Tue 27 Oct 2015 14:10 - 14:30 at Brighton 4 - Session 3

Cyber-physical systems like robots and self-driving vehicles comprise complex software systems. Their software is typically realized as distributed agents that are responsible for dedicated tasks like sensor data handling, sensor data fusion, or action planning. The modular design allows a flexible deployment as well as algorithm encapsulation to exchange software modules where needed. Such distributed software exchanges data using a data marshalling layer to serialize and deserialize data structures between a sending and receiving entity. In this article, we are systematically evaluating Google Protobuf, LCM, and our self-adaptive delta marshalling approach by using a generic description language, of which instances can be composed at runtime. Our results show that Google Protobuf performs well for small messages composed mainly by integral field types; the self-adaptive data marshalling approach is efficient if four or more fields of type double are present, and LCM outperforms both when a mix of many integral and double fields is used.

Tue 27 Oct
Times are displayed in time zone: Eastern Time (US & Canada) change

13:30 - 15:00: Session 3DSM at Brighton 4
13:30 - 13:50
Towards Improving Software Security using Language Engineering and mbeddr C
Markus Völteritemis, Germany, Zaur MolotnikovFortiss, Bernd Kolbitemis AG
Link to publication Pre-print Media Attached
13:50 - 14:10
Extensible Visual Constraint Language
Brian BrollVanderbilt University, Akos LedecziVanderbilt University
14:10 - 14:30
Systematic Evaluation of Three Data Marshalling Approaches for Distributed Software Systems
Hugo AndradeChalmers University of Technology, Federico GiaimoChalmers University of Technology, Christian BergerUniversity of Gothenburg, Ivica CrnkovicChalmers University of Technology, Sweden
14:30 - 15:00
Group work topic selection