Managing Power Conservation in Wireless Networks

Publisher:
Springer
Publication Type:
Chapter
Citation:
Lecture Notes in Artificial Intelligence - Vol 6441 - Advanced Data Mining and Applications, 2010, 1, pp. 314 - 325
Issue Date:
2010-01
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A major 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.
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