As data centers scale to accommodate dynamic workloads, real-time and fine-grained traffic engineering (TE) becomes critical. Software Defined Networking (SDN) offers centralized control over data flows, yet its effectiveness is constrained by traditional telemetry mechanisms that lack responsiveness. In-Band Network Telemetry (INT) addresses this gap by embedding real-time path metrics directly into packets, enabling adaptive traffic control based on live network conditions. This study implements and evaluates INT in a programmable Clos fabric using P4 enabled switches. It compares three TE strategies: static ECMP, switch assisted CONGA, and INT informed INT HULA. The simulation incorporates synthetic and trace based data center workloads, including elephant flows and incast scenarios. Performance is assessed using flow completion time (FCT), queue depth, link utilization, and failure recovery speed. INT metadata sizes (32–96 bytes) are also analyzed to quantify overhead vs. performance trade offs. Results indicate that INT HULA consistently outperforms ECMP and CONGA. It reduces FCT by up to 50%, decreases queue occupancy by a factor of three, increases link utilization by more than 25%, and shortens reroute times from 85 ms to 20 ms. These gains are achieved with manageable telemetry overhead and without requiring hardware changes. INT’s real time visibility also improves decision making in centralized SDN controllers and supports hybrid TE architectures. In conclusion, INT fundamentally enhances SDN based TE by enabling closed loop, real time optimization. Its integration with programmable data planes and potential for AI based control loops positions it as a cornerstone of next generation data center networks.
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