  This paper introduces a new source coding paradigm called Sequential Massive
Random Access (SMRA). In SMRA, a set of correlated sources is encoded once for
all and stored on a server, and clients want to successively access to only a
subset of the sources. Since the number of simultaneous clients can be huge,
the server is only allowed to extract a bitstream from the stored data: no
re-encoding can be performed before the transmission of the specific client's
request. In this paper, we formally define the SMRA framework and introduce
both storage and transmission rates to characterize the performance of SMRA. We
derive achievable transmission and storage rates for lossless source coding of
i.i.d. and non i.i.d. sources, and transmission and storage rates-distortion
regions for Gaussian sources. We also show two practical implementations of
SMRA systems based on rate-compatible LDPC codes. Both theoretical and
experimental results demonstrate that SMRA systems can reach the same
transmission rates as in traditional point to point source coding schemes,
while having a reasonable overhead in terms of storage rate. These results
constitute a breakthrough for many recent data transmission applications in
which different parts of the data are requested by the clients.
