Adaptive and Network-Aware Source Coding

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The goal of source coding (data compression) is to give a compact representation of data (e.g., text, image, audio, video, and other, non-traditional data types such as graphical data) from which the original data can be reconstructed either perfectly or in a perceptually acceptable manner. With the proliferation of large data sets in our society and the coming of the big data revolution, source coding has become a key component in contemporary information technologies as it facilitates the efficient storage and remote access of large volumes of data, as well as the efficient transmission of information-bearing signals over communication channels such as the Internet or wireless networks. The proposed research will focus on designing and analyzing novel source coding methods that meet the challenges posed by contemporary settings in which several users, connected via multiple links of different capacities, want to communicate or store data that may not be stationary and/or well structured. New and substantial research challenges arise in the analysis and design of schemes that adapt to changing source statistics and incorporate practical constraints on memory, complexity, and delay, contrasting the more established traditional theory of source coding where such constraints are usually disregarded. ******The research objectives are divided into two main themes: (1) The systematic study of the performance and finer structure of optimal zero- or limited-delay codes for information sources in the single user and distributed settings as well as for two-way networks; (2) The investigation of the rich connections between data compression and online learning/distributed optimization to facilitate the construction and analysis of low-complexity, adaptive sequential schemes for lossy coding of highly non-stationary sources in distributed settings, such as coding for sensor networks. ******The training component of the proposed research will provide 2 M.Sc. and 3 Ph.D. students each year with stimulating research challenges and immerse them in important current topics in information and communication technologies. The research is expected to provide a deeper understanding of the fundamental principles of lossy source coding as well as its practical aspects, such as the transmission of multimedia signals in communication networks.