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SUMMARY:Two talk double feature: NetFridgeS and The Small World Web of AI 
 - Zhukun Wang (University of Oxford) / Noa Zilberman (University of Oxford
 )
DTSTART:20251111T150000Z
DTEND:20251111T160000Z
UID:TALK239905@talks.cam.ac.uk
CONTACT:Professor Andrew W. Moore
DESCRIPTION:Talk 1.\n\nNetFridgeS: Enabling Dynamic Frequency Scaling on N
 etwork Switches through Carbon-Aware Routing\n\nAbstract: High performance
  network switches are designed to meet peak throughput demands\, always op
 erating at maximum clock frequency to avoid packet drops. However\, real-w
 orld network traffic exhibits clear periodic patterns\, leading to a waste
  of energy due to over-provisioning during non-peak hours. Dynamic frequen
 cy scaling\, a popular energy saving mechanism\,was not adopted by network
  switches due to differences in architecture from CPUs and the requirement
  not to drop packets. In this paper\, we present NetFridgeS\, enabling dyn
 amic frequency scaling on high-performance network switches. NetFridgeS bu
 ilds upon carbon-aware routing to forecast network utilization and adjust 
 pipeline frequency. NetFridgeS is prototyped on FPGA using three distinct 
 pipeline architectures\, with sub-microsecond frequency switching times an
 d minimal latency and resource overhead. By scaling down the frequency\, N
 etFridgeS achieves an average energy saving of 77.74% at minimum throughpu
 t. In real network topologies\, the combination of NetFridgeS and carbon a
 ware routing results in up to a 22.11% reduction in overall energy consump
 tion and a 27.76% reduction in carbon emissions compared with current netw
 ork deployments.\n\nTalk 2.\n\nTitle: The Small World Web of AI\n\nAbstrac
 t: The rise of generative AI has transformed many fields\, including netwo
 rking. While generative AI is already used for network management and oper
 ation\, little was done to fundamentally change the way we use the web. In
  this paper\, we make the case for reimagining the web in the age of AI. W
 ith just minor changes to HTTP\, we demonstrate that web content can be di
 stributed as prompts turned into content on end user devices. This new sma
 ll world web (SWW) of AI reduces storage demands and network load\, and ha
 s the potential to improve Internet sustainability over time.
LOCATION:SS03 William Gates Building
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