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22 June 2023

17 Pages

Performance Enhancement of CAN/Ethernet Automotive Gateway with a CAN Data Reduction Algorithm

,
,
,
and
1
Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
2
Department of Computer Engineering, Kyungnam University, Changwon 51767, Republic of Korea
*
Author to whom correspondence should be addressed.
Electronics2023, 12(13), 2777;https://doi.org/10.3390/electronics12132777
This article belongs to the Special Issue Ubiquitous Sensor Networks, 2nd Edition
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Abstract

Data reduction (DR) techniques for the controller area network (CAN) are being developed to reduce the increased bus load caused by the growing number of electronic control units (ECUs) and automotive software complexity in modern automobiles. DR techniques enable the transmission of the same information with less bandwidth, effectively reducing the busload in CAN-based networks. Modern vehicles are composed of various in-vehicle network (IVN) protocols, such as CAN, local interconnect network (LIN), and Ethernet. However, existing DR techniques only consider the communication between CAN nodes. The application of DR techniques to a CAN bus may lead to compatibility issues when communicating with heterogeneous IVN protocols. This paper proposed a CAN/Ethernet gateway system for seamless communication with CAN DR. The proposed gateway system was implemented on a TC275-based embedded system, and its performance was evaluated and analyzed. The experimental results revealed that CAN DR compression effectively improves both the CAN bus load and end-to-end processing time of the gateway system. The CAN bus load was reduced by up to 33.68%, and the average end-to-end processing time was reduced to 336 μs.

1. Introduction

Electronic control units (ECUs) enable a wide range of features and requirements in modern vehicles. As a result, the number of ECUs in automobiles continuously grew to implement advanced functionality and meet safety standards. Some contemporary automobiles may have as many as 150 ECUs connected through various in-vehicle network (IVN) protocols, including the Controller Area Network (CAN), local interconnect network (LIN), FlexRay, and Ethernet [1]. As the number of ECUs in vehicles continues to rise, the associated data traffic on in-vehicle networks is increasing. The CAN is the dominant protocol for IVNs; however, its bandwidth is limited to 1 Mbps. This limitation can lead to CAN bus overload when data traffic is high, causing low-priority messages to experience increased latency and potentially miss deadlines [2]. Consequently, estimating the worst-case response times can be challenging, which can lead to critical issues in automotive networks.
The use of higher-bandwidth network protocols or the design of multi-bus networks are potential solutions for reducing bus loads. However, implementing these solutions requires significant changes to existing automotive network systems, potentially resulting in increased costs and reliability issues [3,4]. Another approach to address the increased data traffic on the CAN bus is the implementation of the CAN data reduction (DR) technique, also known as data compression. The basic concept of the DR is to transmit only the differences between the previous and current data instead of all data, as successive CAN data typically do not change frequently [5]. This reduction in transmitted data helps alleviate the load on the CAN bus. Compared to other solutions, the DR offers a cost advantage, as it can be implemented through software updates without requiring hardware changes [6].
Contemporary vehicles use various IVN protocols, and communication between these different protocols is essential [7,8,9]. However, existing CAN DR techniques primarily focus on the communication between CAN nodes, necessitating additional implementations to enable seamless communication with networks using other protocols. The implementation of CAN DR on all nodes using other protocols is inefficient. The implementation of CAN DR in the gateway system can solve this problem. The gateway system allows a CAN with DR to communicate with other protocols while using the DR technique. Additionally, the gateway system typically possesses higher computing power compared to normal ECUs, allowing for faster execution of compression and decompression processes.
This paper builds upon our work presented in [10] and extends the scope beyond merely measuring the compression efficiency of CAN DR algorithms. Its primary objective was to evaluate the impact of CAN DR in an automotive network with heterogeneous IVN protocols. To achieve this, the paper conducted comprehensive measurements and assessments of (de-)compression processing time at the gateway system, CAN message delay times, and CAN/Ethernet end-to-end processing times. The experimental results presented in this paper demonstrate the advantages of utilizing CAN DR in a vehicle network environment with multiple IVN protocols.
The rest of this paper is structured as follows: Section 2 provides a brief overview of related work. Section 3 describes the implementation of the gateway system. In Section 4, we present the experimental setup and discuss the results. Finally, Section 5 concludes the paper, summarizing and suggesting future research directions.

