International Center for Computational Logic - Benutzerbeiträge [de]

Inproceedings3147/en

2017-06-01T06:35:39Z

Alexander Krause: Page created automatically by parser function on page Inproceedings3147

#REDIRECT [[Inproceedings3147]]

Inproceedings3147

2017-06-01T06:35:39Z

Alexander Krause: Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorVorname=Alexander |ErsterAutorNachname=Krause |FurtherAuthors=Thomas Kissinger; Dirk Habich; Wolfgang Lehner }} {{Inproc…“

{{Publikation Erster Autor
|ErsterAutorVorname=Alexander
|ErsterAutorNachname=Krause
|FurtherAuthors=Thomas Kissinger; Dirk Habich; Wolfgang Lehner
}}
{{Inproceedings
|Referiert=1
|Title=Asynchronous Graph Pattern Matchong on Multiprocessor Systems
|To appear=1
|Year=2017
|Month=September
|Booktitle=21st European Conference on Advances in Databases and Information Systems, Nicosia, Cyprus
}}
{{Publikation Details
|Abstract=Pattern matching on large graphs is the foundation for a variety of application domains. Strict latency requirements and continuously increasing graph sizes demand the usage of highly parallel in-memory graph processing engines that need to consider non-uniform memory access (NUMA) and concurrency issues to scale up on modern multiprocessor systems. To tackle these aspects, graph partitioning becomes increasingly important. Hence, we present a technique to process graph pattern matching on NUMA systems in this paper. As a scalable pattern matching processing infrastructure, we leverage a data-oriented architecture that preserves data locality and minimizes concurrency-related bottlenecks on NUMA systems. We show in detail, how graph pattern matching can be asynchronously processed on a multiprocessor system.
|Projekt=HAEC B08
|Forschungsgruppe=Wissensbasierte Systeme
}}

Inproceedings3146

2017-06-01T06:32:59Z

Alexander Krause:

{{Publikation Erster Autor
|ErsterAutorVorname=Alexander
|ErsterAutorNachname=Krause
|FurtherAuthors=Thomas Kissinger; Dirk Habich; Hannes Voigt; Wolfgang Lehner
}}
{{Inproceedings
|Referiert=1
|Title=Partitioning Strategy Selection for In-Memory Graph Pattern Matchign on Multiprocessor Systems
|To appear=1
|Year=2017
|Month=August
|Booktitle=23rd International Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain
}}
{{Publikation Details
|Abstract=Pattern matching on large graphs is the foundation for a variety of application domains. The continuously increasing size of the underlying graphs requires highly parallel in-memory graph processing engines that need to consider non-uniform memory access (NUMA) and concurrency issues to scale up on modern multiprocessor systems. To tackle these aspects, a fine-grained graph partitioning becomes increasingly important. Hence, we present a classification of graph partitioning strategies and evaluate representative algorithms on medium and large-scale NUMA systems in this paper. As a scalable pattern matching processing infrastructure, we leverage a data-oriented architecture that preserves data locality and minimizes concurrency-related bottlenecks on NUMA systems. Our in-depth evaluation reveals that the optimal partitioning strategy depends on a variety of factors and consequently, we derive a set of indicators for selecting the optimal partitioning strategy suitable for a given graph and workload.
|Download=Europar-2017.pdf
|Projekt=HAEC B08
|Forschungsgruppe=Wissensbasierte Systeme
}}

Inproceedings3146/en

2017-06-01T06:31:59Z

Alexander Krause: Page created automatically by parser function on page Inproceedings3146

#REDIRECT [[Inproceedings3146]]

