Large Language Models (LLMs) can generate drone programs from natural-language mission descriptions, but syntactically valid programs may still violate user intent, environmental constraints, and mission-level behavior. This problem is pronounced in cyber-physical applications, where correctness depends on the interact...
Unmanned Aerial Vehicles (UAVs) performing deadline-bound analytics over large rural areas cannot reliably offload workloads to sparse cellular base stations. We propose an approach that uses scheduled public buses as \textit{mobile fogs}: a UAV hands off data to a bus during a halt, and the bus carries it until its ro...
Suman Raj, Arindam Khanda, D. GaganaM et al.· 0 citations
Traffic management in emerging megacities requires real-time analytics over thousands of CCTV video streams under latency, bandwidth, compute and energy constraints. We present TrafficFab, an autonomic edge--cloud testbed for AI-driven traffic management, designed to validate a representative slice of a megacity deploy...
Mayank Arya, Pranjal Naman, Priyanshu Pansari et al.· 0 citations
Edge accelerators such as Nvidia Jetsons are an integral part of the computing continuum, and are used for DNN inference and training. Jetson edge devices have 2000+ CUDA cores within a 70W power envelope and offer 1000s of power modes to customize CPU, GPU and memory frequencies, enabling diverse power–performance tra...
P. K, Kunal Kumar Sahoo, Amartya Ranjan Saikia et al.· Proceedings of the Internati...· 0 citations
This work develops time and energy roofline characterizations for Orin AGX across power modes, coupled with analytical models of compute and memory for DNN inference, and extends these models to DNN training, and demonstrates power-mode tuning that achieves up to \(15\%\) lower energy with small inference-time impact f...
P. K, Kunal Kumar Sahoo, Amartya Ranjan Saikia et al.· Proceedings of the Internati...· 0 citations
Taurus is presented, a single-machine system for GNN inference on graphs that do not fit in RAM, supporting both full-graph inference and fanout-sampled inference, and outperforms the strongest layer-wise baseline, DGI.
Pranjal Naman, Yogesh L. Simmhan· arXiv.org· 0 citations
This work proposes and develops an open-source policy simulation framework, LoadStar, which forms a reusable benchmark pipeline for validating policies for resource-centric NoSQL workloads, and defines a resource optimization problem for placing Cosmos DB replicas onto VM nodes, and develops the Luna model for forecast...
Gunika Verma, V. AashutoshA, P. Srinivas et al.· Proceedings of the VLDB Endo...· 0 citations
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