3. Proposed Gateway System

3.1. Gateway Implementation

3.1.1. Hardware Configuration

The implemented gateway system is shown in Figure 2. The gateway system implementation was carried out with an embedded system based on the TC275 MCU product developed by Infineon Technologies [30]. The TC275 MCU was based on the TriCore architecture and is designed for automotive and industrial applications.
Figure 2. Layout of the embedded board for implementation.
The comparisons of commercial evaluation gateway board and the proposed gateway system are shown in Table 4. The two evaluation boards manufactured by Infineon support CAN, CAN FD, LIN, FlexRay, and Ethernet protocols. The S32G3-VNP-RDB3, manufactured by NXP, supports CAN, CAN FD, LIN, FlexRay, and Ethernet TSN protocols. This embedded board provided four channels for CAN, and one channel for Ethernet. The TC275 MCU included CAN and Ethernet controllers. A limitation of the embedded system used in this paper was its lower memory capacity compared to commercial gateway boards.
Table 4. Comparison of the gateway development kit.

3.1.2. Software Configuration

The software architecture of the proposed gateway system was divided into three layers, as shown in Figure 3: a device driver layer, an interface layer, and gateway application layer. The device driver layer provided device drivers to control the hardware components in the hardware layer and included modules for communication, timer, and interrupts.
Figure 3. Software architecture of the gateway system.
The interface layer served as the interface between the gateway application and device driver layer. The gateway routing module and DR (de-)compressor program, which executed the DR algorithm, were implemented in the gateway application layer. The DR compressor decompressed the CAN messages and passed them to the routing module. It also compressed outgoing CAN messages and transmitted them through the CAN interface.

3.2. Data Reduction Mechanism

In the proposed gateway system, we used a modified version of the BFC algorithm on the original BFC algorithm described earlier. In the modified BFC algorithm used in the proposed gateway system, signals with a length of six bits or more, which were identified as BF signals, were compressed using the BFC technique, as in the original BFC algorithm. A detailed description of how to compress the BF signal was already provided in Section 2.2.3 of this paper and in [2].
The modified BFC algorithm differed from the original BFC algorithm in its compression of the NBF signals. In the modified BFC algorithm, NBF signals can be grouped into an NBF signal group with a maximum size of 8 bits. Grouping was performed according to the number and size of NBF signals in each CAN message. An NBF signal group was treated as one NBF signal, such that if one NBF signal in the group changed its value, all signals in the group were transmitted uncompressed. The overhead of grouping was not significant because the frequency of value changes for CAN message signals classified as NBF signals, such as headlight, gear, and engine statuses, was relatively low.
NBF signal group compression was accomplished by comparing the values of all signals within the signal group to their respective previous values. If even one signal in a group changed compared to the previous value, the BPC bit was set to ‘0’, and all signal values in the group were transmitted. Otherwise, only the BPC bit of the group was sent. The values of the NBF signals did not change frequently. Hence, grouping the NBF signals can reduce the number of BPC bits required.
The DR compressor in the proposed gateway system performed the decompression of the signals in the compressed CAN message. The DR compressor knew the order of the signals in each compressed CAN message using the CAN ID when the message was compressed. Therefore, the DR compressor can decompress a compressed signal by reading the appropriate number of bits, without the need for any special bits to classify the signal.
For BF signals, they are decompressed using the same method as the original BFC algorithm. In the case of a group of NBF signals, if the BPC bit is ‘0’, it indicates that one or more signals in the NBF signal group have changed. Consequently, the DR compressor reads additional bits and updates the value of each signal in the group to the buffer, considering the number of signals in the group and their respective lengths. Conversely, if the BPC bit is ‘1’, no action is taken as it signifies no change in the value of the signal within the NBF group.
Although research is ongoing into security mechanisms using CAN DR compression, the proposed gateway system does not consider security mechanisms [34,35].

