Universal lossless coding with random user access: The cost of interactivity

Roumy, Aline; Maugey, Thomas

doi:10.1109/icip.2015.7351125

Cited by 14 publications

(30 citation statements)

References 15 publications

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“…In [24], [25], we have shown that when compressing one single source with several potential side informations available at the decoder, it is possible to use incremental coding in order to only send the necessary amount of bits. Based on the graph-based client's navigation formalism and the transmission/storage costs proposed in Sec.…”

Section: Incremental Coding Based Extractable Compression (Ibec) mentioning

confidence: 99%

Incremental Coding for Extractable Compression in the Context of Massive Random Access

Maugey

Roumy

Dupraz

et al. 2020

IEEE Trans. on Signal and Inf. Process. over Networks

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In this paper, we study the problem of source coding with Massive Random Access (MRA). A set of correlated sources is encoded once for all and stored on a server while a large number of clients access various subsets of these sources. Due to the number of concurrent requests, the server is only able to extract a bitstream from the stored data: no re-encoding can be performed before the transmission of the data requested by the clients.First, we formally define the MRA framework and propose to model the constraints on the way subsets of sources may be accessed by a navigation graph. We introduce both storage and transmission costs to characterize the performance of MRA. We then propose an Incremental coding Based Extractable Compression (IBEC) scheme. We first show that this scheme is optimal in terms of achievable storage and transmission costs. Second, we propose a practical implementation of our IBEC scheme based on rate-compatible LDPC codes. Experimental results show that our IBEC scheme can almost reach the same transmission costs as in traditional point-to-point source coding schemes, while having a reasonable overhead in terms of storage cost.

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Section: Incremental Coding Based Extractable Compression (Ibec) mentioning

confidence: 99%

Incremental Coding for Extractable Compression in the Context of Massive Random Access

Maugey

Roumy

Dupraz

et al. 2020

IEEE Trans. on Signal and Inf. Process. over Networks

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“…Then, by comparing (4) and (5), we observe that there is the same relation between the protographs S 1 , S 2 , and between the parity check matrices H 1 , H 2 . Further, according to (5), the problem of finding a good protograph S 2 for H 2 can be reduced to finding the intermediate protograph S 1→2 that maximizes the threshold of S 2 .…”

Section: B Rate Adaptive Conditionmentioning

confidence: 99%

Optimized Rate-Adaptive Protograph-Based LDPC Codes for Source Coding With Side Information

Dupraz

Mheich

et al. 2019

IEEE Trans. Commun.

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This paper considers the problem of source coding with side information at the decoder, also called Slepian-Wolf source coding scheme. In practical applications of this coding scheme, the statistical relation between the source and the side information can vary from one data transmission to another, and there is a need to adapt the coding rate depending on the current statistical relation. In this paper, we propose a novel rate-adaptive code construction based on LDPC codes for the Slepian-Wolf source coding scheme. The proposed code design method allows to optimize the code degree distributions at all the considered rates, while minimizing the amount of short cycles in the parity check matrices at all rates. Simulation results show that the proposed method greatly reduces the source coding rate compared to the standard LDPCA solution.

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“…This correction can not be done using classical predictive (P-frame) approach, since user's navigation is random from the server's point of view. However, the proofs in [5,6] suggest an alternative approach: model-based coding.…”

Section: Model-based Coding In Interactive Communicationmentioning

confidence: 99%

“…Recently [5,6] proposed an optimistic results for IVC. They derived the information theoretic bounds and showed that interactivity incurs loss in a priori storage only and not in the transmission rate, i.e.…”

Section: Introductionmentioning

confidence: 99%

“…we have to store the data corresponding to the worst user navigation but, after its actual request, one sends him only what is needed [7]. Based on the results obtained in [5], interactivity can be seen as a problem of source coding with Side Information (SI). As a result, unlike predictive coding, in which the residuals within frames are This work was partially supported by the Cominlabs excellence laboratory with funding from the French National Research Agency (ANR-10-LABX-07-01) and by the Brittany Region (Grant No.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Correlation model selection for interactive video communication

Bidgoli

Maugey

Roumy

2017

2017 IEEE International Conference on Image Processing (ICIP)

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Interactive video communication has been recently proposed for multi-view videos. In this scheme, the server has to store the views as compact as possible, while being able to transmit them independently to the users, who are allowed to navigate interactively among the views, hence requesting a subset of them. To achieve this goal, the compression must be done using a model-based coding in which the correlation between the predicted view generated on the user side and the original view has to be modeled by a statistical distribution. In this paper we propose a framework for lossless fixed-length source coding to select a model among a candidate set of models that incurs the lowest extra rate cost to the system. Moreover, in cases where the depth image is available, we provide a method to estimate the correlation model.

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Universal lossless coding with random user access: The cost of interactivity

Cited by 14 publications

References 15 publications

Incremental Coding for Extractable Compression in the Context of Massive Random Access

Incremental Coding for Extractable Compression in the Context of Massive Random Access

Optimized Rate-Adaptive Protograph-Based LDPC Codes for Source Coding With Side Information

Correlation model selection for interactive video communication

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