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SEKHMET: Hash-Chained Perception Contracts for Heterogeneous Real-Time Edge Clusters

Author Mohamed El-Hadedy

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Subject Classification

ACM Subject Classification
  • Computer systems organization → Real-time systems
  • Computer systems organization → Cloud computing
Keywords
  • edge clusters
  • K3s
  • Kubernetes
  • real-time perception
  • scheduling
  • integrity contracts
  • hash chaining
  • Hailo-8L

Metrics

Abstract

Real-time perception pipelines on edge clusters are often scheduled as ordinary latency-sensitive pods, even when safety depends on sustained throughput and stable model outputs. This paper presents SEKHMET (Scheduling Edge Kubernetes with Hash-chained Monitoring of End-to-end Telemetry), a perception-aware orchestration layer for lightweight Kubernetes (K3s) clusters that exports window-level perception status as a control-plane signal. SEKHMET evaluates a perception-integrity contract (PIC) once per fixed-duration window and commits each window outcome into a hash-chained perception root that is published to an otherwise unmodified K3s control plane. The prototype uses a Raspberry Pi 5 perception-root node with a Hailo-8L accelerator, USB camera, and GPS receiver running a YOLOv8s detector, while up to five additional nodes generate elastic interference via swarm-stress. Under contract-unaware scheduling with multi-node interference, the end-to-end perception loop delivers ∼0.8-2.2 FPS and violates the PIC timing requirement in most of 214 windows, despite apparently healthy CPU and memory metrics. Under the same and heavier interference, SEKHMET sustains 27-30 FPS with contract_ok = True across 400 protected windows while publishing one 96-byte record per T=5s window (19.2 B/s control-plane payload). These results show that making perception requirements control-plane-visible can turn fragile best-effort perception into a protected cluster-level resource on commodity edge hardware.

Cite As Get BibTex

Mohamed El-Hadedy. SEKHMET: Hash-Chained Perception Contracts for Heterogeneous Real-Time Edge Clusters. In 7th Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2026). Open Access Series in Informatics (OASIcs), Volume 140, pp. 5:1-5:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/OASIcs.NG-RES.2026.5

Author Details

Mohamed El-Hadedy
  • Department of Electrical and Computer Engineering, California State Polytechnic University, Pomona, CA, USA
  • Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, IL, USA

Acknowledgements

This research was funded by the U.S. Navy NEEC (Grant N001742310002) and the Office of Naval Research (ONR) Summer Faculty Research Program (SFRP). It was also supported in part by the U.S. Department of Defense under award W911NF-24-1-0265 and by the Air Force Research Laboratory (AFRL) under agreement FA8650-24-2-2403. The U.S. Government is authorized to reproduce and distribute reprints for governmental purposes, notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of AFRL or the U.S. Government.

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