Leveraging statistical multiplexing gains in single- and multi-hop networks

Abstract

Packet switched networks achieve significant resource savings due to statistical multiplexing. In this work we explore statistical multiplexing gains in single and multi-hop networks. To this end, we analyze performance metrics such as delay bounds for a through flow comparing different results from the stochastic network calculus. We distinguish different multiplexing gains that stem from independence assumptions between flows at a single hop as well as flows at consecutive hops of a network path. Further, we show corresponding numerical results. In addition to deriving the benefits of various statistical multiplexing models on performance bounds, we contribute insights into the scaling of end-to-end delay bounds in the number of hops n of a network path under statistical independence.