Journal
PROCEEDINGS OF THE 9TH ACM MULTIMEDIA SYSTEMS CONFERENCE (MMSYS'18)
Volume -, Issue -, Pages 460-465Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3204949.3208123
Keywords
Dataset; 4G; LTE; ns-3; Mobility; throughput; context information; adaptive video streaming
Funding
- Science Foundation Ireland (SFI) [13/IA/1892]
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In this paper, we present a 4G trace dataset composed of client-side cellular key performance indicators (KPIs) collected from two major Irish mobile operators, across different mobility patterns (static, pedestrian, car, bus and train). The 4G trace dataset contains 135 traces, with an average duration of fifteen minutes per trace, with viewable throughput ranging from 0 to 173 Mbit/s at a granularity of one sample per second. Our traces are generated from a wellknown non-rooted Android network monitoring application, GNetTrack Pro. This tool enables capturing various channel related KPIs, context-related metrics, downlink and uplink throughput, and also cell-related information. To the best of our knowledge, this is the first publicly available dataset that contains throughput, channel and context information for 4G networks. To supplement our real-time 4G production network dataset, we also provide a synthetic dataset generated from a large-scale 4G ns-3 simulation that includes one hundred users randomly scattered across a seven-cell cluster. The purpose of this dataset is to provide additional information (such as competing metrics for users connected to the same cell), thus providing otherwise unavailable information about the eNodeB environment and scheduling principle, to end user. In addition to this dataset, we also provide the code and context information to allow other researchers to generate their own synthetic datasets.
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