Saved in:
| Main Authors: | Banerjee, Roopkatha, Koti, Sampath, Singh, Gyanendra, Chakraborty, Anirban, Gurrala, Gurunath, Jagyasi, Bhushan, Simmhan, Yogesh |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.08022 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Federated Learning within Global Energy Budget over Heterogeneous Edge Accelerators
by: Banerjee, Roopkatha, et al.
Published: (2025)
by: Banerjee, Roopkatha, et al.
Published: (2025)
OptimES: Optimizing Federated Learning Using Remote Embeddings for Graph Neural Networks
by: Naman, Pranjal, et al.
Published: (2025)
by: Naman, Pranjal, et al.
Published: (2025)
Optimizing Federated Learning using Remote Embeddings for Graph Neural Networks
by: Naman, Pranjal, et al.
Published: (2025)
by: Naman, Pranjal, et al.
Published: (2025)
Ripple: Scalable Incremental GNN Inferencing on Large Streaming Graphs
by: Naman, Pranjal, et al.
Published: (2025)
by: Naman, Pranjal, et al.
Published: (2025)
Understanding the Performance and Power of LLM Inferencing on Edge Accelerators
by: Arya, Mayank, et al.
Published: (2025)
by: Arya, Mayank, et al.
Published: (2025)
Flotilla: A scalable, modular and resilient federated learning framework for heterogeneous resources
by: Banerjee, Roopkatha, et al.
Published: (2025)
by: Banerjee, Roopkatha, et al.
Published: (2025)
Scaling Real-Time Traffic Analytics on Edge-Cloud Fabrics for City-Scale Camera Networks
by: Sharma, Akash, et al.
Published: (2026)
by: Sharma, Akash, et al.
Published: (2026)
ATLAS: Efficient Out-of-Core Inference for Billion-Scale Graph Neural Networks
by: Naman, Pranjal, et al.
Published: (2026)
by: Naman, Pranjal, et al.
Published: (2026)
Evaluating Multi-Instance DNN Inferencing on Multiple Accelerators of an Edge Device
by: Tayal, Mumuksh, et al.
Published: (2025)
by: Tayal, Mumuksh, et al.
Published: (2025)
AeroDaaS: Towards an Application Programming Framework for Drones-as-a-Service
by: Raj, Suman, et al.
Published: (2025)
by: Raj, Suman, et al.
Published: (2025)
AeroGen: Agentic Drone Autonomy through Single-Shot Structured Prompting & Drone SDK
by: Astu, Kautuk, et al.
Published: (2026)
by: Astu, Kautuk, et al.
Published: (2026)
PowerTrain: Fast, Generalizable Time and Power Prediction Models to Optimize DNN Training on Accelerated Edges
by: K., Prashanthi S., et al.
Published: (2024)
by: K., Prashanthi S., et al.
Published: (2024)
Characterizing the Performance of Accelerated Jetson Edge Devices for Training Deep Learning Models
by: K., Prashanthi S., et al.
Published: (2025)
by: K., Prashanthi S., et al.
Published: (2025)
D3FL: Data Distribution and Detrending for Robust Federated Learning in Non-linear Time-series Data
by: Marisetty, Harsha Varun, et al.
Published: (2025)
by: Marisetty, Harsha Varun, et al.
Published: (2025)
AerialDB: A Federated Peer-to-Peer Spatio-temporal Edge Datastore for Drone Fleets
by: Jaiswal, Shashwat, et al.
Published: (2025)
by: Jaiswal, Shashwat, et al.
Published: (2025)
AeroResQ: Edge-Accelerated UAV Framework for Scalable, Resilient and Collaborative Escape Route Planning in Wildfire Scenarios
by: Raj, Suman, et al.
Published: (2025)
by: Raj, Suman, et al.
Published: (2025)
RIPPLE++: An Incremental Framework for Efficient GNN Inference on Evolving Graphs
by: Naman, Pranjal, et al.
Published: (2026)
by: Naman, Pranjal, et al.
Published: (2026)
Adaptive Heuristics for Scheduling DNN Inferencing on Edge and Cloud for Personalized UAV Fleets
by: Raj, Suman, et al.
Published: (2024)
by: Raj, Suman, et al.
Published: (2024)
AeroDaaS: A Programmable Drones-as-a-Service Platform for Intelligent Aerial Systems
by: Astu, Kautuk, et al.
Published: (2026)
by: Astu, Kautuk, et al.
Published: (2026)
Optimizing FaaS Platforms for MCP-enabled Agentic Workflows
by: Kulkarni, Varad, et al.
Published: (2026)
by: Kulkarni, Varad, et al.
Published: (2026)
A Blockchain-Enabled Framework for Storage and Retrieval of Social Data
by: Parab, Aishwarya, et al.
