3 Search Results for "Kephart, Jeffrey O."


Document
JuMP2start: Time-Aware Stop-Start Technology for a Software-Defined Vehicle System

Authors: Anam Farrukh and Richard West

Published in: LIPIcs, Volume 298, 36th Euromicro Conference on Real-Time Systems (ECRTS 2024)


Abstract
Software-defined vehicle (SDV) systems replace traditional ECU architectures with software tasks running on centralized multicore processors in automotive-grade PCs. However, PC boot delays to cold-start an integrated vehicle management system (VMS) are problematic for time-critical functions, which must process sensor and actuator data within specific time bounds. To tackle this challenge, we present JuMP2start: a time-aware multicore stop-start approach for SDVs. JuMP2start leverages PC-class suspend-to-RAM techniques to capture a system snapshot when the vehicle is stopped. Upon restart, critical services are resumed-from-RAM within order of milliseconds compared to normal cold-start times. This work showcases how JuMP2start manages global suspension and resumption mechanisms for a state-of-the-art dual-domain vehicle management system comprising real-time OS (RTOS) and Linux SMP guests. JuMP2start models automotive tasks as continuable or restartable to ensure timing- and safety-critical function pipelines are reactively resumed with low latency, while discarding stale task state. Experiments with the VMS show that critical CAN traffic processing resumes within 500 milliseconds of waking the RTOS guest, and reaches steady-state throughput in under 7ms.

Cite as

Anam Farrukh and Richard West. JuMP2start: Time-Aware Stop-Start Technology for a Software-Defined Vehicle System. In 36th Euromicro Conference on Real-Time Systems (ECRTS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 298, pp. 1:1-1:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{farrukh_et_al:LIPIcs.ECRTS.2024.1,
  author =	{Farrukh, Anam and West, Richard},
  title =	{{JuMP2start: Time-Aware Stop-Start Technology for a Software-Defined Vehicle System}},
  booktitle =	{36th Euromicro Conference on Real-Time Systems (ECRTS 2024)},
  pages =	{1:1--1:27},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-324-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{298},
  editor =	{Pellizzoni, Rodolfo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2024.1},
  URN =		{urn:nbn:de:0030-drops-203046},
  doi =		{10.4230/LIPIcs.ECRTS.2024.1},
  annote =	{Keywords: Time-aware stop-start, Real-time power management, Suspend-to-RAM, Partitioning hypervisor, Vehicle management system, Vehicle-OS, Software-defined vehicles (SDV)}
}
Document
Track A: Algorithms, Complexity and Games
Optimal Non-Adaptive Cell Probe Dictionaries and Hashing

Authors: Kasper Green Larsen, Rasmus Pagh, Giuseppe Persiano, Toniann Pitassi, Kevin Yeo, and Or Zamir

Published in: LIPIcs, Volume 297, 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)


Abstract
We present a simple and provably optimal non-adaptive cell probe data structure for the static dictionary problem. Our data structure supports storing a set of n key-value pairs from [u]× [u] using s words of space and answering key lookup queries in t = O(lg(u/n)/lg(s/n)) non-adaptive probes. This generalizes a solution to the membership problem (i.e., where no values are associated with keys) due to Buhrman et al. We also present matching lower bounds for the non-adaptive static membership problem in the deterministic setting. Our lower bound implies that both our dictionary algorithm and the preceding membership algorithm are optimal, and in particular that there is an inherent complexity gap in these problems between no adaptivity and one round of adaptivity (with which hashing-based algorithms solve these problems in constant time). Using the ideas underlying our data structure, we also obtain the first implementation of a n-wise independent family of hash functions with optimal evaluation time in the cell probe model.

Cite as

Kasper Green Larsen, Rasmus Pagh, Giuseppe Persiano, Toniann Pitassi, Kevin Yeo, and Or Zamir. Optimal Non-Adaptive Cell Probe Dictionaries and Hashing. In 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 297, pp. 104:1-104:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{larsen_et_al:LIPIcs.ICALP.2024.104,
  author =	{Larsen, Kasper Green and Pagh, Rasmus and Persiano, Giuseppe and Pitassi, Toniann and Yeo, Kevin and Zamir, Or},
  title =	{{Optimal Non-Adaptive Cell Probe Dictionaries and Hashing}},
  booktitle =	{51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)},
  pages =	{104:1--104:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-322-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{297},
  editor =	{Bringmann, Karl and Grohe, Martin and Puppis, Gabriele and Svensson, Ola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2024.104},
  URN =		{urn:nbn:de:0030-drops-202471},
  doi =		{10.4230/LIPIcs.ICALP.2024.104},
  annote =	{Keywords: non-adaptive, cell probe, dictionary, hashing}
}
Document
Model-driven Algorithms and Architectures for Self-Aware Computing Systems (Dagstuhl Seminar 15041)

Authors: Samuel Kounev, Xiaoyun Zhu, Jeffrey O. Kephart, and Marta Kwiatkowska

Published in: Dagstuhl Reports, Volume 5, Issue 1 (2015)


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 15041 "Model-driven Algorithms and Architectures for Self-Aware Computing Systems". The design of self-aware computing systems calls for an integrated interdisciplinary approach building on results from multiple areas of computer science and engineering, including software and systems engineering, systems modeling, simulation and analysis, autonomic and organic computing, machine learning and artificial intelligence, data center resource management, and so on. The Dagstuhl Seminar 15041 served as a platform to raise the awareness about the relevant research efforts in the respective research communities as well as existing synergies that can be exploited to advance the state-of-the-art, formulate a new research agenda that takes a broader view on the problem following an integrated and interdisciplinary approach, and establish collaborations between academia and industry.

Cite as

Samuel Kounev, Xiaoyun Zhu, Jeffrey O. Kephart, and Marta Kwiatkowska. Model-driven Algorithms and Architectures for Self-Aware Computing Systems (Dagstuhl Seminar 15041). In Dagstuhl Reports, Volume 5, Issue 1, pp. 164-196, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)


Copy BibTex To Clipboard

@Article{kounev_et_al:DagRep.5.1.164,
  author =	{Kounev, Samuel and Zhu, Xiaoyun and Kephart, Jeffrey O. and Kwiatkowska, Marta},
  title =	{{Model-driven Algorithms and Architectures for Self-Aware Computing Systems (Dagstuhl Seminar 15041)}},
  pages =	{164--196},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2015},
  volume =	{5},
  number =	{1},
  editor =	{Kounev, Samuel and Zhu, Xiaoyun and Kephart, Jeffrey O. and Kwiatkowska, Marta},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.5.1.164},
  URN =		{urn:nbn:de:0030-drops-50385},
  doi =		{10.4230/DagRep.5.1.164},
  annote =	{Keywords: autonomic systems, self-adaptive, self-managing, model-driven, architecture-based, systems management, machine learning, feedback-based design}
}
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