EMS: Encoded Multipath Streaming for real-time live streaming applications

Chow, Alix L. H.; Yang, Hao; Xia, Cathy H.; Kim, Minkyong; Liu, Zhen; Liu, Hui

doi:10.1109/icnp.2009.5339681

Cited by 32 publications

(46 citation statements)

References 16 publications

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“…A new convex optimization problem is formulated with the utility function of RT users replaced by (7). Lagrangian function of this problem is given as:…”

Section: Solution To the Optimization Problem And Call Admission Cmentioning

confidence: 99%

“…A few works [2], [4]- [7] have been reported recently on data transmission over heterogeneous network with multihomed users. In [6], the authors considered the problem of rate allocation across multiple streams.…”

Section: Introductionmentioning

confidence: 99%

“…An end-to-end virtual path is constructed in [2] for stable live video streaming over heterogeneous networks. The authors in [7] proposed an encoded multipath scheme for live RT-streaming applications.…”

Section: Introductionmentioning

confidence: 99%

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Cognitive Multihoming: Maximizing Network Utility over CR-Assisted Cellular Network

Agarwal

Seo

2015

2015 IEEE Globecom Workshops (GC Wkshps)

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Demand for wireless data bandwidth has been increasing explosively so that the present licensed cellular networks (LCNs) themselves are no longer competent to provide high quality service to the users at a reasonable cost. In this paper, we propose a cost-effective system, called cognitive multihoming (CM), that enables high quality service and at the same time incurs low cost. The proposed system considers a cellular base station with added cognitive radio (CR) functionality. The heterogeneous resources are organized into a single centrally-managed virtual system to allocate the heterogeneous users with varying quality and cost constraints. Multiple multihoming-capable heterogeneous users request downlink unicast data from the system. Transmissions to these users are performed simultaneously via LCN and CR network (CRN). This cooperative approach aids lowering service cost to the users. The possibility of loss in quality of service is mitigated by optimally distributing the traffic load between LCN and CRN, based on the users' rate requirements. To evaluate the CM performance we consider a benchmark system with the same total channel resource from LCN and CRN, where a user is served via either LCN or CRN depending on the users quality and cost preferences. Numerical results show that, on average the network utility of the proposed system is nearly 17% higher than the benchmark.

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“…A new convex optimization problem is formulated with the utility function of RT users replaced by (7). Lagrangian function of this problem is given as:…”

Section: Solution To the Optimization Problem And Call Admission Cmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cognitive Multihoming: Maximizing Network Utility over CR-Assisted Cellular Network

Agarwal

Seo

2015

2015 IEEE Globecom Workshops (GC Wkshps)

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show abstract

“…Let (n − k)/k denote the redundancy (i.e., the fraction of redundant FEC packets in the FEC block). There is an inherent tradeoff between FEC redundancy and its error correction power [29]. With more redundant packets, the receiver can recover from more severe losses, at the cost of larger end-to-end delays and higher loads imposed on networks.…”

Section: Fec Redundancy Estimationmentioning

confidence: 99%

“…Besides, encoded multi-path streaming (EMS) [29] and multi-path loss tolerant (MPLOT) [30] are typical protocols exploiting path diversity in wired/wireless multi-path networks based on erasure code. EMS scheme splits traffic loads over multiple paths according to the path loss rate and dynamically adjusts FEC redundancy.…”

Section: Video Delivery In Heterogeneous Wireless Networkmentioning

confidence: 99%

Joint source-channel coding and optimization for mobile video streaming in heterogeneous wireless networks

Shang

Huang

et al. 2013

J Wireless Com Network

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This paper investigates mobile video delivery in a heterogeneous wireless network from a video server to a multi-homed client. Joint source-channel coding (JSCC) has proven to be an effective solution for video transmission over bandwidth-limited, error-prone wireless networks. However, one major problem with the existing JSCC approaches is that they consider the network between the server and the client as a single transport link. The situation becomes more complicated in the context of multiple available links because involving a low-bandwidth, highly lossy, or long-delay wireless network in the transmission will only degrade the video quality. To address the critical problem, we propose a novel flow rate allocation-based JSCC (FRA-JSCC) approach that includes three key phases: (1) forward error correction redundancy estimation under loss requirement, (2) source rate adaption under delay constraint, and (3) dynamic rate allocation to minimize end-to-end video distortion. We present a mathematical formulation of JSCC to optimize video quality over multiple wireless channels and provide comprehensive analysis for channel distortion. We evaluate the performance of FRA-JSCC through emulations in Exata and compare it with the existing schemes. Experimental results show that FRA-JSCC outperforms the competing models in improving the video peak signal-to-noise ratio as well as in reducing the end-to-end delay.

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Robust bandwidth aggregation for real-time video delivery in integrated heterogeneous wireless networks

Shang

Qiao

et al. 2013

Multimed Tools Appl

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EMS: Encoded Multipath Streaming for real-time live streaming applications

Cited by 32 publications

References 16 publications

Cognitive Multihoming: Maximizing Network Utility over CR-Assisted Cellular Network

Cognitive Multihoming: Maximizing Network Utility over CR-Assisted Cellular Network

Joint source-channel coding and optimization for mobile video streaming in heterogeneous wireless networks

Robust bandwidth aggregation for real-time video delivery in integrated heterogeneous wireless networks

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