T-Systems’ powerful end-to-end solution optimizes the entire process and enables data to be used “as a service”, much to the delight of customers. The core components of the solution are edge computing resources, a central cloud platform, the Hadoop/Spark-compatible big data signal processing software and the Federated Spark system based on it. After completing the test drive, the measurement data (signals) are transferred to the big data cluster via Wi-Fi. This is located on the edge computing resources that are permanently installed at the test sites. They are managed and operated by T-Systems. Big data signal processing (BDSP) technology is also installed on the on-site systems. The BDSP pre-processes the measurement data, by transcoding the various collected data formats to established big data formats.
This can achieve up to 40 times faster processing for decoding and subsequent analysis than conventional tools. This is possible because BDSP enables parallel interpretation of the collected measurement results from distributed, binary, or textual trace files. In practice, the data is reduced in size by up to 90 percent. BDSP also offers support for resampling and tagging of signals and has an API that allows it to be connected to other systems. A central cloud with a Federated Spark system complements the edge part of the solution. This system provides engineers with access to measurement data – regardless of where it is located. The Federated Spark system automatically identifies the data for developers. In addition to finding the appropriate data, the developers also initiate the corresponding evaluations on the edge servers via the cloud. In other words, only instructions and results need to be transferred between the test sites and the developers' workstations, not the entire raw data sets. This eliminates the need for cost-intensive expansion of the MPLS network.
The solution also scores points for security
The measurement data is already stored in an encrypted form in the vehicle and remains highly encrypted and secured at all times. This also holds true for the transport layers including the transport protocols between the vehicle and edge resources as well as for access to the networks.