A Secure Communication Protocol between Sensor Nodes and Sink Node in Underwater Acoustic Sensor Networks

Author(s):  
Xiujun Yu ◽  
Huifang Chen ◽  
Lei Xie
Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2885 ◽  
Author(s):  
Sunhyo Kim ◽  
Jee Woong Choi

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.


2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
Andrej Stefanov

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.


Underwater Acoustic Sensor Networks (UASN) has driven a lot of attention from researchers because of advancements in sensor technology and unexplored applications of the ocean. UASNs monitor the targeted area with heterogeneous underwater sensors and relay that information to the onshore sink node in mission-critical applications. It is very much essential to know the source of information whenever some critical events happened in the UASNs. Hence, to learn the source of information, i.e. finding the location of the sensor node is crucial. To address this issue, in this paper, initially geometrical object such as trapezoid is used to form the clusters in the targeted region. After that, the proposed localization algorithm is applied and it works in three phases. (i) In the first phase, the sink node initiates the trapezoid formation process through Trapezoid Formation Agent (TFA) and divides the whole network into trapezoids of different geometrical shapes by traveling across the linear trajectory and also creates a search data structure. (ii) In the second phase, the sink deploys AUV at a certain depth for patrolling along the linear trajectory and broadcasts real-time location contained beacon messages at specified points through that anchor nodes are localized by using RSSI. (iii) Sink node activates Localization Agent (LA) in the third phase to perform the location identification process at the trapezoids by using the trilateration method. This work addresses the inherent localization issue of UASNs algorithms and hence it applies to the applications which consider the localization issue. This proposed scheme is well supported by node agencies and knowledgebase. The proposed scheme is simulated in C and validated by different performance parameters.


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