Video Activity-Based Traffic Policing: A New Paradigm

Abstract

The constant development of new multimedia applications, which are "greedy" in terms of bandwidth and Quality of Service (QoS) requirements, calls for new approaches to the traffic policing problem. This paper proposes, analyzes and presents an extensive performance evaluation of such a new approach, namely the activity-based video traffic policing. Using as a motivation recent work, which has shown that the classic traffic policing mechanisms provide unnecessarily strict policing for conforming but bursty video users, we propose five simple and efficient new mechanisms, which take into consideration and exploit video activity and the Group-of Pictures (GoP) pattern of the video traces. Contrary to the classic approach, our mechanisms do not use a token generator based on a fixed rate, but vary the token generation rate according to specific video activity-based algorithms. The results show significant improvement for conforming users, and reveal that dynamic traffic policing can provide much higher efficiency than the widely used static mechanisms. One of the new mechanisms, the Frame Size Aware Token Bucket, is shown to clearly outperform all other policing approaches for conforming users, and to provide comparable policing results with the classic mechanisms for non-conforming video users.

Efficient policing for screen mirroring traffic

“…As it will be shown in our results in "Results and discussion", our previously proposed mechanism, FSA-TB [26] confirms, for the first dataset of screen mirroring traffic, its excellence in comparison with all other mechanisms from the literature. However, for the second dataset it is impossible to be implemented as FSA-TB is based on the assumption of a standard GoP structure for the video.…”

“…In [26] we first evaluated five static traffic policing mechanisms from the literature. We then proposed a new paradigm in video traffic policing, which focuses on the activity of the source to dynamically tailor the traffic policing accordingly.…”

“…We compared the five static mechanisms against five new activity-based traffic policing mechanisms we proposed. Of those ten mechanisms, six (two static and four activity-based ones) were shown in [26] to provide the best traffic policing results. These were: (a) the token bucket (TB) mechanism, (b) the jumping window (JW) mechanism, (c) the variable exponentially weighted moving average (V-EWMA) mechanism, (d) the hybrid V-EWMA token bucket (VEWMA-TB), (e) the frame size aware token bucket (FSA-TB), (f ) the GOP modeling based jumping window (GMB-JW).…”

“…In our work in [26] we proposed a new traffic policing mechanism, the Frame Size Aware Token Bucket (FSA-TB), which was shown to outperform all of the widely used mechanisms in the literature. However, FSA-TB is based on the standard group of pictures (GoP) structure of a video and for this reason, as we will explain in "The Jaccard index-infused Markovian clustering policer (JIMC-P)" of the paper, it cannot be used for policing video encoded in a similar way to a Miracast hardware encoder.…”

Video Packet Scheduling With Stochastic QoS for Cognitive Heterogeneous Networks

“…This is because the spectral resource in cognitive wireless network is sparse and video traffic needs to consume more radio resource. Hence, different network resources at cognitive heterogeneous networks need to be aggregated to support the video traffic at secondary MT [12].…”