Formal analysis of the startup delay of SOME/IP service discovery

An automotive network needs to start up within the millisecond range. This includes the physical startup, the software boot time, and the configuration of the network. The introduction of Ethernet into the automotive industry expanded the design space drastically and is increasing the complexity of configuring every element in the network. To add more flexibility to automotive Ethernet networks, the concept of Service Discovery was migrated from consumer electronics to AUTOSAR within the SOME/IP middleware. A network is not fully functional until every client has found its service. Consequently, this time interval adds to the startup time of a network. This work presents a formal analysis model to calculate the waiting time of every client to receive the first offer from its service. The model is able to determine the worst case of a given parameter set. Based on this, a method for calculating the total startup time of a system is derived. The model is implemented in a free-to-use octave program and validated by comparing the analytical results to a timing-accurate simulation and an experimental setup. In every case the worst-case assumption holds true - the gap between the maximum of the simulation and the presented method is less than 1.3%.

[1]  Rolf Ernst,et al.  A Formal Approach to MpSoC Performance Verification , 2003, Computer.

[2]  Rolf Ernst,et al.  System Level Performance Analysis for Real-Time Automotive Multicore and Network Architectures , 2009, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[3]  Rene Queck.  Analysis of Ethernet AVB for automotive networks using Network Calculus , 2012, 2012 IEEE International Conference on Vehicular Electronics and Safety (ICVES 2012).

[4]  Eric Rondeau,et al.  Strict priority versus weighted fair queueing in switched Ethernet networks for time critical applications , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[5]  Jürgen Teich,et al.  Gateway Strategies for Embedding of Automotive CAN-Frames into Ethernet-Packets and Vice Versa , 2011, ARCS.

[6]  Robert B. Miller,et al.  Response time in man-computer conversational transactions , 1899, AFIPS Fall Joint Computing Conference.

[7]  Abdelsalam Helal,et al.  Standards for Service Discovery and Delivery , 2002, IEEE Pervasive Comput..

[8]  Rolf Ernst,et al.  Formal worst-case timing analysis of Ethernet topologies with strict-priority and AVB switching , 2012, 7th IEEE International Symposium on Industrial Embedded Systems (SIES'12).

[9]  Henrik Schiøler,et al.  Worst-Case Traversal Time Modelling of Ethernet Based In-Car Networks Using Real Time Calculus , 2011, NEW2AN.

[10]  Erik Guttman,et al.  Service Location Protocol: Automatic Discovery of IP Network Services , 1999, IEEE Internet Comput..

[11]  Rolf Ernst,et al.  System level performance analysis - the SymTA/S approach , 2005 .

[12]  Rolf Ernst,et al.  Improved formal worst-case timing analysis of weighted round robin scheduling for Ethernet , 2013, 2013 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

[13]  Eric Simon,et al.  Dynamic Web Services on a Home Service Platform , 2008, 22nd International Conference on Advanced Information Networking and Applications (aina 2008).

[14]  Rolf Ernst,et al.  Improving formal timing analysis of switched ethernet by exploiting traffic stream correlations , 2014, 2014 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

[15]  Lothar Thiele,et al.  Real-time calculus for scheduling hard real-time systems , 2000, 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353).

[16]  Alan Burns,et al.  Controller Area Network (CAN) schedulability analysis: Refuted, revisited and revised , 2007, Real-Time Systems.