DBOS Network Sensing: A Web Services Approach to Collaborative Awareness Article Swipe
Sophia Lockton
,
Jeremy Kepner
,
Michael Stonebraker
,
Hayden Jananthan
,
Larry W. Anderson
,
William Arcand
,
David Bestor
,
William Bergeron
,
Alex Bonn
,
Daniel Burrill
,
Chansup Byun
,
Timothy M. E. Davis
,
Vijay Gadepally
,
Michael E. Houle
,
Matthew Hubbell
,
Michael G. Jones
,
Piotr Łuszczek
,
Peter Michaleas
,
Lauren Milechin
,
Chasen Milner
,
Guillermo Morales
,
Julie Mullen
,
Michel Pelletier
,
Alex Poliakov
,
Andrew Prout
,
Albert Reuther
,
Antonio Rosa
,
Charles Yee
,
Alex Pentland
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2509.09898
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2509.09898
DBOS (DataBase Operating System) is a novel capability that integrates web services, operating system functions, and database features to significantly reduce web-deployment effort while increasing resilience. Integration of high performance network sensing enables DBOS web services to collaboratively create a shared awareness of their network environments to enhance their collective resilience and security. Network sensing is added to DBOS using GraphBLAS hypersparse traffic matrices via two approaches: (1) Python-GraphBLAS and (2) OneSparse PostgreSQL. These capabilities are demonstrated using the workflow and analytics from the IEEE/MIT/Amazon Anonymized Network Sensing Graph Challenge. The system was parallelized using pPython and benchmarked using 64 compute nodes on the MIT SuperCloud. The web request rate sustained by a single DBOS instance was ${>}10^5$, well above the required maximum, indicating that network sensing can be added to DBOS with negligible overhead. For collaborative awareness, many DBOS instances were connected to a single DBOS aggregator. The Python-GraphBLAS and OneSparse PostgreSQL implementations scaled linearly up to 64 and 32 nodes respectively. These results suggest that DBOS collaborative network awareness can be achieved with a negligible increase in computing resources.
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2509.09898
- https://arxiv.org/pdf/2509.09898
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W4414592972
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4414592972Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2509.09898Digital Object Identifier
- Title
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DBOS Network Sensing: A Web Services Approach to Collaborative AwarenessWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-09-11Full publication date if available
- Authors
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Sophia Lockton, Jeremy Kepner, Michael Stonebraker, Hayden Jananthan, Larry W. Anderson, William Arcand, David Bestor, William Bergeron, Alex Bonn, Daniel Burrill, Chansup Byun, Timothy M. E. Davis, Vijay Gadepally, Michael E. Houle, Matthew Hubbell, Michael G. Jones, Piotr Łuszczek, Peter Michaleas, Lauren Milechin, Chasen Milner, Guillermo Morales, Julie Mullen, Michel Pelletier, Alex Poliakov, Andrew Prout, Albert Reuther, Antonio Rosa, Charles Yee, Alex PentlandList of authors in order
- Landing page
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https://arxiv.org/abs/2509.09898Publisher landing page
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https://arxiv.org/pdf/2509.09898Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2509.09898Direct OA link when available
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0Total citation count in OpenAlex
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| abstract_inverted_index.instances | 140 |
| abstract_inverted_index.operating | 12 |
| abstract_inverted_index.overhead. | 134 |
| abstract_inverted_index.security. | 52 |
| abstract_inverted_index.services, | 11 |
| abstract_inverted_index.sustained | 110 |
| abstract_inverted_index.Anonymized | 85 |
| abstract_inverted_index.Challenge. | 89 |
| abstract_inverted_index.PostgreSQL | 152 |
| abstract_inverted_index.awareness, | 137 |
| abstract_inverted_index.capability | 7 |
| abstract_inverted_index.collective | 49 |
| abstract_inverted_index.functions, | 14 |
| abstract_inverted_index.increasing | 24 |
| abstract_inverted_index.indicating | 123 |
| abstract_inverted_index.integrates | 9 |
| abstract_inverted_index.negligible | 133, 176 |
| abstract_inverted_index.resilience | 50 |
| abstract_inverted_index.resources. | 180 |
| abstract_inverted_index.Integration | 26 |
| abstract_inverted_index.PostgreSQL. | 72 |
| abstract_inverted_index.SuperCloud. | 105 |
| abstract_inverted_index.aggregator. | 147 |
| abstract_inverted_index.approaches: | 66 |
| abstract_inverted_index.benchmarked | 97 |
| abstract_inverted_index.hypersparse | 61 |
| abstract_inverted_index.performance | 29 |
| abstract_inverted_index.resilience. | 25 |
| abstract_inverted_index.capabilities | 74 |
| abstract_inverted_index.demonstrated | 76 |
| abstract_inverted_index.environments | 45 |
| abstract_inverted_index.parallelized | 93 |
| abstract_inverted_index.${>}10^5$, | 117 |
| abstract_inverted_index.collaborative | 136, 168 |
| abstract_inverted_index.respectively. | 162 |
| abstract_inverted_index.significantly | 19 |
| abstract_inverted_index.web-deployment | 21 |
| abstract_inverted_index.IEEE/MIT/Amazon | 84 |
| abstract_inverted_index.collaboratively | 37 |
| abstract_inverted_index.implementations | 153 |
| abstract_inverted_index.Python-GraphBLAS | 68, 149 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 29 |
| citation_normalized_percentile |