Dynamic packet fragmentation based on particle swarm optimised prediction

摘要

Particle Swarm Optimisation (PSO) has been successfully applied in function optimisation, neural network design, classification, pattern recognition, signal processing, robot technology and so on. The new concept of analysis and prediction of network performance using PSO is proposed, and the main challenges come from network traffic for different applications. We collected and analysed traffic of BigBlueButton application, using Hurst calculation approach to judge the performance of network, and offered the necessary prediction. According to Hurst classification, using PSO algorithm to find the right packet size distribution under the network performance constraints. The paper proposes a new dynamic perspective about packet fragmentation and the related performance of the real- time applications. It can reduce network congestion and improve the end user experience. The paper offers a preliminary analysis and simulation with the biological algorithm.