Note on the capacity and geometric realizability of combinatorial mobile sensor networks

[1910.04162] Note on the capacity and geometric realizability of combinatorial mobile sensor networks Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Discrete Mathematics arXiv:1910.04162 (cs) [Submitted on 9 Oct 2019 ( v1 ), last revised 16 Aug 2026 (this version, v4)] Title: Note on the capacity and geometric realizability of combinatorial mobile sensor networks Authors: Yizhen Chen View a PDF of the paper titled Note on the capacity and geometric realizability of combinatorial mobile sensor networks, by Yizhen Chen View PDF HTML (experimental) Abstract: We develop the mathematical theory of a model, constructed by C. Gu, I. Downes, O. Gnawali, and L. Guibas, of networks that diffuse continuously acquired information from mobile sensor nodes. We improve estimates of the expectation and variance of capacity of their model of restricted combinatorial mobile sensor networks (RCMSN) and geometric mobile sensor networks (GMSN), and give the maximum capacity of a variant of GMSN. We also show that the problem of deciding when an RCMSN is generated from a GMSN is NP-Hard, while a simple variant is solvable in polynomial time. Comments: 10 pages, 5 figures. For additional results, see the previous version. Thm. 22 is incorrect in the previous version Subjects: Discrete Mathematics (cs.DM) ; Computational Complexity (cs.CC) MSC classes: 68R05, 68Q17 Cite as: arXiv:1910.04162 [cs.DM] (or arXiv:1910.04162v4 [cs.DM] for this version) https://doi.org/10.48550/arXiv.1910.04162 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Yizhen Chen [ view email ] [v1] Wed, 9 Oct 2019 14:48:31 UTC (916 KB) [v2] Tue, 21 Jan 2020 23:20:58 UTC (583 KB) [v3] Tue, 2 Feb 2021 00:04:54 UTC (581 KB) [v4] Sun, 16 Aug 2026 07:14:04 UTC (13 KB) Full-text links: Access Paper: View a PDF of the paper titled Note on the capacity and geometric realizability of combinatorial mobile sensor networks, by Yizhen Chen View PDF HTML (experimental) TeX Source view license Current browse context: cs.DM < prev | next > new | recent | 2019-10 Change to browse by: cs cs.CC References & Citations NASA ADS Google Scholar Semantic Scholar DBLP - CS Bibliography listing | bibtex export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

Related documents

• Note on the capacity and geometric realizability of combinatorial mobile sensor networks#611197
• The Sheaf Laplacian: A Topological Framework for Data Fusion and Consensus in Distributed Sensing Networks#290556
• Connectivity Preservation and Graph Stretching in Range-Only Swarm Dispersion#1064734
• On the asymptotic spectral distribution of Cartesian powers of line graphs of complete graphs#290500
• On a possible lockup condition in IMP subnet due to message sequencing#213346