Please use this identifier to cite or link to this item: https://doi.org/10.1145/1291233.1291397
Title: Improving mobile ad-hoc streaming performance through adaptive layer selection with scalable video coding
Authors: Qin, M.
Zimmermann, R. 
Keywords: Link availability
Mobile ad-hoc networks
Mobility models
Scalable video coding
Streaming
Issue Date: 2007
Source: Qin, M.,Zimmermann, R. (2007). Improving mobile ad-hoc streaming performance through adaptive layer selection with scalable video coding. Proceedings of the ACM International Multimedia Conference and Exhibition : 717-726. ScholarBank@NUS Repository. https://doi.org/10.1145/1291233.1291397
Abstract: Numerous types of mobile devices are now popular with end users, who increasingly use them to carry multimedia content on the go. As wireless connectivity is integrated into many handheld devices, streaming multimedia content among mobile ad-hoc peers is becoming a popular application. In this paper, we first introduce a mathematical model for calculating the probability of successfully streaming a multimedia object between two mobile ad-hoc peers. Unlike previous techniques that assume a constant wireless bandwidth or fixed node location, our work supports the 802.11 Auto-Rate Fallback scheme along with two popular mobility models: the random waypoint and the random walk mobility model. When delivery of the whole video content is of crucial importance, we introduce a novel streaming strategy to improve the probability of successfully streaming a video sequence based on our proposed mathematical model. This strategy takes advantage of the Scalable Video Coding scheme to adaptively select the number of enhancement layers to be streamed to the receiver. Simulation results show that our strategy can improve the probability to stream a media object by a maximum of 60% while keeping the video quality relatively high. Copyright 2007 ACM.
Source Title: Proceedings of the ACM International Multimedia Conference and Exhibition
URI: http://scholarbank.nus.edu.sg/handle/10635/40279
ISBN: 9781595937025
DOI: 10.1145/1291233.1291397
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