Inproceedings3146

2017-06-01T06:31:59Z

{{Publikation Erster Autor
|ErsterAutorVorname=Alexander
|ErsterAutorNachname=Krause
|FurtherAuthors=Thomas Kissinger; Dirk Habich, Hannes Voigt, Wolfgang Lehner
}}
{{Inproceedings
|Referiert=1
|Title=Partitioning Strategy Selection for In-Memory Graph Pattern Matchign on Multiprocessor Systems
|To appear=1
|Year=2017
|Month=August
|Booktitle=23rd International Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain
}}
{{Publikation Details
|Abstract=Pattern matching on large graphs is the foundation for a variety of application domains. The continuously increasing size of the underlying graphs requires highly parallel in-memory graph processing engines that need to consider non-uniform memory access (NUMA) and concurrency issues to scale up on modern multiprocessor systems. To tackle these aspects, a fine-grained graph partitioning becomes increasingly important. Hence, we present a classification of graph partitioning strategies and evaluate representative algorithms on medium and large-scale NUMA systems in this paper. As a scalable pattern matching processing infrastructure, we leverage a data-oriented architecture that preserves data locality and minimizes concurrency-related bottlenecks on NUMA systems. Our in-depth evaluation reveals that the optimal partitioning strategy depends on a variety of factors and consequently, we derive a set of indicators for selecting the optimal partitioning strategy suitable for a given graph and workload.
|Download=Europar-2017.pdf
|Projekt=HAEC B08
|Forschungsgruppe=Wissensbasierte Systeme
}}

Datei:Europar-2017.pdf

2017-06-01T06:31:46Z

Alexander Krause:

Alexander Krause

2016-07-28T14:15:41Z

Alexander Krause:

{{Mitarbeiter
|Vorname=Alexander
|Nachname=Krause
|Akademischer Titel=Dipl.-Inf.
|Forschungsgruppe=Automatentheorie; Wissensbasierte Systeme
|Stellung=Wissenschaftlicher Mitarbeiter
|Ehemaliger=0
|Telefon=+49 351 469 43543
|Email=Alexander.Krause@tu-dresden.de
|Raum=APB 3053
|Bild=Alexander_Krause.jpg
|Info=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Info EN=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Publikationen anzeigen=1
|Abschlussarbeiten anzeigen=1
}}
{{Forschungsgebiet Auswahl}}

Alexander Krause

2016-07-08T08:48:57Z

Alexander Krause:

{{Mitarbeiter
|Vorname=Alexander
|Nachname=Krause
|Akademischer Titel=Dipl.-Inf.
|Forschungsgruppe=Automatentheorie; Wissensbasierte Systeme
|Stellung=Wissenschaftlicher Mitarbeiter
|Ehemaliger=0
|Email=Alexander.Krause@tu-dresden.de
|Raum=APB 3053
|Bild=Alexander_Krause.jpg
|Info=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Info EN=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Publikationen anzeigen=1
|Abschlussarbeiten anzeigen=1
}}
{{Forschungsgebiet Auswahl}}

Inproceedings3081

2016-06-03T06:37:20Z

Alexander Krause:

{{Publikation Erster Autor
|ErsterAutorVorname=Alexander
|ErsterAutorNachname=Krause
|FurtherAuthors=Hannes Voigt; Wolfgang Lehner
}}
{{Inproceedings
|Referiert=1
|Title=HUGS - A Lightweight Graph Partitioning Approach
|To appear=0
|Year=2016
|Month=Mai
|Booktitle=Proceedings of the 28th GI-Workshop Grundlagen von Datenbanken
}}
{{Publikation Details
|Abstract=The growing interest in graph data lead to increasingly more research in the field of graph data management and graph analytics. Nowadays, even large graphs of upto a size of billions of vertices and edges fit into main memory of big modern multisocket machines, making them a first-grade platform for graph management and graph analytics. High performance data management solutions have to be aware of the NUMA properties of such big machines. A data-oriented architecture (DORA) is a particular solution to that. However, it requires partitioning the data in a way such that inter-partition communication can be avoided.

