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.

中文翻译：

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大规模随机访问背景下可提取压缩的增量编码


在本文中，我们研究了大规模随机访问（MRA）的源编码问题。一组相关源被一次性编码并存储在服务器上，同时大量客户端访问这些源的各个子集。由于并发请求的数量，服务器只能从存储的数据中提取比特流：在传输客户端请求的数据之前不能执行重新编码。首先，我们正式定义 MRA 框架，并建议对导航图访问源子集的方式的约束进行建模。我们引入存储和传输成本来表征 MRA 的性能。然后，我们提出了一种基于增量编码的可提取压缩（IBEC）方案。我们首先证明该方案在可实现的存储和传输成本方面是最优的。其次，我们提出了基于速率兼容 LDPC 码的 IBEC 方案的实际实现。实验结果表明，我们的IBEC方案几乎可以达到与传统点对点源编码方案相同的传输成本，同时在存储成本方面具有合理的开销。