An analysis framework for network-code programs

Distributed real-time systems require a predictable and verifiable mechanism to control the communication medium. Current real-time communication protocols are typically in-dependent of the application and have intrinsic limitations that impede customizing or optimizing them for the application. Therefore, either the developer must adapt her application and work around these subtleties or she must limit the capabilities of the application being developed.Network Code, in contrast, is a more expressive and exible model that specifies real-time communication schedules as programs. By providing a programmable media access layer on the basis of TDMA, Network Code permits creating application-specific protocols that suit the particular needs of the application. However, this gain in exibility also incurs additional costs such as increased communication and run-time overhead. Therefore, engineering an application with network code necessitates that these costs are analyzed, quantified, and weighted against the benefit.In this work, we propose a framework to analyze network-code programs for commonly used metrics such as overhead, schedulability, and average waiting time. We introduce Timed Tree Communication Schedules, based on timed automata to model such programs and define metrics in the context of deterministic and probabilistic communication schedules. To demonstrate the utility of our framework, we study an inverted pendulum system and show that we can decrease the cumulative numeric error in the model's implementation through analyzing and improving the schedule based on the presented metrics.

[1]  Sanjay K. Bose,et al.  An Introduction to Queueing Systems , 2002, Springer US.

[2]  John Lygeros,et al.  Hybrid Systems: Modeling, Analysis and Control , 2008 .

[3]  José Alberto Fonseca,et al.  The FTT-CAN Protocol for Flexibility in Safety-Critical Systems , 2002, IEEE Micro.

[4]  Insup Lee,et al.  Network-Code Machine: Programmable Real-Time Communication Schedules , 2006, 12th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'06).

[5]  Insup Lee,et al.  Generating embedded software from hierarchical hybrid models , 2003 .

[6]  Katsuhisa Furuta,et al.  Swinging up a pendulum by energy control , 1996, Autom..

[7]  Rajeev Alur,et al.  A Theory of Timed Automata , 1994, Theor. Comput. Sci..

[8]  José Alberto Fonseca,et al.  The FTT-CAN protocol: why and how , 2002, IEEE Trans. Ind. Electron..

[9]  Hermann Kopetz,et al.  Real-time systems , 2018, CSC '73.

[10]  Robert L. Grossman,et al.  Timed Automata , 1999, CAV.

[11]  Jay K. Strosnider,et al.  Modeling bus scheduling policies for real-time systems , 1995, Proceedings 16th IEEE Real-Time Systems Symposium.

[12]  Insup Lee,et al.  Generating embedded software from hierarchical hybrid models , 2003, LCTES '03.

[13]  Hermann Kopetz,et al.  The fault-hypothesis for the time-triggered architecture , 2004, IFIP Congress Topical Sessions.

[14]  References , 1971 .

[15]  Ernesto Wandeler,et al.  Optimal TDMA time slot and cycle length allocation for hard real-time systems , 2006, Asia and South Pacific Conference on Design Automation, 2006..