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Enabling intermediate nodes in networks with the capability of storing the past communication can offer several benefits. Recently, the authors have shown that by utilizing memory at intermediate nodes, one can compress the data stream sent from the source node with superior performance compared to the conventional end-to-end compression of individual sequences destined to each client. In other words, memorization or learning of past traffic at intermediate nodes provide extra compression gain. This gain comes from the fact that utilizing previous traffic shared between the source and intermediate nodes with memory helps to close the gap between the compression performance of universal compression techniques and entropy of each individual sequence.
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