Distributed Source Coding for Interactive Function Computation
نویسندگان
چکیده
In networked systems where distributed inferencing and control needs to be performed, the raw-data generated at different nodes needs to be transformed and combined in a number of ways to extract actionable information. This requires performing distributed computations on the rawdata. A pure data-transfer solution approach would advocate first reliably reproducing the rawdata at decision-making nodes and then performing suitable computations to extract actionable information. Two-way interaction and statistical dependencies among source, destination, and relay nodes, would be utilized, if at all, to primarily improve the reliability of data-reproduction than overall computation-efficiency. However, to maximize the overall computation-efficiency, it is necessary for nodes to interact bidirectionally, perform computations, and exploit statistical dependencies in data as opposed to only generating, receiving, and forwarding data. In this talk we will explore this common wisdom through some examples of distributed function-computation with the goal of minimizing the total number of bits transferred per unit time. We will highlight the role of interaction in computation-efficiency within a distributed source coding setting involving block-coding asymptotics and vanishing probability of function-computation error. We will discuss informationtheoretic characterizations of the set of feasible coding-rates for these problems and explore the fascinating interplay of function-structure, distribution-structure, and interaction.
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