scholarly journals Analysis of Throughput and Delay for an Underwater Multi-DATA Train Protocol with Multi-RTS Reception and Block ACK

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6473
Author(s):  
Ho Young Hwang
Keyword(s):  
Propagation Delay ◽  
Sensor Nodes ◽  
Sink Node ◽  
Underwater Acoustic Sensor Networks ◽  
Data Frame ◽  
Underwater Acoustic ◽  
Acoustic Sensor Networks ◽  
Multiple Data ◽  
Normalized Throughput ◽  
Throughput And Delay

We propose an underwater multi-DATA train protocol with multi-RTS reception and block ACK (BACK) for underwater acoustic sensor networks. Due to long underwater acoustic propagation delay, some RTS frames may not overlap at a sink node, even if the RTS frames were sent to the sink node simultaneously by different sensor nodes. We consider that our underwater sink node can recover these nonoverlapping RTS frames. Since our RTS frame contains ID of the RTS sending node and a timestamp, the sink node calculates the propagation delay between the RTS sending node and the sink node, then broadcasts a CTS frame. Since our CTS frame contains when each RTS sending node can transmit a DATA frame to the sink node, multiple DATA frames transmitted by different sensor nodes can be formed as a train at the sink node. We also propose an underwater BACK protocol which is analogous to our proposed underwater multi-DATA train protocol. We analyze normalized throughput and mean access delay of our proposed protocols and the conventional protocols. The analytical and simulation results show that our analysis is accurate and our proposed protocols outperform the conventional protocols. Our proposed protocol can shorten the delay and increase the throughput via the multi-DATA train, multi-RTS reception, and BACK.

scholarly journals Packet Flow Based Reinforcement Learning MAC Protocol for Underwater Acoustic Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2284
Author(s):  
Ibrahim B. Alhassan ◽  
Paul D. Mitchell
Keyword(s):  
Sensor Networks ◽  
Mac Protocol ◽  
Propagation Delay ◽  
Basic Function ◽  
Acoustic Sensor ◽  
Underwater Acoustic Sensor Networks ◽  
Medium Access ◽  
Underwater Acoustic ◽  
Q Learning ◽  
Acoustic Sensor Networks

Medium access control (MAC) is one of the key requirements in underwater acoustic sensor networks (UASNs). For a MAC protocol to provide its basic function of efficient sharing of channel access, the highly dynamic underwater environment demands MAC protocols to be adaptive as well. Q-learning is one of the promising techniques employed in intelligent MAC protocol solutions, however, due to the long propagation delay, the performance of this approach is severely limited by reliance on an explicit reward signal to function. In this paper, we propose a restructured and a modified two stage Q-learning process to extract an implicit reward signal for a novel MAC protocol: Packet flow ALOHA with Q-learning (ALOHA-QUPAF). Based on a simulated pipeline monitoring chain network, results show that the protocol outperforms both ALOHA-Q and framed ALOHA by at least 13% and 148% in all simulated scenarios, respectively.

scholarly journals Optimal Deployment of Vector Sensor Nodes in Underwater Acoustic Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2885 ◽  
Author(s):  
Sunhyo Kim ◽  
Jee Woong Choi
Keyword(s):  
Sensor Networks ◽  
Particle Velocity ◽  
Sensor Nodes ◽  
Acoustic Sensor ◽  
Underwater Acoustic Sensor Networks ◽  
Communication Performance ◽  
Underwater Acoustic ◽  
Acoustic Sensor Networks ◽  
Vector Sensor ◽  
Optimal Deployment

Underwater acoustic sensor networks have recently attracted considerable attention as demands on the Internet of Underwater Things (IoUT) increase. In terms of efficiency, it is important to achieve the maximum communication coverage using a limited number of sensor nodes while maintaining communication connectivity. In 2017, Kim and Choi proposed a new deployment algorithm using the communication performance surface, which is a geospatial information map representing the underwater acoustic communication performance of a targeted underwater area. In that work, each sensor node was a vertically separated hydrophone array, which measures acoustic pressure (a scalar quantity). Although an array receiver is an effective system to eliminate inter-symbol interference caused by multipath channel impulse responses in underwater communication environments, a large-scale receiver system degrades the spatial efficiency. In this paper, single-vector sensors measuring the particle velocity are used as underwater sensor nodes. A single-vector sensor can be considered to be a single-input multiple-output communication system because it measures the three directional components of particle velocity. Our simulation results show that the optimal deployment obtained using single-vector sensor nodes is more effective than that obtained using a hydrophone (three-channel vertical-pressure sensor) array.

