Notice of Violation of IEEE Publication Principles: Group-Aware Delay-Constrained Video Transmission Over Multihomed Device-to-Device Networks

Notice of Violation of IEEE Publication Principles

"Group-Aware Delay-Constrained Video Transmission Over Multihomed Device-to-Device Networks"
by Junfei Huang and Zhaowen Lin,
in IEEE Access, Volume 5, 2017, pp 2651-2664

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles.

This paper is a duplication of the original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.

"Group-Aware Delay-Constrained Streaming in Wireless Device-to-Device Networks"
by Xiaoyi Zhang, Jiawei Liang, Jiyan Wu, and Lin Zhang,
in the ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM). Submitted December 26, 2016


The technological advancements in wireless communication systems enable mobile users to leverage different radio interfaces (e.g., cellular and WiFi) for concurrent data transmission. However, the existing transmission schemes do not seriously consider the problem of real-time video multicast to a cluster of co-located multihomed mobile devices. Conventionally, each client fetches the video streaming to the best of its capability, and this results in competing resources that degrade user-perceived video quality. Several literatures investigated the problem of using cellular to obtain video contents from the remote server and sharing them through WiFi. However, the stringent delay constraint of real-time video is not addressed in these solutions. In this paper, a cooperative transmission scheme is proposed to tackle the problem. First, a mathematical framework dubbed (Group-Aware Delay-COnstraint) is developed to formulate the delay-constrained goodput maximization problem of real-time video transmission to a group of multihomed mobiles. Second, a dataflow distribution mechanism is presented to conserve the cellular bandwidth and maximize user experience. Then, a prototype is implemented on the Android platform involving real-time video encoded with H.264 codec. Experimental results show that the proposed scheme achieves appreciable improvements over the reference schemes in video peak signal-to-noise ratio, end-to-end delay, and goodput.