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Göteborgs universitets publikationer

Systematic Evaluation of Three Data Marshalling Approaches for Distributed Software Systems

Författare och institution:
Hugo Sica de Andrade (Institutionen för data- och informationsteknik, Software Engineering (Chalmers), Chalmers); Federico Giaimo (Institutionen för data- och informationsteknik, Software Engineering (Chalmers), Chalmers); Christian Berger (Institutionen för data- och informationsteknik (GU)); Ivica Crnkovic (Institutionen för data- och informationsteknik, Software Engineering (Chalmers), Chalmers)
Publicerad i:
Proceedings of the 15th Workshop on Domain-Specific Modelling, s. 71-76
ISBN:
978-1-4503-3903-2
Publikationstyp:
Konferensbidrag, refereegranskat
Publiceringsår:
2015
Språk:
engelska
Fulltextlänk:
Sammanfattning (abstract):
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.
Ämne (baseras på Högskoleverkets indelning av forskningsämnen):
NATURVETENSKAP ->
Data- och informationsvetenskap ->
Programvaruteknik
Nyckelord:
Data marshalling, Distributed software systems, Self-adaptive data marshalling
Postens nummer:
229542
Posten skapad:
2016-01-04 13:01
Posten ändrad:
2016-07-07 08:54

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