Trading Throughput for Freshness: Freshness-aware Traffic Engineering and In-Network Freshness Control

Abstract

With the advent of the Internet of Things (IoT), applications are becoming increasingly dependent on networks to not only transmit content at high throughput but also deliver it when it is fresh, i.e., synchronized between source and destination. Existing studies have proposed the metric age of information (AoI) to quantify freshness and have system designs that achieve low AoI. However, despite active research in this area, existing results are not applicable to general wired networks for two reasons. First, they focus on wireless settings, where AoI is mostly affected by interference and collision, while queueing issues are more prevalent in wired settings. Second, traditional high-throughput/low-latency legacy drop-adverse (LDA) flows are not taken into account in most system designs; hence, the problem of scheduling mixed flows with distinct performance objectives is not addressed. In this article, we propose a hierarchical system design to treat wired networks shared by mixed flow traffic, specifically LDA and AoI flows, and study the characteristics of achieving a good tradeoff between throughput and AoI. Our approach to the problem consists of two layers: freshness-aware traffic engineering (FATE) and in-network freshness control (IFC). The centralized FATE solution studies the characteristics of the source flow to derive the sending rate/update frequency for flows via the optimization problem LDA-AoI Coscheduling. The parameters specified by FATE are then distributed to IFC, which is implemented at each outport of the network’s nodes and used for efficient scheduling between LDA and AoI flows. We present a Linux implementation of IFC and demonstrate the effectiveness of FATE/IFC through extensive emulations. Our results show that it is possible to trade a little throughput (5% lower) for much shorter AoI (49% to 71% shorter) compared to state-of-the-art traffic engineering.