Graph partitioning is a long studied problem and state-of-the-art solutions, such as multilevel k-way partitioning and recursive bisection achieve good results in feasible time. Integrating such solution is a rather difficult task, though. In this paper, we present a more lightweight approach called HUGS. The key idea of HUGS is to reuse the BFS routine present in a graph data management system anyway, since it is the foundation of many analytical graph algorithms. HUGS is not meant to produce a good general-purpose graph partitioning but good runtimes of BFS graph traversals such as reachability queries on DORA systems. In our experiments HUGS showed capable of finding good graph partitionings faster than state-of-the-art approaches. The partitioning found by HUGS also showed shorter runtimes for reachability queries.
|Download=Gvdb-2016.pdf
|Projekt=HAEC B08
|Forschungsgruppe=Wissensbasierte Systeme
}}

Inproceedings3081

2016-05-25T08:57:09Z

Alexander Krause:

{{Publikation Erster Autor
|ErsterAutorVorname=Alexander
|ErsterAutorNachname=Krause
|FurtherAuthors=Hannes Voigt; Wolfgang Lehner
}}
{{Inproceedings
|Referiert=1
|Title=HUGS - A Lightweight Graph Partitioning Approach
|To appear=0
|Year=2016
|Month=Mai
|Booktitle=Proceedings of the 28th GI-Workshop Grundlagen von Datenbanken
}}
{{Publikation Details
|Abstract=Nowadays, even large graphs of upto a size of billions of vertices and edges fit into main memory of big modern multisocket machines, making them a first-grade platform for graph management and graph analytics.
High performance data management solutions have to be aware of the NUMA properties of such big machines.
A data-oriented architecture (DORA) is a particular solution to that.
However, it requires partitioning the data in a way such that inter-partition communication can be avoided.

Graph partitioning is a long studied problem and state-of-the-art solutions, such as multilevel k-way partitioning and recursive bisection achieve good results in feasible time.
Integrating such solution is a rather difficult task, though.
In this paper, we present a more lightweight approach called HUGS.
The key idea of HUGS is to reuse the BFS routine present in a graph data management system anyway, since it is the foundation of many analytical graph algorithms.
HUGS is not meant to produce a good general-purpose graph partitioning but good runtimes of BFS graph traversals such as reachability queries on DORA systems.
In our experiments HUGS showed capable of finding good graph partitionings faster than state-of-the-art approaches.
The partitioning found by HUGS also showed shorter runtimes for reachability queries.
|Download=Gvdb-2016.pdf
|Projekt=HAEC B08
|Forschungsgruppe=Wissensbasierte Systeme
}}

Inproceedings3081

2016-05-23T13:43:50Z

Alexander Krause:

{{Publikation Erster Autor
|ErsterAutorVorname=Alexander
|ErsterAutorNachname=Krause
|FurtherAuthors=Hannes Voigt, Wolfgang Lehner
}}
{{Inproceedings
|Referiert=1
|Title=HUGS - A Lightweight Graph Partitioning Approach
|To appear=0
|Year=2016
|Month=Mai
|Booktitle=Grundlagen von Datenbanken Workshop
}}
{{Publikation Details
|Abstract=Nowadays, even large graphs of upto a size of billions of vertices and edges fit into main memory of big modern multisocket machines, making them a first-grade platform for graph management and graph analytics.
High performance data management solutions have to be aware of the NUMA properties of such big machines.
A data-oriented architecture (DORA) is a particular solution to that.
However, it requires partitioning the data in a way such that inter-partition communication can be avoided.

Graph partitioning is a long studied problem and state-of-the-art solutions, such as multilevel k-way partitioning and recursive bisection achieve good results in feasible time.
Integrating such solution is a rather difficult task, though.
In this paper, we present a more lightweight approach called HUGS.
The key idea of HUGS is to reuse the BFS routine present in a graph data management system anyway, since it is the foundation of many analytical graph algorithms.
HUGS is not meant to produce a good general-purpose graph partitioning but good runtimes of BFS graph traversals such as reachability queries on DORA systems.
In our experiments HUGS showed capable of finding good graph partitionings faster than state-of-the-art approaches.
The partitioning found by HUGS also showed shorter runtimes for reachability queries.
|Download=Gvdb-2016.pdf
|Projekt=HAEC B08
|Forschungsgruppe=Knowledge Systems
}}

Alexander Krause

2016-05-23T13:43:01Z

Alexander Krause:

