On the Impact of Coding Depth in Sliding Window Random Linear Network Coding Schemes

Sliding Window Random Linear Network Coding (RLNC) offers a clear path towards achieving ultra-high reliability and low latency at the same time. Such requirements are pivotal for a wide range of applications in the future Internet as well as in 5G and beyond networks. While traditional RLNC has been extensively used for some years now, its Sliding Window flavor is rather recent and extremely promising because of its implementation advantages and the high degree of customization. Probably the most essential parameter of Sliding Window RLNC is the coding depth, i.e., the extent of non-coded packets protected by a coded one. In this work, for the first time, we elaborate on properly choosing the coding depth and shed light on the related trade-offs. We, first, show, experimentally, that significant performance gains can be obtained by fine-tuning the coding depth. Then, we propose and validate an analytical framework that allows us to decide the coding depth based on a channel’s reliability profile. Finally, we introduce a dynamic algorithm that, based on our analytical findings, can improve the performance of sliding window RLNC in the presence of bursts of errors.