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A Novel Cross-Layer Routing Protocol Based on Network Coding for Underwater Sensor Networks

College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410000, China
Author to whom correspondence should be addressed.
Sensors 2017, 17(8), 1821;
Received: 29 June 2017 / Revised: 4 August 2017 / Accepted: 6 August 2017 / Published: 8 August 2017
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Underwater wireless sensor networks (UWSNs) have attracted increasing attention in recent years because of their numerous applications in ocean monitoring, resource discovery and tactical surveillance. However, the design of reliable and efficient transmission and routing protocols is a challenge due to the low acoustic propagation speed and complex channel environment in UWSNs. In this paper, we propose a novel cross-layer routing protocol based on network coding (NCRP) for UWSNs, which utilizes network coding and cross-layer design to greedily forward data packets to sink nodes efficiently. The proposed NCRP takes full advantages of multicast transmission and decode packets jointly with encoded packets received from multiple potential nodes in the entire network. The transmission power is optimized in our design to extend the life cycle of the network. Moreover, we design a real-time routing maintenance protocol to update the route when detecting inefficient relay nodes. Substantial simulations in underwater environment by Network Simulator 3 (NS-3) show that NCRP significantly improves the network performance in terms of energy consumption, end-to-end delay and packet delivery ratio compared with other routing protocols for UWSNs. View Full-Text
Keywords: underwater sensor networks; network coding; routing protocol; cross-layer design underwater sensor networks; network coding; routing protocol; cross-layer design

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Wang, H.; Wang, S.; Bu, R.; Zhang, E. A Novel Cross-Layer Routing Protocol Based on Network Coding for Underwater Sensor Networks. Sensors 2017, 17, 1821.

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