Unequal-Protected LT Code for Layered Video Streaming

Chang, Sheng-Yuan; Yang, Kai-Chao; Wang, Jia-Shung

doi:10.1109/icc.2008.99

Cited by 18 publications

(8 citation statements)

References 6 publications

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“…The general idea is to virtually extend the block length K so as to reduce the overhead ε. In [9], the authors introduced an error correction code adopted a binarytree-like structure rather than randomly selected bipartite graph as the coding graph. Nevertheless, the encoding redundancy is high, and the degree distribution does not meet Soliton Distribution.…”

Section: Introductionmentioning

confidence: 99%

Service-Driven Approximate LT Codes

Yang¹,

Lin

et al. 2010

2010 IEEE International Conference on Communications

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Luby Transform (LT) codes are becoming increasingly important in transmission due to the ability to protect the source data in high reliability economically. LT codes generate rateless packets on-the-fly through randomly chosen encoding degree, so it cannot control or manage the service quality according to distinct service demands of clients. In this article, we extended LT codes with a service-driven control policy. The proposed encoder arranges the encoding degree through the basic building structures via various control policies to fulfill the requests of majority of clients. With the proposed control policies in the multicasting or broadcasting channel, source data of most clients can be recovered as soon as possible. Besides, comparing to LT codes in point-to-point protocol, the proposed codes also introduce lower decoding overhead, better intermediate performance, and built-in unequal error protection property through appropriately arranging the placements of source data in the coding graph.

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Section: Introductionmentioning

confidence: 99%

Service-Driven Approximate LT Codes

Yang¹,

Lin

et al. 2010

2010 IEEE International Conference on Communications

Self Cite

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“…However, it is hard to dynamically adjust redundancy in these methods because of their complex calculation. On the other hand, the rateless code methods based on UEP are proposed in [8], [9], [10], [11], [12]. Rateless code generates arbitrary number of encoded symbols from source symbols (original data).…”

Section: Introductionmentioning

confidence: 99%

ECLIPSE: Error Correction based on Loss probability and data Importance for Plural Server Environment

Fujimoto¹,

Hirota²,

Tode³

et al. 2012

JCM

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Video streaming technique is widely used in the Internet with the development of access networks. Although some techniques such as Forward Error Correction or Content Distribution Network are effective for video streaming services, they are not sufficient in the case that streams are suffered from heavy packet loss. For this problem, we propose a novel error correction method called “ECLIPSE: Error Correction based on Loss probability and data Importance for Plural Server Environment”. The ECLIPSE recovers lost packets with a parity stream which exploits multiple streams. In order to improve video quality, ECLIPSE gives priority to each data of multiple streams in terms of recovery from packet losses. It is designed for recovering important data with higher probability. The priority of each data is set based on two criteria. The one is the inherent importance of the data within one stream. The other is the loss probability of one stream which is compared with the loss probabilities of other streams. We also clarify the performance of the proposed method through theoretical analysis. Moreover, we focus on the creation method of redundant data. They are transferred from another server for multiple worse conditioned streams, which greatly affects the recovery capability. We propose the adaptive creation method for various network conditions.<br />Our simulation results show that the ECLIPSE can recover more important data with higher probability. Furthermore, it can also achieve almost the same restoration ratio among streams of recovery targets which have different loss probabilities

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“…Another method in [10] changes the degree distribution in order to encode the layered stream data together with UEP ability, but it decreases the decoding efficiency resulting in a larger overhead. In [11], hierarchical coding graphs are proposed to obtain different decoding paths for layered encoded symbol, but the overhead is still high due to a fixed structure of the coding graph.…”

Section: Introductionmentioning

confidence: 99%