DBOS Network Sensing: A Web Services Approach to Collaborative Awareness

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 work-flow 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<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sup>, 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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Published
2025-09-15
DOI
https://doi.org/10.1109/hpec67600.2025.11196670
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
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article

DBOS Network Sensing: A Web Services Approach to Collaborative Awareness

Albert Reuther, Alex Pentland, Michael E. Houle, William Arcand et al.
Energy Efficient Wireless Sensor Networks
article

DBOS Network Sensing: A Web Services Approach to Collaborative Awareness

Albert Reuther, Alex Pentland, Michael E. Houle, William Arcand, Vijay Gadepally, Timothy M. E. Davis, Michel Pelletier, Lauren Milechin, Julie Mullen, William Bergeron, Hayden Jananthan, Jeremy Kepner, David Bestor, Piotr Łuszczek, Michael Stonebraker, Matthew Hubbell, Alex Poliakov, Andrew Prout, Chansup Byun, Guillermo Morales, Daniel Burrill, Michael G. Jones, Antonio Rosa, Larry W. Anderson, Charles Yee, Peter Michaleas, Chasen Milner, Alex Bonn, Sophia Lockton
article en

Abstract

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 work-flow 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<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sup>, 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.

Kubota (Japan) (JP), Moscow Institute of Thermal Technology (RU)
Openalex Percentile: Top 65%
Energy Efficient Wireless Sensor Networks
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