On optimum communication cost for joint compression and dispersive information routing

2011 IEEE International Symposium on Information Theory Proceedings

Rose

2011

Self Cite

Abstract-This paper considers the problem of optimal multihop routing of correlated sources over a network with multiple sinks and arbitrary network demands. We recently introduced a new routing paradigm in [10] called 'dispersive information routing' (DIR), wherein the intermediate nodes are allowed to split a packet and forward a subset of the received bits on each forward path. DIR ensures that each sink receives just the information it requires to decode the sources it intends to reconstruct, and thereby outperforms conventional routing techniques in the literature. We proposed an encoding scheme called 'power binning' which achieves complete rate region and the minimum cost under this paradigm when each sink is allowed to receive packets only from the sources it wants to reconstruct. This paper considers the optimum encoding scheme when every source can (possibly) communicate with every sink irrespective of what the sinks reconstruct. This generalization happens to be considerably more complex and we derive an achievable rate region and an associated achievable cost using principles from distributed source coding and multiple descriptions encoding.

Section: Introductionmentioning

confidence: 99%

“…In a precursor work [10], we introduced a new routing paradigm called 'dispersive information routing' (DIR), wherein the intermediate nodes are allowed to 'split' a packet and forward different subsets of the packets on each forward path. It was demonstrated using simple examples that DIR outperforms broadcasting for multi-sink networks.…”

Section: Introductionmentioning

confidence: 99%

An achievable rate region for distributed source coding and dispersive information routing

Viswanatha

2011 IEEE International Symposium on Information Theory Proceedings

Rose

2011

Self Cite

“…However, it is worthwhile to question this assumption in today's network scenario wherein an intermediate node forwards packets to multiple receivers (see [13] for the potential benefits of such considerations in general networked source coding problems). The SISC problem setting demonstrates the validity of this proposition: the classical scalable compression clearly requires the transmission of redundant information to receivers.…”

Section: A New Interpretation Of Networked Scalable Codingmentioning

confidence: 99%

On scalable coding in the presence of decoder side information

2014 IEEE International Symposium on Information Theory

Mitra

Tuncel

et al. 2014

Self Cite

Abstract-The problem of scalable coding while exploiting the decoder side information is considered. Prior work considered the two important cases concerning the degraded side information where source X and the side information variables (Y1, Y2) form a Markov chain in the order of either X −Y1 −Y2 or X −Y2 −Y1. While the encoding schemes for these settings differ considerably, they are both based on the combination of conditional codebook encoding, a standard tool in scalable coding, and random binning, conventionally used in decoder side information problems. In this paper, an encoding scheme is proposed solely on the basis of random binning, which essentially performs scalable and WynerZiv coding simultaneously. Proposed scheme achieves the ratedistortion regions of prior results. A practical advantage of the unifying scheme is the fact that random binning can be realized via practical tools such as nested lattice codes and channel codes. Finally, motivated by the proposed encoding scheme, a network interpretation of scalable coding is considered. An achievable region is derived for this problem setting and the potential benefits of networked scalable coding are shown.

“…We derive an achievable rate-distortion region for the CMS scheme and show that it subsumes the achievable region due to VKG in [3]. We note that the underlying principle behind CMS has been shown in precursor work to be useful in related applicational contexts of routing for networks with correlated sources [10] and data storage for selective retrieval [11].…”

Section: Introductionmentioning

confidence: 99%

“…Let α W (Q) and β(S) be defined as in (9) and (10). Let R K ∀K ∈ J (L) and R l ∀l ∈ L be any set of rate tuples satisfying:…”

Section: B L−channel Casementioning

confidence: 99%

Combinatorial Message Sharing for a refined multiple descriptions achievable region

Viswanatha

2011 IEEE International Symposium on Information Theory Proceedings

Rose

2011

Self Cite

Abstract-This paper presents a new achievable rate-distortion region for the L-channel multiple descriptions problem. Currently, the most popular region for this problem is due to Venkataramani, Kramer and Goyal [3]. Their encoding scheme is an extension of the Zhang-Berger scheme to the L-channel case and includes a combinatorial number of refinement codebooks, one for each subset of the descriptions. All the descriptions also share a single common codeword, which introduces redundancy, but assists in better coordination of the descriptions. This paper proposes a novel encoding technique involving 'Combinatorial Message Sharing', where every subset of the descriptions may share a distinct common message. This introduces a combinatorial number of shared codebooks along with the refinement codebooks of [3]. These shared codebooks provide a more flexible framework to trade off redundancy across the messages for resilience to descriptions loss. We derive an achievable ratedistortion region for the proposed technique, and show that it subsumes the achievable region of [3].