3.3. Routing

The proposed gateway system provides two routing methods: PDU-based and signal-based routing. A typical automotive gateway system additionally provides a frame-based routing method. In frame-based routing, a message frame received on one network is forwarded to another network with only the frame format translation [9]. Routing is performed directly between each protocol interface in the interface layer [11]. However, the DR compression and decompression are conducted by the DR compressor in the gateway application layer. We did not implement frame-based routing in our proposed gateway system because the compressed CAN messages are sent as Ethernet messages without any modifications, which may not be compatible with the receiving network’s protocol.
The proposed gateway system utilized a routing module that performed PDU and a signal-based routing process. As the proposed system used a modified version of the CAN protocol with the DR algorithm, the received CAN messages must be decompressed before routing. In contrast, when routing an Ethernet message to a CAN network, the message was translated into CAN message(s) via a router before compression was performed.
Examples of routing sequences of the CAN/Ethernet message are shown in Figure 4 and Figure 5. Both examples illustrate PDU-based routing situations. The received CAN messages were converted into decompressed CAN messages by the DR compressor. Then, the routing module copied the CAN message ID and data of each CAN message into an Ethernet message based on the ID of the received CAN message. Due to the minimum frame length of Ethernet being 64 bytes, which was longer than the size of a single CAN data field (8 bytes), it was possible to include multiple PDUs within an Ethernet message. If the transmission conditions of the Ethernet message were satisfied, the message was forwarded to the Ethernet interface. However, when the gateway system received an Ethernet message that included multiple CAN PDUs, each PDU in the Ethernet message was translated into destination CAN messages using the routing module. Each CAN message must be compressed before it is sent to the CAN bus, which was performed by the DR compressor.
Figure 4. Example of the routing CAN to Ethernet.
Figure 5. Example of the routing Ethernet to CAN.

4. Results and Discussion

This section describes the experiments conducted to evaluate the performance of the proposed gateway system. To evaluate compression performance, we measured the number of bytes sent for each CAN message and the CAN bus load. Additionally, we measured the end-to-end transmission latency, as well as the compression and decompression processing time, to evaluate the delay caused by adding the compression and decompression processes.

4.1. Experimental Environment

An experimental environment was designed to evaluate the performance of the gateway system using an embedded system and two VN5610 devices, as illustrated in Figure 6. The configurations of the CAN and Ethernet network are listed in Table 5. The proposed gateway system utilized one CAN channel and one Ethernet channel. The gateway system was connected to a TC275-based ECU via an Ethernet switch. The TC275-based ECU was used to communicate the Ethernet messages with the gateway. The VN5610s, a USB-IVN interface module developed by Vector, were used to interface with the CANoe, an IVN analysis and simulation software. Two VN5610s were connected to the CAN bus and Ethernet network, respectively, to measure each network.
Figure 6. Experiment environment.
Table 5. Configuration of the used protocol.
In addition, the CANoe software was utilized to analyze the CAN bus and Ethernet network and to implement virtual CAN nodes. Within the CANoe-based environment, three virtual CAN nodes were implemented, with each node responsible for transmitting compressed CAN messages onto the CAN bus.
The CAN messages and signal values used in the experiments were based on actual vehicle driving data. Driving data of the KIA Morning (Picanto) were extracted by connecting the VN5640 device to the OBD-II terminal of the vehicle. The driving data were collected under two conditions: normal and rough driving. Rough driving conditions involved scenarios such as sudden acceleration and sudden stops. To simulate the CAN bus communication during driving, the values of the CAN message signals within the extracted bus data log were saved as comma-separated value (CSV) files, which were used to compress and transfer the data in the virtual CAN nodes. In addition, they were used to configure the Ethernet packets sent by the TC275-based ECU.
Six CAN IDs were selected from the extracted driving data and used in the experiment: 0xA0 (EngFrzFrm1), 0xA1 (EngFrzFrm2), 0x1F1 (TCS5), 0x316 (EMS11), 0x4B0 (WHL_SPD), and 0x4B1 (WHL_PUL). EngFrzFrm messages and EMS provide information related to engine control. The TCS5 message provided information related to traction control. The WHL_SPD and WHL_PUL messages provide information related to the car’s wheels [23]. These CAN message data were provided as bytes.
0xA1 and 0x1F1 messages were routed from Ethernet to CAN, while 0xA0, 0x316, 0x4B0, and 0x4B1 messages were routed from CAN to Ethernet. These routing rules were chosen arbitrarily for experimentation.

