Home/EURASIP Journal on Wireless Communications and Networking/Article Record
Peer-Reviewed Article June 2, 2010

Efficient Vector-Based Forwarding for Underwater Sensor Networks

Are you an author of this work?Link to your sovereign AfriScholar profile
Published in: EURASIP Journal on Wireless Communications and Networking
Publisher: Springer Nature • Egypt • 1687-1472
DOI: https://doi.org/10.1155/2010/195910

Abstract

Underwater Sensor Networks (UWSNs) are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, node mobility, high error probability, and 3-dimensional space. These new features bring many challenges to the network protocol design of UWSNs. In this paper, we tackle one fundamental problem in UWSNs: robust, scalable, and energy efficient routing. We propose vector-based forwarding (VBF), a geographic routing protocol. In VBF, the forwarding path is guided by a vector from the source to the target, no state information is required on the sensor nodes, and only a small fraction of the nodes is involved in routing. To improve the robustness, packets are forwarded in redundant and interleaved paths. Further, a localized and distributed self-adaptation algorithm allows the nodes to reduce energy consumption by discarding redundant packets. VBF performs well in dense networks. For sparse networks, we propose a hop-by-hop vector-based forwarding (HH-VBF) protocol, which adapts the vector-based approach at every hop. We evaluate the performance of VBF and HH-VBF through extensive simulations. The simulation results show that VBF achieves high packet delivery ratio and energy efficiency in dense networks and HH-VBF has high packet delivery ratio even in sparse networks.

Download Full Text PDFView at PublisherCrossref RecordCrossref XML

Verified Citation Velocity

Recorded scholarly citations in African and international peer-reviewed literature

70
Total Citations

Citations are continuously tracked and harvested across continental OJS endpoints and OpenAlex feeds.