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Improving Bandwidth Efficiency with Self-Adaptation for Data Marshalling on the Example of a Self-Driving Miniature Car

Conference paper
Authors Federico Giaimo
Hugo Sica de Andrade
Christian Berger
Ivica Crnkovic
Published in Proceedings of the 2015 European Conference on Software Architecture Workshops Article No. 21
ISBN 978-1-4503-3393-1
Publisher Association for Computing Machinery (ACM)
Publication year 2015
Published at Department of Computer Science and Engineering (GU)
Institutionen för data- och informationsteknik, Software Engineering (GU)
Department of Computer Science and Engineering, Computing Science (GU)
Language en
Keywords Data marshalling, Self-adaptation, Cyber-physical systems, Self-driving cars, Communication, Publish/subscribe
Subject categories Computer Systems, Embedded Systems


Publish/subscribe communication is a common architectural design pattern in component-based software systems used in many of today’s cyber-physical systems to exchange information between distributed software components. These systems typically deal with an increased number of data transfers, with a risk of lacking resources. Our recent domain analysis for a lane-following algorithm of a self-driving miniature car unveiled that the actual “information increment” between two subsequently sent packets is often small. Such scenario enables possibilities for a more efficient data exchange by avoiding redundant and/or unnecessary information transfer. In this paper, we propose and evaluate our concept for “self-adaptive data marshalling” that transparently adapts data types in messages to be exchanged by analyzing the actual information increment. The approach could reduce the bandwidth usage by more than 50% in comparison to the current approach, and by approximately 33% compared to the use of the general-purpose compression library zlib.

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