Underwater Wireless Sensor Network Performance Analysis Using Diverse Routing Protocols

Author:

Sathish Kaveripaka,Ravikumar Chinthaginjala Venkata,Rajesh Anbazhagan,Pau GiovanniORCID

Abstract

The planet is the most water-rich place because the oceans cover more than 75% of its land area. Because of the unique activities that occur in the depths, we know very little about oceans. Underwater wireless sensors are tools that can continuously transmit data to one of the source sensors while monitoring and recording their surroundings’ physical and environmental parameters. An Underwater Wireless Sensor Network (UWSN) is the name given to the network created by collecting these underwater wireless sensors. This particular technology has a random path loss model due to the time-varying nature of channel parameters. Data transmission between underwater wireless sensor nodes requires a careful selection of routing protocols. By changing the number of nodes in the model and the maximum speed of each node, performance parameters, such as average transmission delay, average jitter, percentage of utilization, and power used in transmit and receive modes, are explored. This paper focuses on UWSN performance analysis, comparing various routing protocols. A network path using the source-tree adaptive routing-least overhead routing approach (STAR-LORA) Protocol exhibits 85.3% lower jitter than conventional routing protocols. Interestingly, the fisheye routing protocol achieves a 91.4% higher utilization percentage than its counterparts. The results obtained using the QualNet 7.1 simulator suggest the suitability of routing protocols in UWSN.

Publisher

MDPI AG

Subject

Control and Optimization,Computer Networks and Communications,Instrumentation

Reference42 articles.

1. A survey on routing techniques in underwater wireless sensor networks

2. Shallow water acoustic networks

3. Research challenges and applications for underwater sensor networking;Heidemann;Proceedings of the Wireless Communications and Networking Conference (WCNC 2006), IEEE,2006

4. CLAM—Collaborative embedded networks for submarine surveillance: An overview;Meratnia;Proceedings of the OCEANS 2011 IEEE-Spain, IEEE,2011

5. An Integrated System for Regional Environmental Monitoring and Management Based on Internet of Things

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