Title: Chien-Chih(Paul) Chao
1Introduction of FlexRay
- Chien-Chih(Paul) Chao
- Chih-Chiang(Michael) Chang
- Instructor Dr. Ann Gordon-Ross
2Summary
- General Background
- Performance Analysis of FlexRay-based ECU
Networks - Motivations
- Basic framework
- Modeling FlexRay
- Case Study
- Conclusion
- FlexRay Schedule Optimization of the Static
Segment - Background Introduction
- Motivation
- Problem definition
- Methodology
- Experimental Results
- Conclusion
3General Background
A next generation automotive network
communications protocol.
First public release(Version 2.0) on Jun
2004. The latest version 3.0.1 was released on
Oct 2010.
- High bandwidth
- Flexibility
- Fault-tolerance
- Reliability
4General Background
- Controller Area Network(CAN)
- 10Mbps x 2 bandwidth
- Time-triggered for real-time transmission
- Event-triggered for low-priority data
- Synchronous
- Deterministic system design
- Bandwidth up to 1Mbps
- Contention resolved by priority.
- Asynchronous
- Acknowledgment and retransmission when message is
corrupted
5General Background
BMW X5 on 2006, BMW 5-Series, BMW 7-Series Audi
A8, Bentley Mulsanne, Rolls-Royce Ghost
6General Background
- How does it work?
- Dual channel - scalable system fault-tolerance
- Bus Guardian
- Interconnect topologies centralized or bus
7General Background
- Macrotick- the nodes own internal clock or
timer. - Microtick- a cluster wide synchronized clock.
8Performance Analysis of FlexRay-based ECU Networks
- Andrei Hagiescu, Unmesh D. Bordoloi, Samarjit
Chakraborty - Department of Computer Science, National
University of Singapore - Prahladavaradan Sampath, P. Vignesh V. Ganesan,
S. Ramesh - General Motors RD India Science Laboratory,
Bangalore - Design Automation Conference (DAC) 2007,
- San Diego, California, USA
9Motivation
- In a high-end car there are up to 70 electronic
control units (ECUs) exchanging up to 2500
signals. - Commonly used protocols include CAN, local
interconnection network(LIN). - Previous implementations of FlexRay using only
static segment, with the dynamic segment being
unutilized. - Dynamic part of protocol is more complex.
- The potential messages for dynamic segment is
more irregular. - Techniques for analyzing the static segment are
known(TDMA scheme).
10Basic Framework
11Difficulties in Modeling FlexRay
- A message cannot straddle two communication
cycles. - Once a task misses in the dynamic segment, it
will wait till the next cycle. - A task can send at most one message in each
dynamic segment. - One minislot is consumed from the available
service when a task is not ready to transfer a
message.
12Modeling FlexRay
- Step 1 Extract k1 minislots of service during
each communication cycle from ?l . - Step 2 Discretize the service bound obtained
from step 1. - Step 3 The resulting service bound is shifted by
d time units. - Step 4A minislot is lost even when a task does
not transmit any message.
13Modeling FlexRay
14Case Study
- Adaptive Cruise Control application.
- Implemented framework using Matlab as a
front-end. - Using Java to handle all the function
transformation.
15Results
16Conclusion
- Present a compositional performance model for a
network of ECUs communicating via FlexRay bus. - Formal model of the protocol governing the
dynamic segment of FlexRay. - The framework can also be used for deriving the
parameters of the FlexRay protocol. - Help in resource dimensioning and determining
optimal scheduling policies for multitasking ECUs.
17FlexRay Schedule Optimization of the Static
Segment
- Martin Lukasiewycz, Michael Glaß, and Jürgen
Teich - University of Erlangen-Nuremberg, Germany
- Paul Milbredt
- I/EE-81, AUDI AG, German
- CODESISSS 2009, Grenoble, France
18Quick View
- Presenting a Scheduling Optimization scheme for
the static segment of the FlexRay bus in
compliance with the AUTOSAR specification. - What is AUTOSAR?