4.2. Performance Analysis

4.2.1. Compression Ratio and CAN Busload

To evaluate the compression performance of the DR algorithm used in the proposed gateway system, we analyzed the CAN message compression ratio and the CAN bus with and without data reduction.
In the CANoe-based environment, virtual CAN nodes transmit compressed CAN messages to the gateway at regular intervals of either 10 or 5 ms. To evaluate the reduction in CAN bus load, we varied the CAN message cycle to simulate different loads on the bus. The gateway also received Ethernet messages from the TC275-based ECUs, translated them into CAN messages, compressed them, and forwarded them to the CAN bus. CANoe was used to measure the length of data bytes in CAN messages and CAN bus load. It provided the capability of monitoring message transmission and reception times, message IDs, data byte lengths, and transmitted data.
The CAN bus log monitored using the CANoe is shown in Figure 7. These are screenshots captured without and with CAN DR compression, respectively. (1) represents the bus log of uncompressed CAN messages sent with a default data length of 8 bytes. (2) represents a bus log of compressed CAN messages sent with reduced data lengths using the DR algorithm.
Figure 7. Monitoring compressed and uncompressed on the CAN bus by CANoe.
To calculate the compression ratio, we measured the number of bytes sent for each message. The compression ratio is defined as follows:
C o m p r e s s i o n   r a t i o   ( % ) = ( 1 − #   o f   b y t e s   o f   c o m p r e s s e d   m s g #   o f   b y t e s   o f   o r i g i n a l   m s g ) × 100
In the CANoe simulation environment, we measured the number of CAN data bytes sent out on the CAN bus by virtual CAN nodes and the gateways. The compression ratios calculated for each message are listed in Table 6. The number of bytes sent was measured while each message was sent 20,000 times. Each message was sent with a default data length of 8 bytes when uncompressed. Therefore, the total number of data bytes for the original message per message ID was 160,000. The results demonstrate that the DR algorithm effectively reduced the number of data bytes transmitted over the CAN bus. In particular, the results show that the ID 0xA1 message, when compressed, transmitted 74.92% fewer data bytes than the original message in the measurement environment using normal driving data and provided a 74.85% compression ratio on rough driving data.
Table 6. Compression efficiencies.
The results also show that the compression ratio was dependent on the driving data, which were measured under driving conditions that intentionally included sudden acceleration and stopping to increase the size and frequency of the signal value changes. Therefore, in the rough driving data, the signal was less likely to be fully compressed compared with normal driving data because of the larger and more frequent changes in signal values.
In addition, the compression ratio of each CAN ID message depended on the properties of the data in the CAN message. For example, the 0x4B1 message showed the lowest compression ratio among all measured CAN message IDs in the experiment. The 0x4B1 message provided information regarding the wheel pulse sensor. The data field of the message consisted of five 8-bit signals, four 2-bit signals, and padding. Based on the collected driving data logs, it was observed that the signal values within the 0x4B1 message undergo more frequent changes compared to other CAN IDs messages. As a result, this led to a lower compression ratio of 36.98% for normal driving data and 35.65% for rough driving data.
The average value and standard deviation of the number of bytes transmitted during 20,000 transmissions for each CAN ID are shown in Table 7. It was observed that the compression ratio for each CAN ID in Table 6 was proportional to the average number of bytes transmitted in Table 7. Additionally, the standard deviation of the number of bytes transmitted was higher in rough driving conditions compared to normal driving. This indicates that there was greater variability in the values during the transfer of rough driving, resulting in a less consistent size of the compressed message.
Table 7. Measurement of the number of bytes transmitted with compression.
The reduction in the CAN bus load resulting from CAN data compression was measured. The bus load is defined as follows:
B u s l o a d   ( % ) = n u m b e r   o f   b i t s   s e n t   i n   a   s e c o n d b a u d r a t e   b p s ∗ 100
Bus load refers to the utilization of the CAN bus network. The peak load represents the maximum bus load. Comparisons of the measured CAN bus peak loads are shown in Figure 8 and Figure 9. The peak load was measured using the CANoe tool in the experimental environment to obtain compression efficiency. With the implementation of the CAN DR, the peak load can be reduced by 33.43% for normal driving data in a 10 ms message cycle. However, in rough driving conditions, where the signal value in the CAN message may change more rapidly, the compression efficiency for rough driving data may be slightly reduced. Nonetheless, the peak load can still be reduced by 30.42%. The bus load increased with a shorter CAN message cycle, as shown in Figure 8. Using the CAN DR algorithm resulted in a 33.68% reduction in the peak load for normal driving data and 31.79% reduction for rough driving data.
Figure 8. Comparison of CAN bus peak load (CAN message cycle is 10 ms).
Figure 9. Comparison of CAN bus peak load (CAN message cycle is 5 ms).

