, Australia;Computing and Mathematics, UWS, Sydney, Australia
Venue:
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Year:
2010

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Abstract

Amajor project is investigating methods for conserving power in wireless networks. A component of this project addresses methods for predicting whether the user demand load in each zone of a network is increasing, decreasing or approximately constant.These predictions are then fed into the power regulation system. This paper describes a real-time predictive model of network traffic load which is derived from experiments on real data. This model combines a linear regression based model and a highly reactive model that are applied to real-time data that is aggregated at two levels of granularity. The model gives excellent performance predictions when applied to network traffic load data.