Adaptive Video Streaming Using Dynamic NDN Multicast in WLAN | IEEE Conference Publication | IEEE Xplore

Adaptive Video Streaming Using Dynamic NDN Multicast in WLAN


Abstract:

Video streaming takes a dominant role for rapidly-increasing mobile Internet traffic in Wireless Local Area Networks (WLAN). As consumers often request the same contents,...Show More

Abstract:

Video streaming takes a dominant role for rapidly-increasing mobile Internet traffic in Wireless Local Area Networks (WLAN). As consumers often request the same contents, such as popular videos and live videos, using multicast transmissions under Named Data Networking (NDN) architecture can significantly reduce the network cost. However, to guarantee the transmission reliability for wireless multicast, the existing multicast schemes generally adopt the lowest data rate (e.g., 1 Mbps for IEEE 802.11b, and 6 Mbps for IEEE 802.11a) to transmit the multicast data, inevitably reducing the best quality of experience (QoE) for those high-speed consumers. In this paper, under the Scalable Video Coding (SVC) mechanism, we propose an adaptive video streaming scheme by using the NDN multicast (named NM-ABR), where NDN multicast groups are dynamically formed according to the network conditions and SVC characteristics. In NM-ABR, after detecting a multicast group, we first devise a multicast data rate selection algorithm in order to maximize the receiving throughput of consumers within the group. Then, we integrate the transmission data rate into the adaptive bit rate (ABR) algorithm to request for video segments with the most suitable bitrate. At last, for those low-speed consumers, we propose an SVC-based multiple-layer control approach to reduce the retransmission of video segments in enhancement layers. We implement the proposed NM-ABR in NS-3 via the ndnSIM module, and conduct extensive experiments to demonstrate its efficacy in terms of video bitrate, startup delay, and stalling time.
Date of Conference: 06-09 July 2020
Date Added to IEEE Xplore: 10 August 2020
ISBN Information:
Conference Location: Toronto, ON, Canada

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