Cubic-Permutation-Polynomial-Based Sliding Window Network Coding Algorithm in IoT

Abstract

Network coding (NC) is an information transmission technology that encodes and transmits data packets on a network. NC can be applied to the Internet of Things (IoT) and can effectively improve the data transmission quality and throughput of the IoT. The complexity of data packets encoding and decoding is an important problem in NC applications. The cubic permutation polynomial (CPP) can better optimize the data packets participating in NC, reduce the computational complexity of data packet encoding/decoding, and improve the data packet transmission bandwidth and data throughput of the IoT. This paper proposes a Cubic Permutation Polynomial-based Sliding Window NC algorithm in IoT (CPP-SWNC). In the paper, firstly, the fusion theory of CPP and sliding window (SW) was discussed. Secondly, the theory that optimize the size of sliding windows was demonstrated. Thirdly, an analysis was conducted from the perspective of mathematical theory. Finally, simulation experiments were conducted to evaluate the performance of the CPP-SWNC algorithm using Network Simulation (NS) software, mainly by comparing and analyzing the network throughput, average packet encoding overhead, and packet decoding delay. The simulation results show that CPP-SWNC algorithm can improve the performance and data packet transmission quality of the IoT, and can further improve the application field of the IoT.