Broadband cellular networks are emerging to be the most common means for mobile data access worldwide. Predictions from industry analysts indicate that the volume of data through cellular data networks will increase exponentially in near future. Understanding of the mobile data traffic via measurement and analysis is critical for the development of resource management techniques for these networks. While spectrum resources are of great concern, this project specifically focuses on the energy required to operate the cellular network infrastructure, specifically base stations. The project undertakes a significant modeling exercise with two goals. One goal is intellectual, driven towards understanding the spatio-temporal dynamics of mobile traffic and discovering possible structure or relationships. The project uses state-of-the-art machine learning tools to develop models using large-scale data collected directly from the operator's networks. Such modeling will bring new insights that in turn will help to deploy and manage future generation cellular data networks. The second goal is utilitarian. Here, techniques are developed to predict base station loads for use in resource management, specifically energy. Algorithms are designed to exploit energy-optimization opportunities to turn off specific network resources based on the forecasted load.

The project has significant broader impact. It develops technologies to appreciably reduce energy consumption in cellular networks. Overall, this exercise will both reduce cost, and contribute to the environment. The project also contributes to several green initiatives in both institutions and to the education and training of graduate students.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
1117597
Program Officer
Thyagarajan Nandagopal
Project Start
Project End
Budget Start
2011-08-01
Budget End
2014-07-31
Support Year
Fiscal Year
2011
Total Cost
$103,774
Indirect Cost
Name
Lucent Technologies Bell Laboratories
Department
Type
DUNS #
City
Murray Hill
State
NJ
Country
United States
Zip Code
07974