We consider the distributed source coding problem in which correlated data picked up by scattered sensors has to be encoded separately and transmitted to a common receiver, subject to a rate-distortion constraint. Although near-to-optimal solutions based on Turbo and LDPC codes exist for this problem, in most cases the proposed techniques do not scale to networks of hundreds of sensors. We present a scalable solution based on the following key elements: (a) distortion-optimized index assignments for low-complexity distributed quantization, (b) source-optimized hierarchical clustering based on the Kullback-Leibler distance and (c) sum-product decoding on specific factor graphs exploiting the correlation of the data.

Abstract-When correlated sources are to be communicated over a network to more than one sink, joint source-network coding is, in general, required for information theoretically optimal transmission. Whereas on the encoder side simple randomized schemes based on linear codes suffice, the decoder is required to perform joint source-network decoding which is computationally expensive. Focusing on maximum a-posteriori decoders (or, in the case of continuous sources, conditional mean estimators), we show how to exploit (structural) knowledge about the network topology as well as the source correlations giving rise to an efficient decoder implementation (in some cases even with linear dependency on the number of nodes). In particular, we show how to statistically represent the overall system (including the packets) by a factor-graph on which the sum-product algorithm can be run. A proof-of-concept is provided in the form of a working decoder for the case of three sources and two sinks.

Recent experimental works have demonstrated the feasibility of the visible light based vehicular communications (VVLC) in intelligent transportation systems (ITS). However, in many respects, this technology is in its infancy and requires further research efforts in several areas. This work presents a flexible network architecture named flexible light (Flight), which is designed for VLC to tackle existing mobility challenges in the network environment. Flight proposes a low-latency handover system that decreases the handover delays to a few tens and hundreds of milliseconds. By means of experiments, we emulate and evaluate indoor mobile network scenarios using only VLC technology.