acmmmsys Goto Github PK

Name: ACM MMSys

Type: Organization

Twitter: acmmmsys

ACM MMSys's Projects

2018-avtrack360

A repository containing the source code for the paper "AVTrack360: An Open Dataset and Software Recording People’s Head Rotations Watching 360° Videos on an HMD"

2018-dashc

A repository containing the source code for the paper "dashc: A Highly Scalable Client Emulator for DASH Video"

2018-hindsight

A repository containing the source code for the paper "HINDSIGHT: An R-Based Framework Towards Long Short Term Memory (LSTM) Optimization"

2018-http-adaptive-streaming-qoe-estimation-with-p.1203

A repository containing the source code and dataset for the paper "HTTP Adaptive Streaming QoE Estimation with ITU-T Rec. P.1203"

2018-mimir

A repository containing the source code for the paper "Mimir: An Automatic Reporting and Reasoning System for Deep Learning based Analysis in the Medical Domain"

2018-monroe-astream

A repository containing the source code for the AStream tool of the paper "Open Video Datasets over Operational Mobile Networks with MONROE"

2018-monroe-webstreamer

A repository containing the source code for the Webstreamer tool of the paper "Open Video Datasets over Operational Mobile Networks with MONROE"

2018-opencv.js

A repository containing the source code for the paper "OpenCV.js: Computer Vision Processing for the Open Web Platform"

2018-opensea

A repository containing the source code for the paper "OpenSea - Open Search Based Classification Tool"

2018-popsift

A repository containing the source code for the paper "PopSift: a faithful SIFT implementation for real-time applications"

2018-swapugc

A repository containing the source code for the paper "SWAPUGC: Software for Adaptive Playback of Geotagged UGC"

2019-360dataset

A Taxonomy and Dataset for 360-degree videos

2019-cave

Content-aware Video Encoding for Cloud Gaming

2019-nano

Supplementary material for the paper: "A Comparative Study of Video Annotation Tools for Scene Understanding: Yet (not) another Annotation Tool", shortly NANO

2019-two-layer_lf_compression

A repository containing the source code of the demo for the paper "Adaptive Two-Layer Light Field Compression Scheme Based on Sparse Reconstruction"

In this work, we present a 5G trace dataset collected from a major Irish mobile operator. The dataset is generated from two mobility patterns (static and car), and across two application patterns(video streaming and file download). The dataset is composed of client-side cellular key performance indicators (KPIs) comprised of channel-related metrics, context-related metrics, cell-related metrics and throughput information. These metrics are generated from a well-known non-rooted Android network monitoring application, G-NetTrack Pro. To the best of our knowledge, this is the first publicly available dataset that contains throughput, channel and context information for 5G networks. To supplement our real-time 5G production network dataset, we also provide a 5G large scale multi-cell ns-3 simulation framework. The availability of the 5G/mmwave module for the ns-3 mmwave network simulator provides an opportunity to improve our understanding of the dynamic reasoning for adaptive clients in 5G multi-cell wireless scenarios. The purpose of our framework is to provide additional information (such as competing metrics for users connected to the same cell), thus providing otherwise unavailable information about the basestation (eNodeB or eNB) environment and scheduling principle, to end user. Our framework permits other researchers to investigate this interaction through the generation of their own synthetic datasets.

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