Radio Link Buffer Management and Scheduling for Wireless Video Streaming

Liebl, G.; Jenkac, H.; Stockhammer, Thomas; Buchner, C.

doi:10.1007/s11235-005-4328-x

Cited by 29 publications

(27 citation statements)

References 11 publications

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“…For instance in [21,22], the concept of incrementally additive distortion is used to determine the importance of video packets for each user's precoded non-scalable video stream. Essentially, the increase in distortion due to the loss of a video packet is a function of all the other video packets that are dependent on it and cannot be decoded if it is not sent.…”

Section: Content-aware Scheduling and Resource Allocation At The Enodebmentioning

confidence: 99%

QoE-driven multi-user scheduling and rate adaptation with reduced cross-layer signaling for scalable video streaming over LTE wireless systems

Khan

Martini

2016

J Wireless Com Network

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The scarcity of the available radio spectrum coupled with the growing popularity of bandwidth intensive mobile video applications poses a huge challenge to network operators. The solution of over-provisioning the network is not economical; hence, an appropriate strategy for scheduling and resource allocation among the users in the system is of crucial importance. This work focuses on scheduling multiple video flows on the downlink of a wireless system based on orthogonal frequency division multiple access (OFDMA), such as Long-Term Evolution (LTE) and LTE-A (LTE-Advanced) standards. We propose a joint multi-user scheduling and multi-user rate adaptation strategy providing an appropriate trade-off between efficiency and fairness, while ensuring high quality of experience (QoE) for the end users. We consider Scalable Video Coding (SVC) which facilitates the truncation of bit streams, thus allowing graceful degradation of video quality in the event of wireless channel variations or network congestion. The proposed scheduler utilizes QoE-aware priority marking, where video layers are mapped to priority classes and targets at minimizing delay bound violations for the most important priority classes under congestion. In order to reduce congestion, we propose multi-user rate adaptation at the MAC layer via a novel dynamic filtering policy for QoE-based priority classes. Simulation results show that the proposed approach delivers to the end users a similar QoE as delivered by the stateof-the-art cross-layer approaches, where extensive cross-layer signaling, additional video rate adaptation modules at the core network, and frequent link probing from the wireless access network to the rate adaptation modules are required. The latter approaches are not implemented in real systems due to the aforementioned drawbacks, while our approach can be implemented without major modifications in the standard behavior of existing networks and equipment. The proposed framework can deliver delay-sensitive traffic as well as delay-tolerant best-effort traffic.

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Section: Content-aware Scheduling and Resource Allocation At The Enodebmentioning

confidence: 99%

QoE-driven multi-user scheduling and rate adaptation with reduced cross-layer signaling for scalable video streaming over LTE wireless systems

Khan

Martini

2016

J Wireless Com Network

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“…This proposed cross-layer algorithm has the objective of maximizing the overall video qualities among all users by guaranteeing that the delay constraint and fairness constraints are satisfied. The authors in [20] proposed a drop-based scheduling strategy at the radio link buffer in which they used the side-information of the temporal dependency structure in the scheduled video streams.…”

Section: Related Workmentioning

confidence: 99%

A Channel-Aware and Occupancy-Dependent Scheduler for Video Transmission over Wireless Channels

Hassan¹,

Landolsi²,

Mukhtar³

2010

IJCNC

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In this paper, we propose an adaptive and fair priority scheduler for video streaming over wireless links. The proposed scheme selects the client to be served based on the instantaneous occupancy of the decoder buffers of the wireless clients as well as the quality of the channel as seen by these clients in addition to the sensitivity of scheduled video frames. Unlike conventional scheduling algorithms, the proposed scheme accounts for the characteristics and strict requirements of multimedia applications with considerably low computational complexity. When compared to other commonly-used scheduling algorithms, the proposed algorithm achieves better performance in terms of the individual and average buffer occupancies of the decoder buffers of the wireless clients as well as the end-to-end delay experienced by the video frames. Simulations are carried out to study the interactions among the key parameters of the proposed scheduling algorithm.

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“…In [16], the potential benefits of using SVC in mobile networks are described and several uses in mobile broadcast, multicast, and unicast networks that could benefit from SVC are discussed. Strategies for dynamic sharing of radio links in a multi-user streaming network is proposed in [10]. The authors combine SVC with radio link buffer management strategies and try to maximize the video quality of the transmitted video streams by dropping the packets in a way that does not violate temporal scalability.…”

Section: Related Workmentioning

confidence: 99%

Optimal scalable video multiplexing in mobile broadcast networks

Tabrizi¹,

Hsu²,

Hefeeda³

et al. 2010

Proceedings of the 3rd Workshop on Mobile Video Delivery - MoViD '10

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We study the problem of broadcasting multiple variable bit rate scalable video streams from a base station to a large number of mobile receivers. Our objective is to maximize bandwidth utilization, energy saving and perceived quality of the transmitted videos. In practice, the aggregate bitrate of the video streams can be greater than the available bandwidth and then the receivers may experience playout glitches. We propose an algorithm to take advantage of opportunities provided by scalable video coding to improve performance when the bandwidth is limited. To achieve this, we provide a model for prioritizing video packets coded in medium grain scalability and a decision mechanism to drop quality layers of video frames when the bandwidth is limited. The result is increased bandwidth utilization and quality of the transmitted videos. Our experiments, performed on a real mobile TV testbed, show that our algorithm significantly out-performs current methods in terms of bandwidth utilization and also achieves near optimal energy saving and quality of the transmitted video streams.

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Radio Link Buffer Management and Scheduling for Wireless Video Streaming

Cited by 29 publications

References 11 publications

QoE-driven multi-user scheduling and rate adaptation with reduced cross-layer signaling for scalable video streaming over LTE wireless systems

QoE-driven multi-user scheduling and rate adaptation with reduced cross-layer signaling for scalable video streaming over LTE wireless systems

A Channel-Aware and Occupancy-Dependent Scheduler for Video Transmission over Wireless Channels

Optimal scalable video multiplexing in mobile broadcast networks

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