Issue
Dagstuhl Reports, Volume 6, Issue 7
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Volume:
Dagstuhl Reports, Volume 6
Journal: Dagstuhl Reports (DagRep)
Publication Details
- published at: 2016-11-30
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- DBLP: db/journals/dagstuhl-reports/dagstuhl-reports6
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Document
Complete Issue
Dagstuhl Reports, Volume 6, Issue 7, July 2016, Complete Issue
Abstract
Dagstuhl Reports, Volume 6, Issue 7, July 2016, Complete Issue
Cite as
Dagstuhl Reports, Volume 6, Issue 7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@Article{DagRep.6.7,
title = {{Dagstuhl Reports, Volume 6, Issue 7, July 2016, Complete Issue}},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2016},
volume = {6},
number = {7},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.6.7},
URN = {urn:nbn:de:0030-drops-67716},
doi = {10.4230/DagRep.6.7},
annote = {Keywords: Dagstuhl Reports, Volume 6, Issue 7, July 2016, Complete Issue}
}
Document
Front Matter
Dagstuhl Reports, Table of Contents, Volume 6, Issue 7, 2016
Abstract
Table of Contents, Frontmatter
Cite as
Dagstuhl Reports, Volume 6, Issue 7, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@Article{DagRep.6.7.i,
title = {{Dagstuhl Reports, Table of Contents, Volume 6, Issue 7, 2016}},
pages = {i--ii},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2016},
volume = {6},
number = {7},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.6.7.i},
URN = {urn:nbn:de:0030-drops-67708},
doi = {10.4230/DagRep.6.7.i},
annote = {Keywords: Dagstuhl Reports, Table of Contents, Volume 6, Issue 7, 2016}
}
Document
Algorithmic Foundations of Programmable Matter (Dagstuhl Seminar 16271)
Abstract
his report documents the program and the outcomes of Dagstuhl Seminar 16271 "Algorithmic Foundations of Programmable Matter", a new and emerging field that combines theoretical work on algorithms with a wide spectrum of practical applications that reach all the way from small-scale embedded systems to cyber-physical structures at nano-scale.
The aim of the Dagstuhl seminar was to bring together researchers from the algorithms community with selected experts from robotics and distributed systems in order to set a solid base for the development of models, technical solutions, and algorithms that can control programmable matter. Both communities benefited from such a meeting for the following reasons:
- Meeting experts from other fields provided additional insights, challenges and focus when considering work on programmable matter.
- Interacting with colleagues in a close and social manner gave many starting points for continuing collaboration.
- Getting together in a strong, large and enthusiastic group provided the opportunity to plan a number of followup activities.
In the following, we provide details and activities of this successful week.
Cite as
Sándor Fekete, Andréa W. Richa, Kay Römer, and Christian Scheideler. Algorithmic Foundations of Programmable Matter (Dagstuhl Seminar 16271). In Dagstuhl Reports, Volume 6, Issue 7, pp. 1-14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@Article{fekete_et_al:DagRep.6.7.1,
author = {Fekete, S\'{a}ndor and Richa, Andr\'{e}a W. and R\"{o}mer, Kay and Scheideler, Christian},
title = {{Algorithmic Foundations of Programmable Matter (Dagstuhl Seminar 16271)}},
pages = {1--14},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2016},
volume = {6},
number = {7},
editor = {Fekete, S\'{a}ndor and Richa, Andr\'{e}a W. and R\"{o}mer, Kay and Scheideler, Christian},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.6.7.1},
URN = {urn:nbn:de:0030-drops-67599},
doi = {10.4230/DagRep.6.7.1},
annote = {Keywords: distributed algorithms, distributed systems, programmable matter, robotics, self-organization}
}
Document
Network Latency Control in Data Centres (Dagstuhl Seminar 16281)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 16281 "Network Latency Control in Data Centres". This seminar explored existing and future techniques for controlling data centre latency and thus explores research directions in the new field of data centre latency control in networking research. This need for a new research direction is motivated by the fact that traditional networking equipment and TCP-IP stacks were designed for wide-area networks, where the goal is to maximize throughput, and the control loop between end systems is measured in 10s of milliseconds. Consequently, this seminar discussed new research direction for data center latency control across the entire software and hardware stack, including in-network solutions, end-host solutions, and others.