19Background Introduction
- AUTOSAR
- AUTomotive Open System ARchitecture
- FlexRay
- An Automotive Communication System
- Protocol Data Units (PDUs)
20Background AUTOSAR
- AUTomotive Open System Architecture
- Open and Standardized automotive software
architecture - Partnership for automotive E/E (Electrics/Electron
ics) architectures - Standardization
- Basic systems functions,
- Scalability to different vehicle
- Transferability throughout the network
- Maintainability throughout the entire product
life-cycle - Etc.
21Background FlexRay
- Static Segment
- Time-triggered
- Enable a guaranteed real-time transmission of
critical data - Periodic and Safety-critical data
- Reserved slots for deterministic data that
arrives at a fixed period - Dynamic Segment
- Even-triggered
- For low priority data
- Maintenance and Diagnosis data
- does not require determinism
22Background FlexRay (Cont.)
- Communication Cycle
- Symbol WindowTypically used for network
maintenance and signaling for starting the
network. - Network Idle TimeA known "quiet" time used to
maintain synchronization between node clocks.
23Background FlexRay Static Seg.
24Background FlexRay Static Seg.
- Made up of n equally sized slots
- each slots is uniquely assigned to one node
- Node may occupy more than one slot
1
2
3
25Background FlexRay Static Seg.
- Each slot header, trailer, and payload segment
PDU
PDU
PDU
PDU
PDU
PDU
PDU
PDU
26Background PDUs
- The mechanism for communicating information
between protocols, they are most generally called
protocol data units (PDUs).
OSI Layer PDU Name
Application Data
Presentation Data
Session Data
Transport Segment
Network Packet
Data Link Frame
Physical Bits
27Motivation
- To minimize the number of used slots in order to
maximize the utilization of the bus - Scheduling optimization scheme for the static
segment of the FlexRay bus
28Problem definition
- Scheduling Problem
- Scheduling Requirements
- the static time-triggered segment
- Why optimization?
- high flexibility for incremental schedule changes
- for future automotive networks with a higher data
volume - fast scheduling techniques are necessary
- to allow for an effective parameter
exploration - AUTOSAR Interface Specification
- cycle multiplexing for a single slot
- maximizes the utilization of the
- static segment in compliance with
- the high requirements for reliability
- and robustness
29Methodology
30Methodology
Bin
Slot
Optimal
31Methodology
- Problem Transformation
- Transform the scheduling problem into a special
two-dimensional bin packing problem - 1 slot ?? 1 bin
- Constraints
32Methodology
- Bin Packing
- The Heuristic Approach
- Fast Greedy Heuristic
- Better with Unconstrained Problems
- ILP Approach
- Better with Constrained Problems
- Enhanced ILP
- Mutex Packing
- Add Mutual Exclusion to the bin packing
- Reordering
- For Extensibility of a bin and a slot
33Fast Greedy Heuristic
- Greedy implies Local Optimal ? Global Optimal
- To put elements into bins
- The Order of the elements (by height and weight)
- Allocated new empty bin
34Integer Linear Programming (ILP)
- Placing the elements starting from the highest
element to the most left void space in the bin s
at the level l results in a feasible solution of
the bin packing problem. - Enhanced ILP
- This constraint improves the runtime of the ILP
If the optimal solution is reached and equals the
lower bound, the optimization process terminates
immediately.
35Experimental Results
- Schedule Optimization
- Incremental Scheduling
- Scalability Analysis
- ILP Heuristic
- Slot Size Exploration
- Supportive Test Case
36Results - Schedule Optimization
- Intel Pentium 4 3.20 GHz machine with 512 MB RAM
- highly heterogeneous in terms of their period and
size - the only approach currently, TTX Plan
37Results - Incremental Scheduling
- In contrast to the ILP approach, the heuristic
scheduling method allows an incremental
scheduling. - An incremental scheduling might be favored if the
number of allocated slots is still not critical
since integration tests are time-consuming and
expensive.
38Results Scalability
39Results - Supportive Test Case
40Conclusion
- There exists no publication regarding the FlexRay
bus scheduling in compliance with the industrial
AUTOSAR Interface Specification. - The case study show that the heuristic and ILP
approach are superior to a commercial tool in
runtime and quality. - A supportive case study shows the flexibility and
robustness of the proposed algorithms
41Thank you!