{{Mitarbeiter
|Vorname=Alexander
|Nachname=Krause
|Akademischer Titel=Dipl.-Inf.
|Forschungsgruppe=Automatentheorie; Knowledge Systems
|Stellung=Wissenschaftlicher Mitarbeiter
|Ehemaliger=0
|Telefon=+49 351 463 43503
|Email=Alexander.Krause@tu-dresden.de
|Raum=APB 3031
|Bild=Alexander_Krause.jpg
|Info=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Info EN=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Publikationen anzeigen=1
|Abschlussarbeiten anzeigen=1
}}
{{Forschungsgebiet Auswahl}}

Inproceedings3081

2016-05-23T13:42:12Z

Alexander Krause:

{{Publikation Erster Autor
|ErsterAutorVorname=Alexander
|ErsterAutorNachname=Krause
|FurtherAuthors=Hannes Voigt, Wolfgang Lehner
}}
{{Inproceedings
|Referiert=1
|Title=HUGS - A Lightweight Graph Partitioning Approach
|To appear=0
|Year=2016
|Month=Mai
|Booktitle=Grundlagen von Datenbanken Workshop 2016
}}
{{Publikation Details
|Abstract=Nowadays, even large graphs of upto a size of billions of vertices and edges fit into main memory of big modern multisocket machines, making them a first-grade platform for graph management and graph analytics.
High performance data management solutions have to be aware of the NUMA properties of such big machines.
A data-oriented architecture (DORA) is a particular solution to that.
However, it requires partitioning the data in a way such that inter-partition communication can be avoided.

Graph partitioning is a long studied problem and state-of-the-art solutions, such as multilevel k-way partitioning and recursive bisection achieve good results in feasible time.
Integrating such solution is a rather difficult task, though.
In this paper, we present a more lightweight approach called HUGS.
The key idea of HUGS is to reuse the BFS routine present in a graph data management system anyway, since it is the foundation of many analytical graph algorithms.
HUGS is not meant to produce a good general-purpose graph partitioning but good runtimes of BFS graph traversals such as reachability queries on DORA systems.
In our experiments HUGS showed capable of finding good graph partitionings faster than state-of-the-art approaches.
The partitioning found by HUGS also showed shorter runtimes for reachability queries.
|Download=Gvdb-2016.pdf
|Projekt=HAEC B08
|Forschungsgruppe=Knowledge Systems
}}

Inproceedings3081/en

2016-05-23T13:40:14Z

Alexander Krause: Page created automatically by parser function on page Inproceedings3081

#REDIRECT [[Inproceedings3081]]

Inproceedings3081

2016-05-23T13:40:13Z

Alexander Krause: Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorVorname=Alexander |ErsterAutorNachname=Krause |FurtherAuthors=Hannes Voigt, Wolfgang Lehner }} {{Inproceedings |Referier…“

{{Publikation Erster Autor
|ErsterAutorVorname=Alexander
|ErsterAutorNachname=Krause
|FurtherAuthors=Hannes Voigt, Wolfgang Lehner
}}
{{Inproceedings
|Referiert=1
|Title=HUGS - A Lightweight Graph Partitioning Approach
|To appear=1
|Year=2016
|Month=Mai
|Booktitle=Grundlagen von Datenbanken Workshop 2016
}}
{{Publikation Details
|Abstract=Nowadays, even large graphs of upto a size of billions of vertices and edges fit into main memory of big modern multisocket machines, making them a first-grade platform for graph management and graph analytics.
High performance data management solutions have to be aware of the NUMA properties of such big machines.
A data-oriented architecture (DORA) is a particular solution to that.
However, it requires partitioning the data in a way such that inter-partition communication can be avoided.

