Coordination and Self-Adaptive Communication Primitives for Low-Power Wireless Networks
Licentiatavhandling, 2020

The Internet of Things (IoT) is a recent trend where objects are augmented with computing and communication capabilities, often via low-power wireless radios. The Internet of Things is an enabler for a connected and more sustainable modern society: smart grids are deployed to improve energy production and consumption, wireless monitoring systems allow smart factories to detect faults early and reduce waste, while connected vehicles coordinate on the road to ensure our safety and save fuel. Many recent IoT applications have stringent requirements for their wireless communication substrate: devices must cooperate and coordinate, must perform efficiently under varying and sometimes extreme environments, while strict deadlines must be met. Current distributed coordination algorithms have high overheads and are unfit to meet the requirements of today's wireless applications, while current wireless protocols are often best-effort and lack the guarantees provided by well-studied coordination solutions. Further, many communication primitives available today lack the ability to adapt to dynamic environments, and are often tuned during their design phase to reach a target performance, rather than be continuously updated at runtime to adapt to reality.

In this thesis, we study the problem of efficient and low-latency consensus in the context of low-power wireless networks, where communication is unreliable and nodes can fail, and we investigate the design of a self-adaptive wireless stack, where the communication substrate is able to adapt to changes to its environment. We propose three new communication primitives: Wireless Paxos brings fault-tolerant consensus to low-power wireless networking, STARC is a middleware for safe vehicular coordination at intersections, while Dimmer builds on reinforcement learning to provide adaptivity to low-power wireless networks. We evaluate in-depth each primitive on testbed deployments and we provide an open-source implementation to enable their use and improvement by the community.

Low-power Wireless Networks

IoT

Internet of Things

Synchronous Transmissions

Distributed Systems

Wireless Sensors Networks

DQN

Reinforcement Learning

WSN

Consensus

CSE EDIT 8103
Opponent: Luca Mottola, Politecnico di Milano, Italy and RISE SICS, Sweden

Författare

Valentin Poirot

Chalmers, Data- och informationsteknik, Nätverk och system

Paxos Made Wireless: Consensus in the Air

Proceedings of the 2019 International Conference on Embedded Wireless Systems and Networks,; (2019)p. 1-12

Paper i proceeding

STARC: Low-power Decentralized Coordination Primitive for Vehicular Ad-hoc Networks

Proceedings of IEEE/IFIP Network Operations and Management Symposium 2020: Management in the Age of Softwarization and Artificial Intelligence, NOMS 2020,; (2020)

Paper i proceeding

Poirot, V, Landsiedel, O. Dimmer: Self-Adaptive Network Floods with Reinforcement Learning

AgreeOnIT: Lättvikts konsensus och distribuerat datakunskap i resursbegränsade sakernas Internet

Vetenskapsrådet (VR), 2019-01-01 -- 2022-12-31.

Ultralåg fördröjning, effektsnåla trådlösa nät

Stiftelsen för Strategisk forskning (SSF), 2017-01-01 -- 2021-12-31.

Ämneskategorier

Datorteknik

Telekommunikation

Kommunikationssystem

Styrkeområden

Informations- och kommunikationsteknik

Technical report - Department of Computing Science, Chalmers University of Technology and Göteborg University: 216L

Utgivare

Chalmers tekniska högskola

CSE EDIT 8103

Online

Opponent: Luca Mottola, Politecnico di Milano, Italy and RISE SICS, Sweden

Mer information

Senast uppdaterat

2020-09-07