Managing your Trees: Insights from a Metropolitan-Scale Low-Power Wireless Network
Paper i proceeding, 2014

Low-power wireless, such as IEEE 802.15.4, is envisioned as one key technology for wireless control and communication. In the context of the Advanced Metering Infrastructure (AMI), it serves as an energy-efficient communication technology for both communications at building-scale networks and city-scale networks. Understanding real-world challenges and key properties of 802.15.4 based networks is an essential requirement for both the research community and practitioners: When deploying and operating low-power wireless networks at metropolitan-scale, a deep knowledge is essential to ensure network availability and performance at production-level quality. Similarly, researchers require realistic network models when developing new algorithms and protocols. In this paper, we present new and real-world insights from a deployed metropolitan-scale low-power wireless network: It includes 300,000 individual wireless connected meters and covers a city with roughly 600,000 inhabitants. Our findings, for example, help to estimate real-world parameters such as the typical size of routing trees, their balance, and their dynamics over time. Moreover, these insights facilitate the understanding and the realistic calibration of simulation models in key properties such as reliability and throughput.

Smart grid

ZigBee

Advanced Metering Infrastructure

AMI

Författare

Zhang Fu

Chalmers, Data- och informationsteknik, Nätverk och system

Olaf Landsiedel

Chalmers, Data- och informationsteknik, Nätverk och system

Magnus Almgren

Chalmers, Data- och informationsteknik, Nätverk och system

Marina Papatriantafilou

Chalmers, Data- och informationsteknik, Nätverk och system

CCSES'14: Proceedings of the 3rd Workshop on Communications and Control for Smart Energy Systems held in conjunction with the 33rd IEEE International Conference on Computer Communications (INFOCOM)

Styrkeområden

Informations- och kommunikationsteknik

Energi

Ämneskategorier

Datavetenskap (datalogi)