Measurements As First-class Artifacts

Abstract
The emergence of programmable switches has sparked a significant amount of work on new techniques to perform more powerful measurement tasks, for instance, to obtain fine-grained traffic and performance statistics. Previous work has focused on the efficiency of these measurements alone and has neglected flexibility, resulting in solutions that are hard to reuse or repurpose and that often overlap in functionality or goals. In this paper, we propose the use of a set of reusable primitive building blocks that can be composed to express measurement tasks in a concise and simple way. We describe the rationale for the design of our primitives, that we have named MAFIA (Measurements As FIrst-class Artifacts), and using several examples we illustrate how they can be combined to realize a comprehensive range of network measurement tasks. Writing MAFIA code does not require expert knowledge of low-level switch architecture details. Using a prototype implementation of MAFIA, we demonstrate the applicability of our approach and show that the use of our primitives results in compiled code that is comparable in size and resource usage with manually written specialized P4 code, and can be run in current hardware.

Citation
Laffranchini, P., Rodrigues, L., Canini, M., & Krishnamurthy, B. (2019). Measurements As First-class Artifacts. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. doi:10.1109/infocom.2019.8737383

Acknowledgements
This work was partially supported by (FCT) and Feder projects with references PTDC/EEI- COM/29271/2017 (Cosmos) and UID/ CEC/ 50021/ 2019. Paolo Laffranchini was supported by a fellowship from the Erasmus Mundus Joint Doctorate in Distributed Computing (EMJD-DC) program funded by the European Commission (EACEA) (FPA 2012-0030). We thank David Walker and Leonid Ryzhyk for their constructive comments on this work.

Publisher
Institute of Electrical and Electronics Engineers (IEEE)

Conference/Event Name
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications

DOI
10.1109/INFOCOM.2019.8737383

arXiv
1901.05279

Additional Links
https://ieeexplore.ieee.org/document/8737383/https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8737383

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