The Mathematical Parallels Between Packet Switching and Information Transmission
Tony T. Lee
Abstract
All communication networks comprise of transmission systems and switching systems, even though they are usually treated as two separate issues. Communication channels are generally disturbed by noise from various sources. In circuit switched networks, reliable communication requires the error-tolerant transmission of bits over noisy channels. In packet switched networks, however, not only can bits be corrupted with noise, but resources along connection paths are also subject to contention. Thus, quality of service (QoS) is determined by buffer delays and packet losses. The theme of this paper is to show that transmission noise and packet contention actually have similar characteristics and can be tamed by comparable means to achieve reliable communication, and a number of analogies between switching and transmission are identified. The sampling theorem of bandlimited signals provides the cornerstone of digital communication and signal processing. Recently, the Birkhoff-von Neumann decomposition of traffic matrices has been widely applied to packet switches. With respect to the complexity reduction of packet switching, we show that the decomposition of a doubly stochastic traffic matrix plays a similar role to that of the sampling theorem in digital transmission. We conclude that packet switching systems are governed by mathematical laws that are similar to those of digital transmission systems as envisioned by Shannon in his seminal 1948 paper, A Mathematical Theory of Communication.
Create a lesson
Related papers
Deterministic Identification over Additive Gaussian Channels
Jonathan E. W. Huffmann, Holger Boche
Knowledge Distillation Driven Semantic NOMA with GAN Refinement for 6G Robotic Vehicle Networks
Qifei Wang, Zhen Gao, Li Qiao et al.
Real-Time Reconstruction of Markov Sources over MPR Channels
Pansee S. Elessawy, Nikolaos Pappas
Minimum Rate For Partially Observable Linear System with Side Information: LQG Plant and Gaussian-Markov Source
Sijie Li, Hyeji Kim
Spectral Approximation and Ergodic-Capacity Convergence of HMIMO Channels under Spatial-Wavenumber Domain Mismatch
Hangsong Yan, Hong Yang, Shu Sun
Sharp Minimax Regret for Infinite-Memory Logistic Prediction
Vaneet Aggarwal