arXiv (All)
open access
Nova: Scalable Streaming Join Placement and Parallelization in Resource-Constrained Geo-Distributed Environments
Real-time data processing in large geo-distributed applications, like the Internet of Things (IoT), increasingly shifts computation from the cloud to the network edge to reduce latency and mitigate network congestion. In this setting, minimizing latency while avoiding node overload requires jointly
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- dSTAR: Straggler Tolerant and Byzantine Resilient Distributed SGD#1035272
- MonkeyTree: Near-Minimal Congestion for Multi-tenant Training via Migration#1011041
- Estimation, scalability, robustness, and coordination methods for Direct-to-Satellite IoT#378065
- Design and Implementation of a Scalable Distributed Machine Learning Infrastructure for Real-Time High-Frequency Financial Transactions#110591
- Bandwidth-Aware and Cost-Efficient Pipeline Parallel Scheduling in Geo-Distributed LLM Training#224467
Record · ID 1036648
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive