3 Search Results for "Gerth, John"

Document
DOI: 10.4230/DagRep.13.5.114
Scalable Data Structures (Dagstuhl Seminar 23211)

Authors: Gerth Stølting Brodal, John Iacono, László Kozma, Vijaya Ramachandran, and Justin Dallant

Published in: Dagstuhl Reports, Volume 13, Issue 5 (2023)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23211 "Scalable Data Structures". Data structures enable the organization, storage and retrieval of data across a variety of applications. As they are deployed at unprecedented scales, data structures can profoundly affect the efficiency of almost all computational tasks. The study of data structures thus continues to be an important and active area of research with an interplay between data structure design and analysis, developments in computer hardware, and the needs of modern applications. The extended abstracts included in this report give a snapshot of the current state of research on scalable data structures and establish directions for future developments in the field.
Cite as

Gerth Stølting Brodal, John Iacono, László Kozma, Vijaya Ramachandran, and Justin Dallant. Scalable Data Structures (Dagstuhl Seminar 23211). In Dagstuhl Reports, Volume 13, Issue 5, pp. 114-135, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@Article{brodal_et_al:DagRep.13.5.114,
  author =	{Brodal, Gerth St{\o}lting and Iacono, John and Kozma, L\'{a}szl\'{o} and Ramachandran, Vijaya and Dallant, Justin},
  title =	{{Scalable Data Structures (Dagstuhl Seminar 23211)}},
  pages =	{114--135},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{5},
  editor =	{Brodal, Gerth St{\o}lting and Iacono, John and Kozma, L\'{a}szl\'{o} and Ramachandran, Vijaya and Dallant, Justin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.13.5.114},
  URN =		{urn:nbn:de:0030-drops-193676},
  doi =		{10.4230/DagRep.13.5.114},
  annote =	{Keywords: algorithms, big data, computational models, data structures, GPU computing, parallel computation}
}
Document
DOI: 10.4230/DagRep.11.1.1
Scalable Data Structures (Dagstuhl Seminar 21071)

Authors: Gerth Stølting Brodal, John Iacono, Markus E. Nebel, and Vijaya Ramachandran

Published in: Dagstuhl Reports, Volume 11, Issue 1 (2021)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 21071 "Scalable Data Structure". Even if the field of data structures is quite mature, new trends and limitations in computer hardware together with the ever-increasing amounts of data that need to be processed raise new questions with respect to efficiency and continuously challenge the existing models of computation. Thermal and electrical power constraints have caused technology to reach "the power wall" with stagnating single processor performance, meaning that all nontrivial applications need to address scalability with multiple processors, a memory hierarchy and other communication challenges. Scalable data structures are pivotal to this process since they form the backbone of the algorithms driving these applications. The extended abstracts included in this report contain both recent state of the art advances and lay the foundation for new directions within data structures research.
Cite as

Gerth Stølting Brodal, John Iacono, Markus E. Nebel, and Vijaya Ramachandran. Scalable Data Structures (Dagstuhl Seminar 21071). In Dagstuhl Reports, Volume 11, Issue 1, pp. 1-23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

Copy BibTex To Clipboard

@Article{brodal_et_al:DagRep.11.1.1,
  author =	{Brodal, Gerth St{\o}lting and Iacono, John and Nebel, Markus E. and Ramachandran, Vijaya},
  title =	{{Scalable Data Structures (Dagstuhl Seminar 21071)}},
  pages =	{1--23},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2021},
  volume =	{11},
  number =	{1},
  editor =	{Brodal, Gerth St{\o}lting and Iacono, John and Nebel, Markus E. and Ramachandran, Vijaya},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.11.1.1},
  URN =		{urn:nbn:de:0030-drops-143481},
  doi =		{10.4230/DagRep.11.1.1},
  annote =	{Keywords: algorithms, big data, data structures, GPU computing, large data sets, models of computation, parallel algorithms}
}
Document
DOI: 10.4230/DagSemProc.09211.5
Interactive Exploration of the Network Behavior of Personal Machines

Authors: Mike Sips, Sascha Simon, and John Gerth

Published in: Dagstuhl Seminar Proceedings, Volume 9211, Visualization and Monitoring of Network Traffic (2009)

Abstract
Personal machines are often the weakest points within a large network. Although they run an ever-increasing number of network services, these machines are often controlled by users who are unaware of security threats. Thus, a well-informed attacker can, with modest effort, identify and gain control over personal machines. However, system administrators need to know the tools and techniques used for attacks while simultaneously needing to invest huge analytical efforts to detect malicious behavior in the vast volumes of network traffic. In our research project we investigate the idea that an understanding of the regular behavior of personal machines can improve the chance of detecting the point in time when a machine shows malicious behavior. We propose a visual exploration system based on a data abstraction layer and temporal visual representations of the network traffic. The data abstraction layer enables an interactive change in the level of detail of the network traffic while temporal visualizations help system administrators to detect unexpected network traffic. In the next phase of this project, we will conduct experiments to get a good feel about the limits of our system in detecting malicious behavior in real-world scenarios.
Cite as

Mike Sips, Sascha Simon, and John Gerth. Interactive Exploration of the Network Behavior of Personal Machines. In Visualization and Monitoring of Network Traffic. Dagstuhl Seminar Proceedings, Volume 9211, pp. 1-4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

Copy BibTex To Clipboard

@InProceedings{sips_et_al:DagSemProc.09211.5,
  author =	{Sips, Mike and Simon, Sascha and Gerth, John},
  title =	{{Interactive Exploration of the Network Behavior of Personal Machines}},
  booktitle =	{Visualization and Monitoring of Network Traffic},
  pages =	{1--4},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9211},
  editor =	{Daniel A. Keim and Aiko Pras and J\"{u}rgen Sch\"{o}nw\"{a}lder and Pak Chung Wong},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09211.5},
  URN =		{urn:nbn:de:0030-drops-21565},
  doi =		{10.4230/DagSemProc.09211.5},
  annote =	{Keywords: Visualization, Communication Patterns, Data Abstraction, Personal Machines}
}
  • Refine by Author
  • 2 Brodal, Gerth Stølting
  • 2 Iacono, John
  • 2 Ramachandran, Vijaya
  • 1 Dallant, Justin
  • 1 Gerth, John
  • Show More...

  • Refine by Classification
  • 2 Theory of computation → Data structures design and analysis
  • 2 Theory of computation → Design and analysis of algorithms
  • 1 Theory of computation → Parallel algorithms

  • Refine by Keyword
  • 2 GPU computing
  • 2 algorithms
  • 2 big data
  • 2 data structures
  • 1 Communication Patterns
  • Show More...

  • Refine by Type
  • 3 document

  • Refine by Publication Year
  • 1 2009
  • 1 2021
  • 1 2023

Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2024 Schloss Dagstuhl – LZI GmbH Imprint Privacy Contact