QoS support in MANETs: a modular architecture based on the IEEE 802.11e technology
IEEE Transactions on Circuits and Systems for Video Technology
Video-aware opportunistic network coding over wireless networks
IEEE Journal on Selected Areas in Communications - Special issue on network coding for wireless communication networks
Content-aware distortion-fair video streaming in congested networks
IEEE Transactions on Multimedia - Special issue on quality-driven cross-layer design for multimedia communications
Application-centric routing for video streaming over multi-hop wireless networks
SECON'09 Proceedings of the 6th Annual IEEE communications society conference on Sensor, Mesh and Ad Hoc Communications and Networks
On-line learning and optimization for wireless video transmission
IEEE Transactions on Signal Processing
IEEE Journal on Selected Areas in Communications
Performance evaluation of video streaming over multi-hop wireless local area networks
IEEE Transactions on Wireless Communications
A distortion-minimizing rate controller for wireless multimedia sensor networks
Computer Communications
Cooperative coding and caching for streaming data in multihop wireless networks
EURASIP Journal on Wireless Communications and Networking - Special issue on multimedia communications over next generation wireless networks
LossEstimate: Distributed failure estimation in wireless networks
Journal of Systems and Software
Hi-index | 0.08 |
Emerging multi-hop wireless networks provide a low-cost and flexible infrastructure that can be simultaneously utilized by multiple users for a variety of applications, including delay-sensitive multimedia transmission. However, this wireless infrastructure is often unreliable and provides dynamically varying resources with only limited quality of service (QoS) support for multimedia applications. To cope with the time-varying QoS, existing algorithms often rely on non-scalable, flow-based optimizations to allocate the available network resources (paths and transmission opportunities) across the various multimedia users. Moreover, previous research seldom optimizes jointly the dynamic routing with the adaptation and protection techniques available at the medium access control (MAC) or physical (PHY) layers. In this paper, we propose a distributed packet-based cross-layer algorithm to maximize the decoded video quality of multiple users engaged in simultaneous real-time streaming sessions over the same multi-hop wireless network. Our algorithm explicitly considers packet-based distortion impact and delay constraints in assigning priorities to the various packets and then relies on priority queuing to drive the optimization of the various users' transmission strategies across the protocol layers as well as across the multi-hop network. The proposed solution is enabled by the scalable coding of the video content (i.e. users can transmit and consume video at different quality levels) and the cross-layer optimization strategies, which allow priority-based adaptation to varying channel conditions and available resources. The cross-layer strategies - application layer packet scheduling, the policy for choosing the relays, the MAC retransmission strategies, the PHY modulation and coding schemes - are optimized per packet, at each node, in a distributed manner. The main component of the proposed solution is a low-complexity, distributed, and dynamic routing algorithm, which- relies on prioritized queuing to select the path and time reservation for the various packets, while explicitly considering instantaneous channel conditions, queuing delays and the resulting interference. Our results demonstrate the merits and need for end-to-end cross-layer optimization in order to provide an efficient solution for real-time video transmission using existing protocols and infrastructures. Importantly, our proposed delay-driven, packet-based transmission is superior in terms of both network scalability and video quality performance to previous flow-based solutions that statically allocate resources based on predetermined paths and rate requirements. In addition, the results provide important insights that can guide the design of network infrastructures and streaming protocols for video streaming.