July 02, 2019

RAn resource usage prediction for a 5G slice broker

  • Grinshpun E.
  • Gutterman C.
  • Sharma S.
  • Zussman G.

Network slicing will allow 5G network operators to oer a diverse set of services over a shared physical infrastructure. We focus on supporting the operation of the Radio Access Network (RAN) slice broker, which maps slice requirements into allocation of Physical Resource Blocks (PRBs). We rst develop a new metric, REVA, based on the number of PRBs available to a single Very Active bearer. REVA is independent of channel conditions and allows easy derivation of an individual wireless link?s throughput. In order for the slice broker to eciently utilize the RAN, there is a need for reliable and short term prediction of resource usage by a slice. To support such prediction, we construct an LTE testbed and develop custom additions to the scheduler. Using data collected from the testbed, we compute REVA and develop a realistic time series prediction model for REVA. Specically, we present the X-LSTM prediction model, based upon Long Short-Term Memory (LSTM) neural networks. Evaluated with data collected in the testbed, X-LSTM outperforms Autoregressive Integrated Moving Average Model (ARIMA) and LSTM neural networks by up to 31%. X-LSTM also achieves over 91% accuracy in predicting REVA. By using X-LSTM to predict future usage, a slice broker is more adept to provision a slice and reduce over-provisioning and SLA violation costs by more than 10% in comparison to LSTM and ARIMA.

View Original Article

Recent Publications

May 01, 2019

Digital networks at the nexus of productivity growth

  • Kamat S.
  • Prakash S.
  • Saniee I.
  • Weldon M.

This paper takes a fresh look at the debate over the relationship between digital technology and productivity. The argument of economic historian Robert J. Gordon is that digital technology will not lead to increases in productivity such as we saw in the last century, based on his analysis of the ...

January 01, 2019

Friendly, appealing or both? Characterising user experience in sponsored search landing pages

  • Bron M.
  • Chute M.
  • Evans H.
  • Lalmas M.
  • Redi M.
  • Silvestri F.

© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Many of today's websites have recognised the importance of mobile friendly pages to keep users engaged and to provide a satisfying user experience. However, next to the experience provided by the sites themselves, ...

January 01, 2019

Analyzing uber's ride-sharing economy

  • Aiello L.
  • Djuric N.
  • Grbovic M.
  • Kooti F.
  • Lerman K.
  • Radosavljevic V.

© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Uber is a popular ride-sharing application that matches people who need a ride (or riders) with drivers who are willing to provide it using their personal vehicles. Despite its growing popularity, there exist ...