Cite as
Mohammad Alizadeh Attar, Jon Crowcroft, Lars Eggert, and Klaus Wehrle. Network Latency Control in Data Centres (Dagstuhl Seminar 16281). In Dagstuhl Reports, Volume 6, Issue 7, pp. 15-30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@Article{alizadehattar_et_al:DagRep.6.7.15,
author = {Alizadeh Attar, Mohammad and Crowcroft, Jon and Eggert, Lars and Wehrle, Klaus},
title = {{Network Latency Control in Data Centres (Dagstuhl Seminar 16281)}},
pages = {15--30},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2016},
volume = {6},
number = {7},
editor = {Alizadeh Attar, Mohammad and Crowcroft, Jon and Eggert, Lars and Wehrle, Klaus},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.6.7.15},
URN = {urn:nbn:de:0030-drops-67605},
doi = {10.4230/DagRep.6.7.15},
annote = {Keywords: data centres, end-to-end transport protocols., latency, network architecture, resource control, scheduling}
}
Document
Topological Methods in Distributed Computing (Dagstuhl Seminar 16282)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 16282 "Topological Methods in Distributed Computing", which was attended by 22 international researchers, both junior and senior. In the last 10--15 years, there has been an increasing body of work on applications of topology in theoretical distributed computing. This seminar brought together computer scientists working in
theoretical distributed computing and mathematicians working in combinatorial topology, leading to interesting new collaborations. This report gathers abstracts of the talks given by the participants and of the group research sessions that happened during the seminar.
Cite as
Dmitry Feichtner-Kozlov and Damien Imbs. Topological Methods in Distributed Computing (Dagstuhl Seminar 16282). In Dagstuhl Reports, Volume 6, Issue 7, pp. 31-41, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@Article{feichtnerkozlov_et_al:DagRep.6.7.31,
author = {Feichtner-Kozlov, Dmitry and Imbs, Damien},
title = {{Topological Methods in Distributed Computing (Dagstuhl Seminar 16282)}},
pages = {31--41},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2016},
volume = {6},
number = {7},
editor = {Feichtner-Kozlov, Dmitry and Imbs, Damien},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.6.7.31},
URN = {urn:nbn:de:0030-drops-67614},
doi = {10.4230/DagRep.6.7.31},
annote = {Keywords: combinatorial topology, concurrency, distributed protocols, shared-memory communication, solvability}
}
Document
Data, Responsibly (Dagstuhl Seminar 16291)
Abstract
Big data technology promises to improve people's lives, accelerate
scientific discovery and innovation, and bring about positive societal
change. Yet, if not used responsibly, large-scale data analysis and
data-driven algorithmic decision-making can increase economic
inequality, affirm systemic bias, and even destabilize global markets.
While the potential benefits of data analysis techniques are well
accepted, the importance of using them responsibly - that is, in
accordance with ethical and moral norms, and with legal and policy
considerations - is not yet part of the mainstream research agenda
in computer science.
Dagstuhl Seminar "Data, Responsibly" brought together academic and
industry researchers from several areas of computer science, including
a broad representation of data management, but also data mining,
security/privacy, and computer networks, as well as social sciences
researchers, data journalists, and those active in government
think-tanks and policy initiatives. The goals of the seminar were to
assess the state of data analysis in terms of fairness, transparency
and diversity, identify new research challenges, and derive an agenda
for computer science research and education efforts in responsible
data analysis and use. While the topic of the seminar is
transdisciplinary in nature, an important goal of the seminar was to
identify opportunities for high-impact contributions to this important
emergent area specifically from the data management community.
Cite as
Serge Abiteboul, Gerome Miklau, Julia Stoyanovich, and Gerhard Weikum. Data, Responsibly (Dagstuhl Seminar 16291). In Dagstuhl Reports, Volume 6, Issue 7, pp. 42-71, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@Article{abiteboul_et_al:DagRep.6.7.42,
author = {Abiteboul, Serge and Miklau, Gerome and Stoyanovich, Julia and Weikum, Gerhard},
title = {{Data, Responsibly (Dagstuhl Seminar 16291)}},
pages = {42--71},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2016},
volume = {6},
number = {7},
editor = {Abiteboul, Serge and Miklau, Gerome and Stoyanovich, Julia and Weikum, Gerhard},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.6.7.42},
URN = {urn:nbn:de:0030-drops-67644},
doi = {10.4230/DagRep.6.7.42},
annote = {Keywords: Data responsibly, Big data, Machine bias, Data analysis, Data management, Data mining, Fairness, Diversity, Accountability, Transparency, Personal information management, Ethics, Responsible research, Responsible innovation, Data science education}
}