PhD Forum: Padding Overhead Reduction in Random Linear Coded Variable Size Media Streams

Abstract

Ubiquitous IoT allowed everything to be connected, thereby creating heterogeneous data transmissions in the network, ranging from small sensor packets to large video frames. This prevents error correction techniques from proper algebraic coding without padding the unequal-sized packets. Random Linear Network Coding (RLNC) for instance, generates unreasonable amounts of padding overhead in media distribution that can suppress its pervasive benefits. We propose a set of approaches that overcome this issue, while also reducing the decoding delays at the same time.