Opportunistic Routing in Heterogenous Duty-cycled Wireless Sensor Networks

In this project, we propose a novel routing metric that efficiently captures packet transmission cost in heterogeneous duty-cycled WSNs by estimating both expected rendezvous cost and communication cost. Based on this metric, we design an opportunistic routing protocol which is proved to select optimal routes with the least packet transmission cost.

This work has been reported in ICNP 2015 and IEEE System Journal .

Tao Gu
Tao Gu
Professor in IoT
IEEE Fellow
AAIA Fellow
ACM Distinguished Member
Email: firstname dot lastname AT mq.edu.au
Phone: +61-2-9850-4357
Address: Room 267, 4 Research Park Drive, North Ryde, NSW 2109, Australia

My research interests include Internet of Things, Ubiquitous Computing, Mobile Computing, Embedded AI, Wireless Sensor Networks, and Big Data Analytics.