Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Marc Seidemann

dblp:164/3486 · DBLP profile ↗
← Back
3ranked-venue papers
2as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 100%
Databases, data mining, and information retrieval
1 paper
Data stream processing · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems
indexing
0.412019
ChronicleDB: A High-Performance Event Store · ACM Trans. Database Syst. 2019
Storage systems
storage reliability
0.412019
ChronicleDB: A High-Performance Event Store · ACM Trans. Database Syst. 2019
Data stream processing
event monitoring
0.112019
ChronicleDB: A High-Performance Event Store · ACM Trans. Database Syst. 2019

Methods — techniques the papers use, named apart from their topics

experimental evaluation · 0.8
YearPublicationVenuePosition
2019 ChronicleDB: A High-Performance Event Store
abstract
Reactive security monitoring, self-driving cars, the Internet of Things (IoT), and many other novel applications require systems for both writing events arriving at very high and fluctuating rates to persistent storage as well as supporting analytical ad hoc queries. As standard database systems are not capable of delivering the required write performance, log-based systems, key-value stores, and other write-optimized data stores have emerged recently. However, the drawbacks of these systems are a fair query performance and the lack of suitable instant recovery mechanisms in case of system failures. In this article, we present ChronicleDB, a novel database system with a storage layout tailored for high write performance under fluctuating data rates and powerful indexing capabilities to support a variety of queries. In addition, ChronicleDB offers low-cost fault tolerance and instant recovery within milliseconds. Unlike previous work, ChronicleDB is designed either as a serverless library to be tightly integrated in an application or as a standalone database server. Our results of an experimental evaluation with real and synthetic data reveal that ChronicleDB clearly outperforms competing systems with respect to both write and query performance.
Marc Seidemann, Nikolaus Glombiewski, Michael Körber, Bernhard Seeger
ACM Trans. Database Syst.1
2017 ChronicleDB: A High-Performance Event Store
Marc Seidemann, Bernhard Seeger
EDBT1
2017 Behavior Analysis for Safety and Security in Automotive Systems
abstract
The connection of automotive systems with other systems such as road-side units, other vehicles, and various servers in the Internet opens up new ways for attackers to remotely access safety relevant subsystems within connected cars. The security of connected cars and the whole vehicular ecosystem is thus of utmost importance for consumer trust and acceptance of this emerging technology. This paper describes an approach for on-board detection of unanticipated sequences of events in order to identify suspicious activities. The results show that this approach is fast enough for in-vehicle application at runtime. Several behavior models and synchronization strategies are analyzed in order to narrow down suspicious sequences of events to be sent in a privacy respecting way to a global security operations center for further in-depth analysis.
Roland Rieke, Marc Seidemann, Elise Kengni Talla, Daniel Zelle, Bernhard Seeger
PDP2