scholarly journals GSR-TDMA: A Geometric Spatial Reuse-Time Division Multiple Access MAC Protocol for Multihop Underwater Acoustic Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Changho Yun ◽  
Yong-Kon Lim
Keyword(s):  
Sensor Networks ◽  
Mac Protocol ◽  
Propagation Delay ◽  
Packet Transmission ◽  
Acoustic Sensor ◽  
Spatial Reuse ◽  
Underwater Acoustic Sensor Networks ◽  
Underwater Acoustic ◽  
Performance Improvements ◽  
Acoustic Sensor Networks

The nonnegligible propagation delay of acoustic signals causes spatiotemporal uncertainty that occasionally enables simultaneous, collision-free packet transmission among underwater nodes (UNs). These transmissions can be handled by efficiently managing the channel access of the UNs in the data-link layer. To this end, Geometric Spatial Reuse-TDMA (GSR-TDMA), a new TDMA-based MAC protocol, is designed for use in centralized, multihop underwater acoustic sensor networks (UASNs), and in this case all UNs are periodically scheduled after determining a geometric map according to the information on their location. The scheduling strategy increases the number of UNs that send packets coincidentally via two subscheduling configurations (i.e., interhop and intrahop scheduling). Extensive simulations are used to investigate the reception success rate (RSR) and the multihop delay (MHD) of GSR-TDMA, and the results are compared to those of previous approaches, including C-MAC and HSR-TDMA. GSR-TDMA outperforms C-MAC; the RSR of GSR-TDMA is 15% higher than that of C-MAC, and the MHD of GSR-TDMA is 30% lower than that of C-MAC at the most. In addition, GSR-TDMA provides even better performance improvements over HSR-TDMA; the RSR of GSR-TDMA is 50% higher than that of HSR-TDMA, and the MHD of GSR-TDMA is an order of102lower than that of HSR-TDMA at the most.

scholarly journals Shortest Propagation Delay-Based Relay Selection for Underwater Acoustic Sensor Networks

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 37923-37935
Author(s):  
Ramsha Narmeen ◽  
Ishtiaq Ahmad ◽  
Zeeshan Kaleem ◽  
Umair Ahmad Mughal ◽  
Daniel Benevides Da Costa ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Relay Selection ◽  
Propagation Delay ◽  
Acoustic Sensor ◽  
Underwater Acoustic Sensor Networks ◽  
Underwater Acoustic ◽  
Acoustic Sensor Networks ◽  
Selection For

scholarly journals Distortion Performance of Underwater Acoustic Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
Andrej Stefanov
Keyword(s):  
Sensor Networks ◽  
Sensor Nodes ◽  
Rician Fading ◽  
Acoustic Sensor ◽  
Underwater Acoustic Sensor Networks ◽  
Limited Region ◽  
Underwater Acoustic ◽  
Numerical Examples ◽  
Acoustic Sensor Networks ◽  
The Impact

The paper studies the distortion performance of multihop underwater acoustic sensor networks. The network is composed of bottom mounted sensor nodes and the sensor to sensor links experience Rician fading. The distortion is evaluated for the case when there is interference from other sensors in the network. The focus is on the sustainable number of hops in the network for a maximum allowed (target) route distortion requirement. Numerical examples are provided that illustrate the results of the analysis and the regions where the network operation is limited, namely, the coverage-limited region and the interference-limited region. The paper also considers the impact of retransmissions on the distortion performance. It is found that the network connectivity and robustness improve with automatic repeat request (ARQ). The improvements are manifested as a reduction of the regions of limited performance, that is, an increase of the region where the network exhibits full connectivity. The analysis results are illustrated through numerical examples.

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