RT-kubernetes: containerized real-time cloud computing

This paper presents RT-Kubernetes, a software architecture with the ability to deploy real-time software components within containers in cloud infrastructures. The deployment of containers with guaranteed CPU scheduling is obtained by using a hierarchical real-time scheduler based on the Linux SCHED_DEADLINE policy. Preliminary experimental results provide evidence that this new framework succeeds in providing timeliness guarantees in the target responsiveness range, while achieving strong temporal isolation among containers co-located on the same physical hosts.

[1]  Jörn Kuhlenkamp,et al.  Benchmarking elasticity of FaaS platforms as a foundation for objective-driven design of serverless applications , 2020, SAC.

[2]  Florin Pop,et al.  Near real-time scheduling in cloud-edge platforms , 2020, SAC.

[3]  Tommaso Cucinotta,et al.  Container-based real-time scheduling in the Linux kernel , 2019, SIGBED.

[4]  Luca Abeni,et al.  Hierarchical scheduling of real-time tasks over Linux-based virtual machines , 2019, J. Syst. Softw..

[5]  Luca Abeni,et al.  Deadline scheduling in the Linux kernel , 2016, Softw. Pract. Exp..

[6]  Chong Li,et al.  RT-Open Stack: CPU Resource Management for Real-Time Cloud Computing , 2015, 2015 IEEE 8th International Conference on Cloud Computing.

[7]  Insup Lee,et al.  Realizing Compositional Scheduling through Virtualization , 2012, 2012 IEEE 18th Real Time and Embedded Technology and Applications Symposium.

[8]  Insup Lee,et al.  Optimal virtual cluster-based multiprocessor scheduling , 2009, Real-Time Systems.

[9]  G. Lipari,et al.  Schedulability Analysis of Global Scheduling Algorithms on Multiprocessor Platforms , 2009, IEEE Trans. Parallel Distributed Syst..

[10]  James H. Anderson,et al.  Tardiness bounds under global EDF scheduling on a multiprocessor , 2005, 26th IEEE International Real-Time Systems Symposium (RTSS'05).

[11]  Insup Lee,et al.  Compositional real-time scheduling framework , 2004, 25th IEEE International Real-Time Systems Symposium.

[12]  Brian E. Carpenter,et al.  Differentiated services in the Internet , 2002, Proc. IEEE.

[13]  Jonathan Walpole,et al.  A measurement-based analysis of the real-time performance of linux , 2002, Proceedings. Eighth IEEE Real-Time and Embedded Technology and Applications Symposium.

[14]  Daniel F. García,et al.  Worst-case utilization bound for EDF scheduling on real-time multiprocessor systems , 2000, Proceedings 12th Euromicro Conference on Real-Time Systems. Euromicro RTS 2000.

[15]  Giorgio C. Buttazzo,et al.  Integrating multimedia applications in hard real-time systems , 1998, Proceedings 19th IEEE Real-Time Systems Symposium (Cat. No.98CB36279).

[16]  Stefan Savage,et al.  Processor capacity reserves: operating system support for multimedia applications , 1994, 1994 Proceedings of IEEE International Conference on Multimedia Computing and Systems.

[17]  J. Javier Gutiérrez,et al.  Response-Time Analysis of Multipath Flows in Hierarchically-Scheduled Time-Partitioned Distributed Real-Time Systems , 2020, IEEE Access.

[18]  Tommaso Cucinotta,et al.  Performance Modeling in Predictable Cloud Computing , 2020, CLOSER.

[19]  Dirk H. Hohndel,et al.  Internals of the RT Patch , 2007 .

[20]  Zheng Wang,et al.  An Architecture for Differentiated Services , 1998, RFC.