An Energy-Efficient and Obstacle-Avoiding Routing Protocol for Underwater Acoustic Sensor Networks

Jin, Zhigang; Ding, Mengge; Li, Shuo

doi:10.3390/s18124168

Cited by 11 publications

(6 citation statements)

References 32 publications

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“…The shortest path to reach the sink is identified, and further packets are transmitted along the shortest path identified. Jin et al [25] have presented a reinforcement learning-based congestion avoidance routing scheme. The routing protocol takes into account both the node energy level and the network congestion.…”

Section: Related Workmentioning

confidence: 99%

Priority based energy efficient hybrid cluster routing protocol for underwater wireless sensor network

Murgod

Sundaram

Manchaiah

et al. 2023

IJECE

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<p class="Affiliation"><span lang="EN-US">A little change in the environment that goes unnoticed in an underwater communication network might lead to calamity. A little alteration in the environment must also be adequately analyzed in order to deal with a potential crisis. A priority-based routing protocol is required to ensure that the vital data perceived by the sensor about the environment changes. The priority-based routing system guarantees that vital data packets are delivered at a quicker pace to the destination or base station for further processing. In this work, we present a priority-based routing protocol based on the energy efficient hybrid cluster routing protocol (EEHRCP) algorithm. The suggested approach keeps two distinct queues for lower and higher priority data packets. In order to ensure that these packets get at their destination without any information loss and at a quicker rate, all of the crucial sensed data is passed through a higher priority queue. Test findings show that the suggested technique increases throughput, delivery percentage, and reduces latency for the crucial data packets.</span></p>

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Section: Related Workmentioning

confidence: 99%

Priority based energy efficient hybrid cluster routing protocol for underwater wireless sensor network

Murgod

Sundaram

Manchaiah

et al. 2023

IJECE

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“…The linguistic terms are shown in Table 1 and Table 2 . The fuzzy inference provides a basis from which decisions can be made or patterns distinguished [ 20 ]. The system output is a real number in the interval [0,1].…”

Section: Proposed Protocolmentioning

confidence: 99%

Energy-Efficient Packet Forwarding Scheme Based on Fuzzy Decision-Making in Underwater Sensor Networks

Pabani

Luque-Nieto

Hyder

et al. 2021

Sensors

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Underwater Wireless Sensor Networks (UWSNs) are subjected to a multitude of real-life challenges. Maintaining adequate power consumption is one of the critical ones, for obvious reasons. This includes proper energy consumption due to nodes close to and far from the sink node (gateway), which affect the overall energy efficiency of the system. These wireless sensors gather and route the data to the onshore base station through the gateway at the sea surface. However, finding an optimum and efficient path from the source node to the gateway is a challenging task. The common reasons for the loss of energy in existing routing protocols for underwater are (1) a node shut down due to battery drainage, (2) packet loss or packet collision which causes re-transmission and hence affects the performance of the system, and (3) inappropriate selection of sensor node for forwarding data. To address these issues, an energy efficient packet forwarding scheme using fuzzy logic is proposed in this work. The proposed protocol uses three metrics: number of hops to reach the gateway node, number of neighbors (in the transmission range of a node) and the distance (or its equivalent received signal strength indicator, RSSI) in a 3D UWSN architecture. In addition, the performance of the system is also tested with adaptive and non-adaptive transmission ranges and scalable number of nodes to see the impact on energy consumption and number of hops. Simulation results show that the proposed protocol performs better than other existing techniques or in terms of parameters used in this scheme.

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“…Energy-efficient and obstacle-avoiding routing (EOAR) [16] uses fuzzy logic to select the forwarding node. The selection is made based on residual energy, the angle between the two nodes, and the propagation delay.…”

Section: Opportunistic Protocolsmentioning

confidence: 99%

Self-Organized Proactive Routing Protocol for Non-Uniformly Deployed Underwater Networks

Hyder

Luque-Nieto

Poncela

et al. 2019

Sensors

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Electromagnetic (EM) waves cannot propagate more than few meters in sea water due to the high absorption rate. Acoustic waves are more suitable for underwater communication, but they travel very slowly compared to EM waves. The typical speed of acoustic waves in water is 1500 m/s, whereas speed of EM waves in air is approximately 3 × 10 8 m/s. Therefore, the terrestrial wireless sensor network (WSN) protocols assume that the propagation delay is negligible. Hence, reactive protocols are deemed acceptable for WSNs. Other important issues related to underwater wireless sensor networks (UWSNs) are determining the position of the underwater nodes and keeping a time synchronization among the nodes. Underwater nodes can neither determine their position nor synchronize using Global Navigation Satellite Systems (GNSS) because of the short penetration of EM waves in sea water. The limited mobility of UWSN nodes and variation in the propagation speed of acoustic waves make time synchronization a challenging task for underwater acoustic networks (UASNs). For all these reasons, WSN protocols cannot be readily used in UASNs. In this work, a protocol named SPRINT is designed to achieve high data throughput and low energy operation in the nodes. There is a tradeoff between the throughput and the energy consumption in the wireless networks. Longer links mean higher energy consumption. On the other hand, the number of relay nodes or hops between the source node and the final destination node is a key factor which affects the throughput. Each hop increases the delay in the packet forwarding and, as a result, decreases the throughput. Hence, energy consumption requires the nearest nodes to be chosen as forwarding nodes, whereas the throughput requires the farthest node to be selected to minimize the number of hops. SPRINT is a cross-layer, self-organized, proactive protocol which does not require positioning equipment to determine the location of the node. The routing path from the node to the gateway is formed based on the distance. The data sending node prefers to choose the neighbor node which is closest to it. The distance is measured by the signal strength between the two nodes. the sea (Figure 1). The suspended sensor nodes in 3D networks keep moving in all directions. This movement is limited by the length of the connecting rope or chain. The continuous random movement of the nodes makes the protocols design more challenging in 3D networks.Sensors 2020, 20, x FOR PEER REVIEW 2 of 21 directions. This movement is limited by the length of the connecting rope or chain. The continuous random movement of the nodes makes the protocols design more challenging in 3D networks.

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An Energy-Efficient and Obstacle-Avoiding Routing Protocol for Underwater Acoustic Sensor Networks

Cited by 11 publications

References 32 publications

Priority based energy efficient hybrid cluster routing protocol for underwater wireless sensor network

Priority based energy efficient hybrid cluster routing protocol for underwater wireless sensor network

Energy-Efficient Packet Forwarding Scheme Based on Fuzzy Decision-Making in Underwater Sensor Networks

Self-Organized Proactive Routing Protocol for Non-Uniformly Deployed Underwater Networks

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