Schedule Integration for Time-Triggered Systems Outline
Motivation • Automotive software • Automotive architectures • Integration Challenge Time-triggered automotive systems • Sychronization • Schedule Integration • FlexRay ILP scheduling approach Case study & Scalability Conclusion
2 Example: Adaptive Cruise Control
(AUDI AG, ACC)
Florian Sagstetter 3 Distributed Control System
Speed Adjustment Radar
Actuator System Sensor
Network Controller Network
ACC ECU
Florian Sagstetter 4 Delay Requirements
Sensor ts
Network m1
Controller tc
Network m2
Actuator ta
τnetwork τnetwork
τcontrol
Florian Sagstetter 5 Increasing Complexity in Automotive Electronics
400
350
300
250 240
200 175 150
90 100 100 100 50 13 50 1 3 5 0
Memory [MB] ECUs
Sources: Paul Milbredt, AUDI AG, EFTA 2010 - Switched FlexRay: Increasing the Effective Bandwidth and Safety of FlexRay Networks BMW Group, FTF 2010 Orlando - Energy Saving Strategies in Future Automotive E/E Architectures
Florian Sagstetter 6 Integration Challenge
Application: Implementation:
Sender Bus Receiver
Mapping, Configuration and Schedule
Integration:
Defined by: • Message • Timing • Deadline
Florian Sagstetter 7 Rising Gap between Required and Actual System Complexity
TODAY:
INTEGRATION CHALLENGE ?
Source: The Software Car: Information and Communication Technology (ICT) as an Engine for the Electromobility of the Future – ForTISS GmbH
Florian Sagstetter 8 Paradigm Shift
Event-triggered Time-triggered systems systems
utilization Ethernet (PTP) flexibility predictability
(real-time properties (real-time properties are guaranteed) need to be verified)
Florian Sagstetter 9 Introduction: Asynchronous vs. Synchronous
Jitter, lost/unused data Asynchronous task 1
bus x x
task 2
Synchronous task 1
bus
task 2
time
Florian Sagstetter 10 Vision: Holistic Scheduling for Time Triggered Systems
Sender Bus Receiver
Sender Ethernet PTP Bus (Backbone) Receiver Gate- way
Task level Sender Communication TT- Bus Bus controller Receiver
Florian Sagstetter 11 Related Work: Global Scheduling
• Schedule Optimization of Time-Triggered Systems Communicating Over the FlexRay Static Segment H. Zeng, M. Di Natale, A. Ghosal, and A. Sangiovanni-Vincentelli. IEEE Transactions on Industrial Informatics, 7(1):1–17, 2011.
• Modular Scheduling of Distributed Hetero- geneous Time-Triggered Automotive Systems. M. Lukasiewycz, R. Schneider, D. Goswami, and S. Chakraborty. In Proceedings of ASPDAC 2012, pages 665–670, 2012.
Florian Sagstetter 12 Schedule Integration approach
Cluster Schedules:
Sender Sender Sender Bus Bus Bus Receiver Receiver Receiver
Integration:
Sender
Bus
Receiver
Florian Sagstetter 13 Degrees of Freedom
Sender Schedules: Bus Receiver
Sender Sender Bus Bus Receiver Receiver
Global Schedule:
Sender
Bus x x
Receiver
Florian Sagstetter 14 Introduction to FlexRay
3.0
Release of version 3.0, Presentation: “FlexRay – Past Present Disbandment of Future Perfect” - Christopher Temple consortium Foundation of FlexRay Consortium Used in active damping (more than 100 members by 2005) system of BMW X5
2000 2005 2006 2008 2010 future ISO standard in preparation Release of version 2.1, Fully introduced with the current industry BMW 7 series standard
2.1
BMW 7-series Florian Sagstetter 15 FlexRay Protocol (Static Segment)
… CC0 (Communication Cycle) CC1 CCC
Dynamic Symbol Network Static Segment Segment Window Idle Time
Static Static … Static Slot 1 Slot 2 Slot n
Florian Sagstetter 16 Schedule Integration for FlexRay
CC0 CC1 CC2 CC3 … CCC
Static Static Static Static Segment Segment Segment Segment
x x+1 x+2 x x+1 x+2 x x+1 x+2 x x+1 x+2
Florian Sagstetter 17 ILP-based Schedule Integration Approach
Only occupy static FlexRay segment
Each static slot is only occupied once
Search Space Reduction: Filter Offsets: Cycle Breaking:
Florian Sagstetter 18 Case Study
cluster ECUs frames repetition variance body 2 9 2,4 3-217 chassis 3 12 2,4 0-85 information 2 11 4,8 9-278 electric 3 10 1,2 0-55 total 10 42 1,2,4,8 0-278
• Utilization of FlexRay bus: 29% • Feasible schedule for FlexRay 2.1 in 163ms (Xeon 3.2GHz Quadcore,12GB RAM) • ILP formulation of 5207 variables and 146926 constraints • Feasible schedule for FlexRay 3.0 in 208ms • ILP formulation of 14895 variables and 1070730 constraints
Florian Sagstetter 19 Scalability Analysis with 5400 Synthetic Test Cases
Florian Sagstetter 20 Conclusion
• Automotive functions benefit from a synchronous schedule
• Concurrent scheduling of ECUs and buses necessary
• Concurrent scheduling allows reduction of integration efforts
• ILP based scheduling
Florian Sagstetter 21