{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/simple-load-balancing","title":"Simple Load Balancing","arxiv_id":"1808.05389","date":"2018-08-16","proceeding":null,"authors":["Petra Berenbrink","Tom Friedetzky","Dominik Kaaser","Peter Kling"],"abstract":"We consider the following load balancing process for $m$ tokens distributed arbitrarily among $n$ nodes connected by a complete graph: In each time step a pair of nodes is selected uniformly at random. Let $\\ell_1$ and $\\ell_2$ be their respective number of tokens. The two nodes exchange tokens such that they have $\\lceil(\\ell_1 + \\ell_2)/2\\rceil$ and $\\lfloor(\\ell_1 + \\ell_2)/2\\rfloor$ tokens, respectively. We provide a simple analysis showing that this process reaches almost perfect balance within $O(n\\log{n} + n \\log{\\Delta})$ steps, where $\\Delta$ is the maximal initial load difference between any two nodes.","url_abs":"http://arxiv.org/abs/1808.05389v1","url_pdf":"http://arxiv.org/pdf/1808.05389v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"simple-load-balancing","repo_url":"https://github.com/UC-Davis-molecular-computing/ppsim","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}