Graph partitioning is a long studied problem and state-of-the-art solutions, such as multilevel k-way partitioning and recursive bisection achieve good results in feasible time.
Integrating such solution is a rather difficult task, though.
In this paper, we present a more lightweight approach called HUGS.
The key idea of HUGS is to reuse the BFS routine present in a graph data management system anyway, since it is the foundation of many analytical graph algorithms.
HUGS is not meant to produce a good general-purpose graph partitioning but good runtimes of BFS graph traversals such as reachability queries on DORA systems.
In our experiments HUGS showed capable of finding good graph partitionings faster than state-of-the-art approaches.
The partitioning found by HUGS also showed shorter runtimes for reachability queries.

|Download=Gvdb-2016.pdf
|Projekt=HAEC B08
|Forschungsgruppe=Knowledge Systems
}}

Datei:Gvdb-2016.pdf

2016-05-23T13:35:30Z

Alexander Krause:

Alexander Krause

2015-11-17T12:46:36Z

Alexander Krause:

{{Mitarbeiter
|Vorname=Alexander
|Nachname=Krause
|Akademischer Titel=Dipl.-Inf.
|Forschungsgruppe=Automatentheorie; Knowledge Systems
|Stellung=Wissenschaftlicher Mitarbeiter
|Ehemaliger=0
|Telefon=+49 351 463 43503
|Email=Alexander.Krause@tu-dresden.de
|Raum=APB 3031
|Bild=Alexander_Krause.jpg
|Info=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Info EN=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Publikationen anzeigen=0
|Abschlussarbeiten anzeigen=1
}}
{{Forschungsgebiet Auswahl}}

Alexander Krause

2015-10-27T14:08:35Z

Alexander Krause:

{{Mitarbeiter
|Vorname=Alexander
|Nachname=Krause
|Akademischer Titel=Dipl.-Inf.
|Forschungsgruppe=Automatentheorie; Knowledge Systems
|Stellung=Wissenschaftlicher Mitarbeiter
|Ehemaliger=0
|Telefon=+49 351 463 43503
|Email=Alexander.Krause@tu-dresden.de
|Raum=APB 3031
|Bild=Alexander_Krause.jpg
|Info=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Info EN=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Publikationen anzeigen=0
|Abschlussarbeiten anzeigen=0
}}
{{Forschungsgebiet Auswahl}}

Alexander Krause

2015-07-22T12:06:51Z

Alexander Krause:

{{Mitarbeiter
|Vorname=Alexander
|Nachname=Krause
|Akademischer Titel=Dipl.-Inf.
|Forschungsgruppe=Automatentheorie; Knowledge Systems
|Stellung=Wissenschaftlicher Mitarbeiter
|Ehemaliger=0
|Email=Alexander.Krause@tu-dresden.de
|Raum=APB 3030
|Bild=Alexander_Krause.jpg
|Info=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Info EN=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the [http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en HAEC Project], where I am doing my research including but not limited to the fields of distributed Graph Databases.
|Publikationen anzeigen=0
|Abschlussarbeiten anzeigen=0
}}
{{Forschungsgebiet Auswahl}}

Alexander Krause

2015-07-22T12:03:57Z

Alexander Krause:

{{Mitarbeiter
|Vorname=Alexander
|Nachname=Krause
|Akademischer Titel=Dipl.-Inf.
|Forschungsgruppe=Automatentheorie; Knowledge Systems
|Stellung=Wissenschaftlicher Mitarbeiter
|Ehemaliger=0
|Email=Alexander.Krause@tu-dresden.de
|Raum=APB 3030
|Bild=Alexander_Krause.jpg
|Info=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the <a href="http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en">HAEC Project</a>, where I am doing my research in the fields of distributed Graph Databases.
|Info EN=I did my my Diploma Thesis at TUD during the winter semester 2014/2015 about the topic "Framework for the Specification and Execution of Parallel Clustering Algorithms" at the Chair of Databases. After my graduation, I joind the <a href="http://tu-dresden.de/forschung/forschungskompetenz/sonderforschungsbereiche/sfb912/index_html/document_view?set_language=en">HAEC Project</a>, where I am doing my research in the fields of distributed Graph Databases.
|Publikationen anzeigen=0
|Abschlussarbeiten anzeigen=0
}}
{{Forschungsgebiet Auswahl}}

Alexander Krause

2015-07-22T12:03:31Z

Alexander Krause:

Alexander Krause

2015-07-22T11:54:07Z

Alexander Krause:

Alexander Krause

2015-07-22T11:51:04Z

Alexander Krause:

Datei:Alexander Krause.jpg

2015-07-22T11:47:05Z

Alexander Krause: