Abstract
Internet-of-Underwater-Things (IoUT) systems comprising tens or hundreds of underwater acoustic communication nodes will become feasible in the near future. The development of scalable networking protocols is a key enabling technology for such IoUT systems, but this task is challenging due to the fundamental limitations of the underwater acoustic communication channel: extremely slow propagation and limited bandwidth. The aim of this article is to propose the JOIN protocol to enable the integration of new nodes into an existing IoUT network without the control overhead of typical state-of-the-art solutions. The proposed solution is based on the capability of a joining node to incorporate local topology and schedule information into a probabilistic model that allows it to choose when to join the network to minimize the expected number of collisions. The proposed approach is tested in numerical simulations and validated in two sea trials. The simulations show that the JOIN protocol achieves fast convergence to a collision-free solution, fast network adaptation to new nodes, and negligible network disruption due to collisions caused by a joining node. The sea trials demonstrate the practical feasibility of this protocol in real underwater acoustic network deployments and provide valuable insight for future work on the tradeoff between control overhead and reliability of the JOIN protocol in a harsh acoustic communication environment.
Original language | English |
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Article number | 9070166 |
Pages (from-to) | 10023-10037 |
Number of pages | 15 |
Journal | IEEE Internet of Things Journal |
Volume | 7 |
Issue number | 10 |
DOIs | |
State | Published - Oct 2020 |
Bibliographical note
Publisher Copyright:© 2014 IEEE.
Keywords
- Adaptive network
- Internet of Things (IoT)
- medium access control (MAC)
- node integration
- underwater acoustic network (UAN)
ASJC Scopus subject areas
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications