The technological advancements of recent years have steadily increased the complexity of vehicle-internal software systems, and the ongoing development towards autonomous driving will further aggravate this situation. This is leading to a level of complexity that is pushing the limits of existing vehicle software architectures and system designs. By changing the software structure to a service-based architecture, companies in other domains successfully managed the rising complexity and created a more agile and future-oriented development process. This paper presents a case-study investigating the feasibility and possible effects of changing the software architecture for a complex driver assistance function to a microservice architecture. The complete procedure is described, starting with the description of the software-environment and the corresponding requirements, followed by the implementation, and the final testing. In addition, this paper provides a high-level evaluation of the microservice architecture for the automotive use-case. The results show that microservice architectures can reduce complexity and time-consuming process steps and makes the automotive software systems prepared for upcoming challenges as long as the principles of microservice architectures are carefully followed.
Another publish-subscribe middleware called Chromosome and a centralized platform architecture for automotive applications, called Race, have similarities with the above approach and with this work @cite_9 . It is a central computing architecture, which is supporting on the software and network level.
@cite_9
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In this work we present a middleware architecture for a mobile peer-to-peer content distribution system. Our architecture allows wireless content dissemination between mobile nodes without relying on infrastructure support. Contents are exchanged opportunistically when nodes are within communication range. Applications access the service of our platform through a publish subscribe interface and therefore do not have to deal with low-level opportunistic networking issues or matching and soliciting of contents. Our architecture consists of three key components. A content structure that facilitates dividing contents into logical topics and allows for efficient matching of content lookups and downloading under sporadic node connectivity. A solicitation protocol that allows nodes to solicit content meta-information in order to discover contents available at a neighboring node and to download content entries disjointedly from different nodes. An API that allows applications to access the system services through a publish subscribe interface. In this work we describe the design and implementation of our architecture. We also discuss potential applications and present evaluation results from profiling of our system. Distributed graph processing platforms have helped emerging application domains use commodity clusters and Clouds to analyze large graphs. Vertex-centric programming models like Google Pregel, and their subgraph-centric variants, specify data-parallel application logic for a single vertex or component that execute iteratively. The locality and balancing of components within partitions affects the performance of such platforms. We propose three partitioning strategies for a subgraph-centric model, and analyze their impact on CPU utilization, communication, iterations, and makespan. We analyze these using Breadth First Search and PageRank algorithms on powerlaw and spatio-planar graphs. They are validated on a commodity cluster using our GoFFish subgraph-centric platform, and compared against Apache Giraph vertex-centric platform. Our experiments show upto 8 times improvement in utilization resulting to upto 5 times improvement of overall makespan for flat and hierarchical partitioning over the default strategy due to improved machine utilization. Further, these also exhibit better horizontal scalability relative to Giraph. In the last couple of years software functionality of modern cars increased dramatically. This growing functionality leads directly to a higher complexity of development and configuration. Current studies show that the amount of software will continue to grow. Additionally, advanced driver assistance systems (ADAS) and autonomous functionality, such as highly and fully automated driving or parking, will be introduced. Many of these new functions require access to different communication domains within the car, which increases system complexity. AUTOSAR, the software architecture established as a standard in the automotive domain, provides no methodologies to reduce this kind of complexity and to master new challenges. One solution for these evolving systems is developed in the RACE project. Here, a centralized platform computer (CPC) is introduced, which is inspired by the well-established approach used in other domains like avionics and automation. The CPC establishes a generic safety-critical execution environment for applications, providing interfaces for test and verification as well as a reliable communication infrastructure to smart sensors and actuators. A centralized platform also significantly reduces the complexity of integration and verification of new applications, and enables the support for Plug&Play. Abstract In recent years a considerable effort has been spent by research and industrial communities in the digitalization of production environments with the main objective of achieving a new automation paradigm, more flexible, responsive to changes, and safe. This paper presents the architecture, and discusses the benefits, of a distributed middleware prototype supporting a new generation of smart-factory-enabled applications with special attention paid to simulation tools. Devised within the scope of MAYA EU project, the proposed platform aims at being the first solution capable of empowering shop-floor Cyber-Physical-Systems (CPSs), providing an environment for their Digital Twin along the whole plant life-cycle. The platform implements a microservice IoT-Big Data architecture supporting the distributed publication of multidisciplinary simulation models, managing in an optimized way streams of data coming from the shop-floor for real-digital synchronization, ensuring security and confidentiality of sensible data.