Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: ELASTIC: A Client-Side Controller for Dynamic Adaptive Streaming over HTTP (DASH)
What happens when HTTP adaptive streaming players compete for bandwidth?
Client-Driven Network-level QoE fairness for Encrypted 'DASH-S'
Avoiding Quality Bottlenecks in P2P Adaptive Streaming
An HTTP/2-Based Adaptive Streaming Framework for 360° Virtual Reality Videos
Cost effective video streaming using server push over HTTP 2.0
Delivering stable high-quality video: an SDN architecture with DASH assisting network elements
Subjective and Objective Quality-of-Experience of Adaptive Video Streaming
Proxy Caching Mechanisms with Quality Adjustment for Video Streaming Services
Proxy Caching Mechanism for Multimedia Playback Streams in the Internet
Online learning adaptation strategy for DASH clients
TFDASH: A Fairness, Stability, and Efficiency Aware Rate Control Approach for Multiple Clients Over DASH
Modelling the impact of caching and popularity on concurrent adaptive multimedia streams in Information-Centric Networks
ElastiCon: an elastic distributed sdn controller
Adaptive bitrate video delivery using HTTP/2 over MPTCP architecture
A longitudinal view of HTTP video streaming performance
Performance Evaluation of Video Streaming Using MPEG DASH, RTSP, and RTMP in Mobile Networks
A buffer-based approach to rate adaptation: evidence from a large video streaming service
Is Multipath TCP (MPTCP) Beneficial for Video Streaming over DASH?
Characterizing roles of front-end servers in end-to-end performance of dynamic content distribution
Cache-Friendly Streaming Bitrate Adaptation by Congestion Feedback in ICN
Tensor Spectral Clustering for Partitioning Higher-order Network Structures
Watching Video over the Web: Part 1: Streaming Protocols
Moderate alcohol intake and lower risk of coronary heart disease: meta-analysis of effects on lipids and haemostatic factors.
An ambidextrous perspective on business intelligence and analytics support in decision processes: Insights from a multiple case study
Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks