4 Search Results for "Milton, Richard"

Document
DOI: 10.4230/OASIcs.NINeS.2026.10
Scalable Routing in a City-Scale Wi-Fi Network for Disaster Recovery

Authors: Ziqian Liu, Om Chabra, James Lynch, Aaron Martin, Chenning Li, and Hari Balakrishnan

Published in: OASIcs, Volume 139, 1st New Ideas in Networked Systems (NINeS 2026)

Abstract
This paper presents CityMesh, a city-scale decentralized mesh network designed for disaster recovery and emergency scenarios. When wide-area Internet connectivity is unavailable or severely degraded, CityMesh leverages both static access points and mobile devices equipped with Wi-Fi to provide intra-city connectivity and reach opportunistic gateways to the Internet (e.g., via satellite links). The main contribution of this paper is a scalable routing protocol that supports millions of devices, addressing a long-standing limitation of wireless mesh and mobile ad hoc networks. Unlike prior approaches, CityMesh exploits rich building-location and building-geometry data from widely available city maps to guide route computation, improving packet delivery while significantly reducing transmission overhead. Simulation results from 70 cities show that CityMesh improves packet delivery rates by 88% over WEAVE (a state-of-the-art geographic routing protocol). A campus-scale deployment of 300 Wi-Fi devices across 31 buildings shows the practical deployability of CityMesh. These results demonstrate the promise of map-aware routing as a foundation for scalable, resilient city-wide Wi-Fi networks.
Cite as

Ziqian Liu, Om Chabra, James Lynch, Aaron Martin, Chenning Li, and Hari Balakrishnan. Scalable Routing in a City-Scale Wi-Fi Network for Disaster Recovery. In 1st New Ideas in Networked Systems (NINeS 2026). Open Access Series in Informatics (OASIcs), Volume 139, pp. 10:1-10:31, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{liu_et_al:OASIcs.NINeS.2026.10,
  author =	{Liu, Ziqian and Chabra, Om and Lynch, James and Martin, Aaron and Li, Chenning and Balakrishnan, Hari},
  title =	{{Scalable Routing in a City-Scale Wi-Fi Network for Disaster Recovery}},
  booktitle =	{1st New Ideas in Networked Systems (NINeS 2026)},
  pages =	{10:1--10:31},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-414-7},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{139},
  editor =	{Argyraki, Katerina and Panda, Aurojit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.NINeS.2026.10},
  URN =		{urn:nbn:de:0030-drops-255954},
  doi =		{10.4230/OASIcs.NINeS.2026.10},
  annote =	{Keywords: mesh networking, disaster recovery, geographic routing, scalability, Wi-Fi}
}
Document
DOI: 10.4230/OASIcs.SpaceCHI.2025.26
Movement in Low Gravity (MoLo) – LUNA: Biomechanical Modelling to Mitigate Lunar Surface Operation Risks

Authors: David Andrew Green

Published in: OASIcs, Volume 130, Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)

Abstract
The Artemis programme seeks to develop and test concepts, hardware and approaches to support long term habitation of the Lunar surface, and future missions to Mars. In preparation for the Artemis missions determination of tasks to be performed, the functional requirements of such tasks and as mission duration extends whether physiological deconditioning becomes functionally significant, compromising the crew member’s ability to perform critical tasks on the surface, and/or upon return to earth [MoLo-LUNA – leveraging the Molo programme (and several other activities) - could become a key supporting activity for LUNA incl. validation of the Puppeteer offloading system itself via creation of a complementary MoLo-LUNA-LAB. Furthermore, the MoLo-LUNA programme could become a key facilitator of simulator suit instrumentation/definition, broader astronaut training activities and mission architecture development – including Artemis mission simulations. By employing a Puppeteer system external to the LUNA chamber hall it will optimise utilisation and cost-effectiveness of LUNA, and as such represents a critical service to future LUNA stakeholders. Furthermore, MoLo-LUNA would generate a unique data set that can be leveraged to predict de-conditioning on the Lunar surface - and thereby optimise functionality, and minimise mission risk – including informing the need for, and prescription of exercise countermeasures on the Lunar Surface and in transit. Thus, MoLo-LUNA offers a unique opportunity to place LUNA, and ESA as a key ongoing provider of evidence to define, optimise and support crew Artemis surface missions.
Cite as

