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Random linear network coding (RLNC) has the potential to improve the performance of current and future Internet of Things (IoT) communication systems, but is computationally demanding due to matrix multiplications and inversions. Some single-core RLNC implementations achieve already sufficient coding speeds for contemporary multimedia streaming formats. However, advances in multimedia streaming formats...
Random linear network coding (RLNC) is attractive for data transfer as well as data storage and retrieval in complex and unreliable settings. The existing systematic RLNC approach first sends all source symbols in a generation without encoding followed by the coded redundant packets at the tail of the generation. This systematic tail RLNC achieves low delay when packet drops are rare; however, recovery...
Although random linear network coding (RLNC) constitutes a highly efficient and distributed approach to enhance communication networks and distributed storage, it requires additional processing to be carried out in the network and in end devices. For mobile devices, this processing translates into energy use that may reduce the battery life of a device. This paper focuses not only on providing a comprehensive...
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