scholarly journals A Performance Simulation Tool for the Analysis of Data Gathering in Both Terrestrial and Underwater Sensor Networks

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 4190-4208 ◽  
Author(s):  
Mukhtar Ghaleb ◽  
Emad Felemban ◽  
Shamala Subramaniam ◽  
Adil A. Sheikh ◽  
Saad Bin Qaisar
Keyword(s):  
Sensor Networks ◽  
Data Gathering ◽  
Underwater Sensor Networks ◽  
Simulation Tool ◽  
Performance Simulation ◽  
A Performance

scholarly journals Mobile Data Gathering With Hop-Constrained Clustering in Underwater Sensor Networks

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 21118-21132 ◽  
Author(s):  
Seyed Mohammad Ghoreyshi ◽  
Alireza Shahrabi ◽  
Tuleen Boutaleb ◽  
Mohsen Khalily
Keyword(s):  
Sensor Networks ◽  
Data Gathering ◽  
Underwater Sensor Networks ◽  
Constrained Clustering ◽  
Mobile Data ◽  
Mobile Data Gathering

scholarly journals A better-performing Q-learning game-theoretic distributed routing for underwater wireless sensor networks

2018 ◽  
Vol 14 (1) ◽  
pp. 155014771875472 ◽  
Author(s):  
Sungwook Kim
Keyword(s):  
Sensor Networks ◽  
Simulation Analysis ◽  
Dynamic Structure ◽  
Propagation Delay ◽  
Underwater Sensor Networks ◽  
Performance Simulation ◽  
Q Learning ◽  
Transmission Problems ◽  
Learning Game ◽  
Game Theoretic

Underwater sensor networks have recently emerged as a promising networking technique for various underwater applications. However, the acoustic routing of underwater sensor networks in the aquatic environment presents challenges in terms of dynamic structure, high rates of energy consumption, long propagation delay, and narrow bandwidth. Therefore, it is difficult to adapt traditional routing protocols, which are known to be reliable in terrestrial wireless networks. In this study, we focus on the development of novel routing algorithms to tackle acoustic transmission problems in underwater sensor networks. The proposed scheme is based on reinforcement learning and game theory and is designed as a routing game model to provide an effective packet-forwarding mechanism. In particular, our Q-learning game paradigm captures the dynamics of the underwater sensor networks system in a decentralized, distributed manner. The results of a performance simulation analysis show that the proposed scheme can outperform existing schemes while displaying balanced system performance in terms of energy efficiency and underwater sensor networks throughput.

scholarly journals An AUV-Aided Cross-Layer Mobile Data Gathering Protocol for Underwater Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4813
Author(s):  
Faisal Abdulaziz Alfouzan ◽  
Seyed Mohammad Ghoreyshi ◽  
Alireza Shahrabi ◽  
Mahsa Sadeghi Ghahroudi
Keyword(s):  
Sensor Networks ◽  
Network Performance ◽  
Data Gathering ◽  
Mac Protocols ◽  
Cross Layer ◽  
Delivery Ratio ◽  
Underwater Sensor Networks ◽  
Mobile Data ◽  
Packet Delivery ◽  
Mobile Data Gathering

Underwater sensor networks (UWSNs) have recently attracted much attention due to their ability to discover and monitor the aquatic environment. However, acoustic communication has posed some significant challenges, such as high propagation delay, low available bandwidth, and high bit error rate. Therefore, proposing a cross-layer protocol is of high importance to the field to integrate different communication functionalities (i.e, an interaction between data link layer and network layer) to interact in a more reliable and flexible manner to overcome the consequences of applying acoustic signals. In this paper, a novel Cross-Layer Mobile Data gathering (CLMD) scheme for Underwater Sensor Networks (UWSNs) is presented to improve the performance by providing the interaction between the MAC and routing layers. In CLMD, an Autonomous Underwater Vehicle (AUV) is used to periodically visit a group of clusters which are responsible for data collection from members. The communications are managed by using a distributed cross-layer solution to enhance network performance in terms of packet delivery and energy saving. The cluster heads are replaced with other candidate members at the end of each operational phase to prolong the network lifetime. The effectiveness of CLMD is verified through an extensive simulation study which reveals the performance improvement in the energy-saving, network lifetime, and packet delivery ratio with varying number of nodes. The effects of MAC protocols are also studied by studying the network performance under various MAC protocols in terms of packet delivery ratio, goodput, and energy consumption with varying density of nodes.

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