Published: (2025)
by: Parab, Aishwarya, et al.
Published: (2025)
Performance Characterization of Containerized DNN Training and Inference on Edge Accelerators
by: K., Prashanthi S., et al.
Published: (2023)
by: K., Prashanthi S., et al.
Published: (2023)
SageServe: Optimizing LLM Serving on Cloud Data Centers with Forecast Aware Auto-Scaling
by: Jaiswal, Shashwat, et al.
Published: (2025)
by: Jaiswal, Shashwat, et al.
Published: (2025)
Characterizing FaaS Workflows on Public Clouds: The Good, the Bad and the Ugly
by: Kulkarni, Varad, et al.
Published: (2025)
by: Kulkarni, Varad, et al.
Published: (2025)
End-to-End and Phase-Level Performance Optimization for Hyperledger Fabric
by: Sollu, Pavan, et al.
Published: (2026)
by: Sollu, Pavan, et al.
Published: (2026)
AgentX: Towards Orchestrating Robust Agentic Workflow Patterns with FaaS-hosted MCP Services
by: Tokal, Shiva Sai Krishna Anand, et al.
Published: (2025)
by: Tokal, Shiva Sai Krishna Anand, et al.
Published: (2025)
Ocularone-Bench: Benchmarking DNN Models on GPUs to Assist the Visually Impaired
by: Raj, Suman, et al.
Published: (2025)
by: Raj, Suman, et al.
Published: (2025)
Fulcrum: Optimizing Concurrent DNN Training and Inferencing on Edge Accelerators
by: K., Prashanthi S., et al.
Published: (2025)
by: K., Prashanthi S., et al.
Published: (2025)
FedOptimus: Optimizing Vertical Federated Learning for Scalability and Efficiency
by: Shrivastava, Nikita, et al.
Published: (2025)
by: Shrivastava, Nikita, et al.
Published: (2025)
Pagoda: An Energy and Time Roofline Study for DNN Workloads on Edge Accelerators
by: K., Prashanthi S., et al.
Published: (2025)
by: K., Prashanthi S., et al.
Published: (2025)
Collaborative Processing for Multi-Tenant Inference on Memory-Constrained Edge TPUs
by: Ng, Nathan, et al.
Published: (2026)
by: Ng, Nathan, et al.
Published: (2026)
SWARM+: Scalable and Resilient Multi-Agent Consensus for Fully-Decentralized Data-Aware Workload Management
by: Thareja, Komal, et al.
Published: (2026)
by: Thareja, Komal, et al.
Published: (2026)
Totoro$^+$: An Adaptive and Scalable Edge Federated Learning System
by: Ching, Cheng-Wei, et al.
Published: (2026)
by: Ching, Cheng-Wei, et al.
Published: (2026)
CrashEventLLM: Predicting System Crashes with Large Language Models
by: Mudgal, Priyanka, et al.
Published: (2024)
by: Mudgal, Priyanka, et al.
Published: (2024)
Optimizing Microgrid Composition for Sustainable Data Centers
by: Irion, Julius, et al.
Published: (2025)
by: Irion, Julius, et al.
Published: (2025)
Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning
by: Das, Anirban, et al.
Published: (2021)
by: Das, Anirban, et al.
Published: (2021)
Calibrating Microgrid Simulations for Energy-Aware Computing Systems
by: Steinke, Marvin
Published: (2026)
by: Steinke, Marvin
Published: (2026)
Blockchain-enabled Energy Trading and Battery-based Sharing in Microgrids
by: Zekiye, Abdulrezzak, et al.
Published: (2024)
by: Zekiye, Abdulrezzak, et al.
Published: (2024)
Sketched Gaussian Mechanism for Private Federated Learning
by: Li, Qiaobo, et al.
Published: (2025)
by: Li, Qiaobo, et al.
Published: (2025)
Optimizing Federated Learning in the Era of LLMs: Message Quantization and Streaming
by: Xu, Ziyue, et al.
Published: (2025)
by: Xu, Ziyue, et al.
Published: (2025)
Similar Items
-
Federated Learning within Global Energy Budget over Heterogeneous Edge Accelerators
by: Banerjee, Roopkatha, et al.
Published: (2025) -
OptimES: Optimizing Federated Learning Using Remote Embeddings for Graph Neural Networks
by: Naman, Pranjal, et al.
Published: (2025) -
Optimizing Federated Learning using Remote Embeddings for Graph Neural Networks
by: Naman, Pranjal, et al.
Published: (2025) -
Ripple: Scalable Incremental GNN Inferencing on Large Streaming Graphs
by: Naman, Pranjal, et al.
Published: (2025) -
Understanding the Performance and Power of LLM Inferencing on Edge Accelerators
by: Arya, Mayank, et al.
Published: (2025)