A Middleware Protocol for Time-Critical Wireless Communication of Large Data Samples

Abstract

We present a middleware-based protocol that reliably synchronizes large samples consisting of multiple frames efficiently and within application level QoS requirements over a lossy wireless channel. The protocol uses a custom retransmission scheme, exploiting the latency requirements on sample level for frame level scheduling. It can be integrated into the popular DDS middleware. We investigate some technical limits of such a protocol and compare it to existing error protocols in the software stack and in the wireless protocol and combinations thereof. The comparison is based on an Omnet++ simulation using an established wireless channel error model. For evaluation, we take a use case from automated valet parking where infrastructure data provided via a wireless link augments in-vehicle sensor data. The use case respects the related safety requirements. Results show that the application awareness of the presented protocol, significantly improves service availability by transmitting data efficiently in time even under higher frame error rates.

Hard Real-Time Streaming of Large Data Objects with Overlapping Backward Error Correction

“…Future automation applications such as highly automated driving are expected to rely on Vehicle-to-Everything (V2X) communication and similar concepts, with automotive use cases ranging from infrastructure supported applications such as valet parking [1] to out-of-coverage scenarios like truck platooning on highways [2]. While so far only applications exchanging small data have been specified [3], future automation and V2X use cases according to surveys and roadmaps will rely on cooperative perception, meaning large quantities of raw or preprocessed sensor data will be exchanged between participants [4]- [7].…”

“…We refer to such data as samples S that, due to their size, will be transmitted in fragments. State-of-the-art packet-based transmission schemes are largely unaware of large sample structures, which affects error handling as demonstrated in [1].…”

“…Means of error correction for use cases requiring the exchange of large samples in inherently lossy wireless channels have already been addressed in [1]. [1] managed to significantly improve upon existing Backward Error Correction (BEC) mechanisms.…”

“…Means of error correction for use cases requiring the exchange of large samples in inherently lossy wireless channels have already been addressed in [1]. [1] managed to significantly improve upon existing Backward Error Correction (BEC) mechanisms. Those existing BEC mechanisms (e.g., such as found in wireless communication (802.11 and cellular) standards [9], [10]) only address reliability on a per-fragment basis as they are applied at the MAC-layer.…”

“…Those existing BEC mechanisms (e.g., such as found in wireless communication (802.11 and cellular) standards [9], [10]) only address reliability on a per-fragment basis as they are applied at the MAC-layer. In contrast, the Wireless Reliable Real-Time Protocol (W2RP) protocol in [1] exploits BEC mechanisms provided by the popular Data Distribution Service (DDS) [11] middleware and its 'wire' Real-Time Publish-Subscribe (RTPS) protocol [12]. DDS gained popularity due to its use in the Robot Operating System 2 (ROS2) [13] and is also specified as part of the automotive AUTOSAR platform for in-vehicle communication [14].…”