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

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