ncsim combines DAG workflow scheduling with physically grounded CSMA/CA interference modeling and shows that interference-free evaluations select suboptimal schedulers in 27.8% of tested scenarios.
Edge Computing: Vision and Challenges
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.DC 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
The framework uses context-aware adaptive sensing on edge devices to reduce energy consumption in city-scale environmental monitoring, outperforming static and other adaptive strategies in simulations.
citing papers explorer
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ncsim: A Lightweight Simulator for Networked Edge Computing with Wireless Interference Modeling
ncsim combines DAG workflow scheduling with physically grounded CSMA/CA interference modeling and shows that interference-free evaluations select suboptimal schedulers in 27.8% of tested scenarios.
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An AI-Driven Framework for Energy-Efficient Environmental Monitoring in Smart Cities Using Edge Intelligence
The framework uses context-aware adaptive sensing on edge devices to reduce energy consumption in city-scale environmental monitoring, outperforming static and other adaptive strategies in simulations.