Random Linear Network Coding for converge-cast Smart Grid wireless networks

The power electric grid is undergoing a paradigm shift with the inclusion of information and communication technologies that allow for two-way flow of information, automation and distributed intelligence. A reliable and secure Smart-Grid Communications Network (SGCN), is necessary to achieve the SG goals. In particular, the SG Neighbor Area Network (NAN) poses a communications challenge due to the bottlenecks associated with the converge-cast nature of uplink traffic. This can potentially be addressed through network coding. Therefore, this paper aims to determine the feasibility of Random Linear Network Coding (RLNC) at the SG NAN level. Specifically, RLNC is considered in converge-cast scenarios while both network size and link reliability are varied. This preliminary study suggests that inter-session RLNC does achieve throughput enhancements but at the cost of higher network load. Additionally, performance drops sharply with low link reliabilities due to the lack of partial decoding. Therefore, for large converge-cast networks, as in the case of the SG NAN, network coding that allows for partial decoding operations should be more beneficial.