Informed-Source Coding-on-Demand (ISCOD) over Broadcast Channels

We present the Informed-Source Coding-On-Demand (ISCOD) approach for efficiently supplying non-identical data from a central server to multiple caching clients through a broadcast channel. The key idea underlying ISCOD is the joint exploitation of the data already cached by each client, the server’s full awareness of client-cache contents and client requests, and the fact that each client only needs to be able to derive the items requested by it rather than all the items ever transmitted or even the union of the items requested by the different clients. We present a set of two-phase ISCOD algorithms. The server uses these algorithms to assemble ad-hoc error-correction sets based its knowledge of every client’s cache content and of the items requested by it; next, it uses error-correction codes to construct the data that is actually transmitted. Each client uses its cached data and the received supplemental data to derive the items that it has requested. This technique achieves a reduction of up to tens of percents in the amount of data that must be transmitted in order for every client to be able to derive the data requested by it. Finally, we define k-partial cliques in a directed graph, and cast the two-phase approach in terms of partial-clique covers. As a byproduct of this work, bounds and a close approximation for the expected cardinality of the maximum matching in a random graph have been derived and are outlined.