4.2.2. Processing and Delay Time

To measure the processing time of the gateway system’s CAN message compression and decompression processes, we used timestamps generated by the gateway system itself. The CPU clock frequency of the gateway system was 200 Mhz. The compression and decompression processes were repeated 1000 times to measure the average and worst-case processing times, and the results are presented in Table 8. The compression process required an average of 2.04 μs, with the worst case taking 3.06 μs. The decompression process required an average of 1.53 μs, with the worst-case taking 3.24 μs.
Table 8. Compression and decompression processing time (μs).
To measure the CAN message delay when using the CAN DR, we used the CANoe measurement environment. In the CANoe environment, five CAN messages were transmitted from a virtual CAN node. The gateway converted the Ethernet message from TC275-based ECU and sent it on the CAN bus. All messages were sent at 10 ms intervals, and each message was repeated 10,000 times. The experiment was conducted twice, once without DR compression of the CAN messages and once with DR compression. The CAN message delay was measured using timestamps recorded in the CANoe measurement environment. The results are summarized in Table 9. The average delay time without compression was 236 μs, and the worst-case delay time was 287 μs. However, when employing compression, the average delay time was reduced to 143 μs, and the worst-case delay time was decreased to 205 μs. These results suggest that the overhead caused by compression and decompression processing time was negligible. Furthermore, the reduced data-byte length of the CAN message contributed to a decrease in the delay between CAN messages.
Table 9. Comparison of the CAN message delay times (μs).
We conducted measurements of the end-to-end processing time for each Ethernet–CAN message, both with and without CAN DR compression. The experimental setup for measuring the end-to-end processing time was the same as that for CAN message delay measurement environment described above. The end-to-end processing time was measured in the CANoe measurement environment. The measurement results for end-to-end processing time without and with CAN DR compression are shown in Figure 10 and Figure 11, respectively. A comparison of the end-to-end processing times is presented in Table 10. The experimental results show that without CAN DR compression, the average end-to-end processing time of the gateway system is 421 μs, with a worst-case of 793 μs.
Figure 10. Measurement result of the end-to-end processing time without DR compression (μs).
Figure 11. Measurement result of the end-to-end processing time with DR compression (μs).
Table 10. Comparison of the end-to-end processing time (μs).
However, when using CAN DR compression, the average end-to-end processing time decreased to 336 μs, with a worst-case processing time of 703 μs. The end-to-end processing time of Eth2CAN message is the sum of the Ethernet transfer time, gateway processing time, and CAN transfer time. The Ethernet transit time can be assumed to be constant. The gateway processing time includes routing time and the time required for converting the Ethernet message to a CAN message. If compression is used, the gateway processing time also includes the time needed for compression. The processing time of conversion to a CAN message benefits from the reduction in data bytes achieved through compression. Additionally, the gateway’s processing time can be delayed to accommodate previous tasks. Regarding the CAN transfer time, it is the delay caused by the ID-based arbitration of CAN communication [11]. Determining this delay time precisely is challenging due to the non-deterministic feature of CAN. In our experimental environment, the worst-case CAN message delay times were 287 μs without compression and 205 μs with compression, as shown in Table 9. This delay time is the time needed to send CAN frame. The transmission of other CAN ID messages can increase the E2E processing delay time. The peaks in the delay in Figure 10 and Figure 11 can be occurred by worst-case gateway processing time and worst-case CAN message delay caused by arbitration.

5. Conclusions

We implemented a mechanism for compressing/decompressing the CAN messages and CAN/Ethernet routing in the gateway using a TC275-based embedded system. Additionally, we demonstrated the compression and routing mechanisms in an experimental environment. Experimental measurements were presented to evaluate the impact of the CAN DR on heterogeneous networks: compression efficiency, CAN message delay time, (de-) compression processing time, and end-to-end processing time. The experimental results showed that CAN DR compression led to a reduction in the data byte length of the CAN message, resulting in decreased end-to-end processing time and CAN message delay in the gateway system. In our future work, we will investigate a secure gateway system that implements CAN security mechanisms using CAN compression.

Author Contributions

Conceptualization, S.B.O.; methodology, S.B.O.; software, S.B.O. and Y.S.D.; validation, S.B.O.; investigation, S.B.O., Y.S.D. and M.J.L.; resources, S.B.O., M.J.L. and J.H.K.; data curation, S.B.O.; writing—original draft preparation, S.B.O.; writing—review and editing, S.B.O.; visualization, S.B.O.; supervision, J.H.K. and J.W.J.; funding acquisition, J.W.J. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2021-0-01364, An intelligent system for 24/7 real-time traffics surveillance on edge devices).

Data Availability Statement

Not applicable.

Acknowledgments

The authors would like to thank the editors and all the reviewers for their valuable comments.

Conflicts of Interest

The authors declare no conflict of interest.

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