Fed4Fire/CDN-X-ALL network metrics dataset for time series analysis in Media content delivery for 4G/5G networks

2020-01-12T19:42:31Z (GMT) by Roberto Viola

The following dataset was generated at VICOMTECH (https://www.vicomtech.org) under project/experiment CDN-X-ALL: "CDN edge-cloud computing for efficient cache and reliable streaming aCROSS Aggregated unicast-multicast LinkS".

Project funded by Fed4FIRE+ OC5 (https://www.fed4fire.eu) under grant 732638.

The dataset provides network metrics captures across several days employing a GStreamer-based MPEG-DASH player running on an UE connected to a LTE network.

Nitos LTE/OpenAirInterface (OAI) testbed (https://nitlab.inf.uth.gr/NITlab/nitos/lte) was used to deploy the LTE network.

CDN-like server/DASH Dataset -> Internet -> EPC/OAI -> eNodeB/OAI -> UE/DASH player

The player downloads MPEG-DASH video files provided by Distributed DASH dataset (https://dash.itec.aau.at/distributed-dash-datset/), a dataset for CDN-like experiments, and captures the following data:

  1. Date: date when the data is collected
  2. Player: type of the player (in this case it is always "GStreamer")
  3. Num: identifier of the player
  4. URLVid: URL of the MPD file
  5. Latency: latency experienced by the player
  6. BW: bandwidth experienced by the player
  7. Quality: chosen DASH video representation

During the experiments, other players run in order to generate realistic media streaming traffic at the CDN-like servers. These players start playing by following Poisson or Pareto distribution.

The dataset was used to train Machine Learning Time Series predictor in order to forecast network capabilities and can be used for further experimentation concerning time series analysis.