A Taxonomy of Anomalies in Distributed Cloud Systems: The CRI-Model

2017 ◽  
pp. 247-261
Author(s):  
Kim Reichert ◽  
Alexander Pokahr ◽  
Till Hohenberger ◽  
Christopher Haubeck ◽  
Winfried Lamersdorf
Keyword(s):  
Cloud Systems ◽  
Distributed Cloud

Adaptive priority-based data placement and multi-task scheduling in geo-distributed cloud systems

2021 ◽  
Vol 224 ◽  
pp. 107050
Author(s):  
Chunlin Li ◽  
Jun Liu ◽  
Weigang Li ◽  
Youlong Luo
Keyword(s):  
Task Scheduling ◽  
Data Placement ◽  
Cloud Systems ◽  
Distributed Cloud

Towards Federation and Interoperability of Cloud Storage Systems

2013 ◽  
pp. 60-71 ◽  
Author(s):  
Sebastian Dippl ◽  
Michael C. Jaeger ◽  
Achim Luhn ◽  
Alexandra Shulman-Peleg ◽  
Gil Vernik
Keyword(s):  
Big Data ◽  
Cloud Storage ◽  
Storage Systems ◽  
Network Throughput ◽  
Use Cases ◽  
Single System ◽  
Cloud Systems ◽  
Logical Conclusion ◽  
Big Data Applications ◽  
Distributed Cloud

While it is common to use storage in a cloud-based manner, the question of true interoperability is rarely fully addressed. This question becomes even more relevant since the steadily growing amount of data that needs to be stored will supersede the capacity of a single system in terms of resources, availability, and network throughput quite soon. The logical conclusion is that a network of systems needs to be created that is able to cope with the requirements of big data applications and data deluge scenarios. This chapter shows how federation and interoperability will fit into a cloud storage scenario. The authors take a look at the challenges that federation imposes on autonomous, heterogeneous, and distributed cloud systems, and present approaches that help deal with the special requirements introduced by the VISION Cloud use cases from healthcare, media, telecommunications, and enterprise domains. Finally, the authors give an overview on how VISION Cloud addresses these requirements in its research scenarios and architecture.

Joint Scheduling of Data and Computation in Geo-Distributed Cloud Systems

2015 ◽  
Author(s):  
Lingyan Yin ◽  
Jizhou Sun ◽  
Laiping Zhao ◽  
Chenzhou Cui ◽  
Jian Xiao ◽  
...  
Keyword(s):  
Cloud Systems ◽  
Distributed Cloud

scholarly journals Understanding and Statically Detecting Synchronization Performance Bugs in Distributed Cloud Systems

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 99123-99135
Author(s):  
Chen Zhang ◽  
Jiaxin Li ◽  
Dongsheng Li ◽  
Xicheng Lu
Keyword(s):  
Cloud Systems ◽  
Distributed Cloud ◽  
Performance Bugs ◽  
Synchronization Performance

Towards Federation and Interoperability of Cloud Storage Systems

2015 ◽  
pp. 423-434
Author(s):  
Sebastian Dippl ◽  
Michael C. Jaeger ◽  
Achim Luhn ◽  
Alexandra Shulman-Peleg ◽  
Gil Vernik
Keyword(s):  
Big Data ◽  
Cloud Storage ◽  
Storage Systems ◽  
Network Throughput ◽  
Use Cases ◽  
Single System ◽  
Cloud Systems ◽  
Logical Conclusion ◽  
Big Data Applications ◽  
Distributed Cloud

While it is common to use storage in a cloud-based manner, the question of true interoperability is rarely fully addressed. This question becomes even more relevant since the steadily growing amount of data that needs to be stored will supersede the capacity of a single system in terms of resources, availability, and network throughput quite soon. The logical conclusion is that a network of systems needs to be created that is able to cope with the requirements of big data applications and data deluge scenarios. This chapter shows how federation and interoperability will fit into a cloud storage scenario. The authors take a look at the challenges that federation imposes on autonomous, heterogeneous, and distributed cloud systems, and present approaches that help deal with the special requirements introduced by the VISION Cloud use cases from healthcare, media, telecommunications, and enterprise domains. Finally, the authors give an overview on how VISION Cloud addresses these requirements in its research scenarios and architecture.

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