Modeling and analysis of the performance of networks in finite-buffer regime

Abstract

In networks, using large buffers tend to increase end-to-end packet delay and its deviations, conflicting with real-time applications such as online gaming, audio-video services, IPTV, and VoIP. Further, large buffers complicate the design of high speed routers, leading to more power consumption and board space. According to Moore's law, switching speeds double every 18 months while memory access speeds double only every 10 years. Hence, as memory requirements increasingly become a limiting aspect of router design, studying networks in finite-buffer regime seems necessary for network engineers. This work focuses on both practical and theoretical aspects of finite-buffer networks. In Chapters 1-7, we investigate the effects of finite buffer sizes on the throughput and packet delay in different networks. These performance measures are shown to be linked to the stationary distribution of an underlying irreducible Markov chain that exactly models the changes in the network. An iterative scheme is proposed to approximate the steady-state distribution of buffer occupancies by decoupling the exact chain to smaller chains. These approximate solutions are used to analytically characterize network throughput and packet delay, and are also applied to some network performance optimization problems. Further, using simulations, it is confirmed that the proposed framework yields accurate estimates of the throughput and delay performance measures and captures the vital trends and tradeoffs in these networks. In Chapters 8-10, we address the problem of modeling and analysis of the performance of finite-memory random linear network coding in erasure networks. When using random linear network coding, the content of buffers creates dependencies which cannot be captured directly using the classical queueing theoretical models. A careful derivation of the buffer occupancy states and their transition rules are presented as well as decodability conditions when random linear network coding is performed on a stream of arriving packets.