Cyber Physical Systems and the Internet of Things has brought connectivity and computing to physical objects and places. Even traditionally simple objects such as step counters, thermostats, and light bulbs begin to enjoy wireless communication. On the other hand, many applications are not simple, they are extremely mission and safety-critical. A wireless glucose sensor must quickly and reliably exchange information with, for example, an insulin pump to ensure a patient’s well-being, and two autonomous vehicles approaching an intersection must coordinate and decide within a split second which car shall cross first.
Olaf Landsiedel, associate professor in the Networks and Systems division at Computer Science and Engineering, was recently awarded the SSF grant “Framtidens forskningsledare” for the project “Ultra Low-Latency, Low-Power Wireless Mesh Networks”. Current approaches in wireless networking maintain routes in the network, and external factors such as interference and mobility affect these routes, and will force the network to constantly repair them. If a route cannot be repaired sufficiently fast, messages will be delayed, and potentially lost.
In the project, which is based on many years of research, Olaf Landsiedel and his colleagues will work on a novel approach, taking on the challenge of exploiting the physical phenomena of the capture effect (the fact that when two signals are present, one will with a higher probability catch the stronger of the two) to design a communication scheme that will ensure that if there is a route towards a destination, it will be found instantly, regardless of the external factors.
“With this approach, we want to take existing algorithms that work in, for example, the data center world, where they have significantly more compute power, bandwidth and energy, and redesign these algorithms so they can be employed in the much smaller sensor networks, and operate – on batteries – with very limited compute power and bandwidth” says Olaf Landsiedel.
Associate Professor Olaf Landsiedel, Networks and Systems division, Computer Science and Engineering.