David Andrew Green. Movement in Low Gravity (MoLo) – LUNA: Biomechanical Modelling to Mitigate Lunar Surface Operation Risks. In Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025). Open Access Series in Informatics (OASIcs), Volume 130, pp. 26:1-26:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{green:OASIcs.SpaceCHI.2025.26,
  author =	{Green, David Andrew},
  title =	{{Movement in Low Gravity (MoLo) – LUNA: Biomechanical Modelling to Mitigate Lunar Surface Operation Risks}},
  booktitle =	{Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)},
  pages =	{26:1--26:11},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-384-3},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{130},
  editor =	{Bensch, Leonie and Nilsson, Tommy and Nisser, Martin and Pataranutaporn, Pat and Schmidt, Albrecht and Sumini, Valentina},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SpaceCHI.2025.26},
  URN =		{urn:nbn:de:0030-drops-240166},
  doi =		{10.4230/OASIcs.SpaceCHI.2025.26},
  annote =	{Keywords: Locomotion, hypogravity, modelling, Lunar}
}
Document
Position
DOI: 10.4230/TGDK.1.1.5
Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities

Authors: Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, and Valentina Tamma

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines. Research efforts in life sciences are heavily data-driven, as they produce and consume vast amounts of scientific data, much of which is intrinsically relational and graph-structured. The volume of data and the complexity of scientific concepts and relations referred to therein promote the application of advanced knowledge-driven technologies for managing and interpreting data, with the ultimate aim to advance scientific discovery. In this survey and position paper, we discuss recent developments and advances in the use of graph-based technologies in life sciences and set out a vision for how these technologies will impact these fields into the future. We focus on three broad topics: the construction and management of Knowledge Graphs (KGs), the use of KGs and associated technologies in the discovery of new knowledge, and the use of KGs in artificial intelligence applications to support explanations (explainable AI). We select a few exemplary use cases for each topic, discuss the challenges and open research questions within these topics, and conclude with a perspective and outlook that summarizes the overarching challenges and their potential solutions as a guide for future research.
Cite as

Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, and Valentina Tamma. Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 5:1-5:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{chen_et_al:TGDK.1.1.5,
  author =	{Chen, Jiaoyan and Dong, Hang and Hastings, Janna and Jim\'{e}nez-Ruiz, Ernesto and L\'{o}pez, Vanessa and Monnin, Pierre and Pesquita, Catia and \v{S}koda, Petr and Tamma, Valentina},
  title =	{{Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{5:1--5:33},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.5},
  URN =		{urn:nbn:de:0030-drops-194791},
  doi =		{10.4230/TGDK.1.1.5},
  annote =	{Keywords: Knowledge graphs, Life science, Knowledge discovery, Explainable AI}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.38
Exascale Agent-Based Modelling for Policy Evaluation in Real-Time (ExAMPLER) (Short Paper)

Authors: Alison Heppenstall, J. Gary Polhill, Mike Batty, Matt Hare, Doug Salt, and Richard Milton

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
Exascale computing can potentially revolutionise the way in which we design and build agent-based models (ABM) through, for example, enabling scaling up, as well as robust calibration and validation. At present, there is no exascale computing operating with ABM (that we are aware of), but pockets of work using High Performance Computing (HPC). While exascale computing is expected to become more widely available towards the latter half of this decade, the ABM community is largely unaware of the requirements for exascale computing for agent-based modelling to support policy evaluation. This project will engage with the ABM community to understand what computing resources are currently used, what we need (both in terms of hardware and software) and to set out a roadmap by which to make it happen.
Cite as

Alison Heppenstall, J. Gary Polhill, Mike Batty, Matt Hare, Doug Salt, and Richard Milton. Exascale Agent-Based Modelling for Policy Evaluation in Real-Time (ExAMPLER) (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 38:1-38:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{heppenstall_et_al:LIPIcs.GIScience.2023.38,
  author =	{Heppenstall, Alison and Polhill, J. Gary and Batty, Mike and Hare, Matt and Salt, Doug and Milton, Richard},
  title =	{{Exascale Agent-Based Modelling for Policy Evaluation in Real-Time (ExAMPLER)}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{38:1--38:5},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.38},
  URN =		{urn:nbn:de:0030-drops-189334},
  doi =		{10.4230/LIPIcs.GIScience.2023.38},
  annote =	{Keywords: Exascale computing, Agent-Based Modelling, Policy evaluation}
}
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