Optimal Network Coding Under Some Less-Restrictive Network Models

Chih-Hua Chang, Purdue University

Abstract

Network Coding is a critical technique when designing next-generation network systems, since the use of network coding can significantly improve the throughput and performance (delay/reliability) of the system. In the traditional design paradigm without network coding, different information flows are transported in a similar way like commodity flows such that the flows are kept separated while being forwarded in the network. However, network coding allows nodes in the network to not only forward the packet but also process the incoming information messages with the goal of either improving the throughput, reducing delay, or increasing the reliability. Specifically, network coding is a critical tool when designing absolute Shannon-capacity-achieving schemes for various broadcasting and multicasting applications. In this thesis, we study the optimal network schemes for some applications with less restrictive network models. A common component of the models/approaches is how to use network coding to take advantage of a broadcast communication channel.In the first part of the thesis, we consider the system of one server transmitting K information flows, one for each of K users (destinations), through a broadcast packet erasure channels with ACK/NACK. The capacity region of 1-to-K broadcast packet erasure channels with ACK/NACK is known for some scenarios, e.g., K ≤ 3, etc. However, existing achievability schemes with network coding either require knowing the target rate R~ in advance, and/or have a complicated description of the achievable rate region that is difficult to prove whether it matches the capacity or not. In this part, we propose a new network coding protocol with the following features: (i) Its achievable rate region is identical to the capacity region for all the scenarios in which the capacity is known; (ii) Its achievable rate region is much more tractable and has been used to derive new capacity rate vectors; (iii) It employs sequential encoding that naturally handles dynamic packet arrivals; (iv) It automatically adapts to unknown packet arrival rates R~ ; (v) It is based on GF(q) with q ≥ K. Numerically, for K= 4, it admits an average control overhead 1.1% (assuming each packet has 1000 bytes), average encoding memory usage 48.5 packets, and average per-packet delay 513.6 time slots, when operating at 95% of the capacity.

Degree

Ph.D.

Advisors

Wang, Purdue University.

Subject Area

Design

COinS