arXiv (All)
open access
Pipelining vs. Combining in Aggregation Tasks
We study the aggregation task (convergecast) in networks in the case that the values to be aggregated do not fit in a single message. We assume that every node starts with an input value, and there is an aggregation operator that is commutative, associative, and length-preserving, i.e., the result o
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
- Pipelining vs. Combining in Aggregation Tasks#1417806
- Bunching of extreme events on complex network#670385
- Bunching of extreme events on complex network#668320
- Network Accuracy Across Levels of Analysis Using Stochastic Block Models#233215
- Network Accuracy Across Levels of Analysis Using Stochastic Block Models#16259
Record · ID 1424501
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