• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.486-488
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• 2013

In the earth more than half of the space filled with water. In that water most of the part is in the form of oceans. The ocean atmosphere determines climate on the land. Combining the Underwater Acoustic Sensor Network (UWASN) system with Internet Of Things (IoT) is called Internet of Underwater Things (IoUT). Using IoUT we can find the changes in the ocean environment. Underwater sensor nodes are used in UWASN. Underwater sensor nodes are constructive in offshore investigation, disaster anticipation, data gathering, assisted navigation, pollution checking and strategic inspection. By using IoT components such as Database, Server and Internet, ocean data can be broadcasted. This paper introduces IoUT architecture and and explains fish forming application scenario with this IoUT architecture.

• Journal of Convergence for Information Technology
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• v.10 no.5
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• pp.1-7
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• 2020

This paper proposes a link adaptation method for Underwater Internet of Things (IoT), which reduces power consumption of sensor nodes and improves the throughput of network in underwater IoT network. Adaptive Modulation and Coding (AMC) technique is one of link adaptation methods. AMC uses the strong correlation between Signal Noise Rate (SNR) and Bit Error Rate (BER), but it is difficult to apply in underwater IoT as it is. Therefore, we propose the machine learning based AMC technique for underwater environments. The proposed Modulation Coding and Scheme (MCS) prediction model predicts transmission method to achieve target BER value in underwater channel environment. It is realistically difficult to apply the predicted transmission method in real underwater communication in reality. Thus, this paper uses the high accuracy BER prediction model to measure the performance of MCS prediction model. Consequently, the proposed AMC technique confirmed the applicability of machine learning by increase the probability of communication success.

• Journal of Korea Multimedia Society
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• v.18 no.4
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• pp.506-523
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• 2015

The intent is to determine whether or not the custody transfer is helpful for data transmission in challenging underwater communications when running Bundle protocol or underwater protocols. From the point of view defending side, Underwater Acoustic Network (UAN) will be a serious threat for its strong functionality long rang and high precision of surveillance and detection. Therefore, countermeasures must be taken to weaken its effect. Our purpose is analyzed that how to benefit from the UIoT to learn from, exploit and preserve the natural underwater resources. Delay/Disruption Tolerant Network (DTN) is essential part of the network heterogeneity communication network. The vulnerability and potential security factors of UIoT are studied thereafter. Security mechanisms for an underwater environment are difficult to apply owing to the limited bandwidth. Therefore, for underwater security, appropriate security mechanisms and security requirements must be defined simultaneously. The paper consists of mathematical and security model. Most important point of view in the security challenges of effective Buffer and Storage management in DTN.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.41-48
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• 2020

The sensor nodes in underwater IoT networks have practical limitations in power supply. Thus, the reduction of power consumption is one of the most important issues in underwater environments. In this regard, AMC(Adaptive Modulation and Coding) techniques are used by using the relation between SNR and BER. However, according to our hands-on experience, we observed that the relation between SNR and BER is not that tight in underwater environments. Therefore, we propose a deep learning based MLP classification model to reflect multiple underwater channel parameters at the same time. It correctly predicts BER with a high accuracy of 85.2%. The proposed model can choose the best parameters to have the highest throughput. Simulation results show that the throughput can be enhanced by 4.4 times higher than the conventionally measured results.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.1-7
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• 2020

The demand on the underwater communications is extremely increasing in searching for underwater resources, marine expedition, or environmental researches, yet there are many problems with the wireless communications because of the characteristics of the underwater environments. Especially, with the underwater wireless networks, there happen inevitable delay time and spacial inequality due to the distances between the nodes. To solve these problems, this paper suggests a new solution based on ALOHA-Q. The suggested method use random NAV value. and Environments take reward through communications success or fail. After then, The environments setting NAV value from reward. This model minimizes usage of energy and computing resources under the underwater wireless networks, and learns and setting NAV values through intense learning. The results of the simulations show that NAV values can be environmentally adopted and select best value to the circumstances, so the problems which are unnecessary delay times and spacial inequality can be solved. Result of simulations, NAV time decreasing 17.5% compared with original NAV.

• Journal of Convergence for Information Technology
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• v.10 no.7
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• pp.33-40
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• 2020

This work tackles the problem of conventional reinforcement learning scheme which has a relatively long training time to reduce energy consumption in underwater network. The enhanced scheme adjusts the learning range of reinforcement learning based on distance estimation. It can be reduce the scope of learning. To take account the fact that the distance estimation may not be accurate due to the underwater wireless network characteristics. this research added noise in consideration of the underwater environment. In simulation result, the proposed AQ-NAV scheme has completed learning much faster than existing method. AQ-NAV can finish the training process within less than 40 episodes. But the existing method requires more than 120 episodes. The result show that learning is possible with fewer attempts than the previous one. If AQ-NAV will be applied in Underwater Networks, It will affect energy efficiency. and It will be expected to relieved existing problem and increase network efficiency.

• ETRI Journal
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• v.43 no.3
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• pp.414-426
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• 2021

In the task of data routing in Internet of Things enabled volatile underwater environments, providing better transmission and maximizing network communication performance are always challenging. Many network issues such as void holes and network isolation occur because of long routing distances between nodes. Void holes usually occur around the sink because nodes die early due to the high energy consumed to forward packets sent and received from other nodes. These void holes are a major challenge for I-UWSANs and cause high end-to-end delay, data packet loss, and energy consumption. They also affect the data delivery ratio. Hence, this paper presents an energy efficient watchman based flooding algorithm to address void holes. First, the proposed technique is formally verified by the Z-Eves toolbox to ensure its validity and correctness. Second, simulation is used to evaluate the energy consumption, packet loss, packet delivery ratio, and throughput of the network. The results are compared with well-known algorithms like energy-aware scalable reliable and void-hole mitigation routing and angle based flooding. The extensive results show that the proposed algorithm performs better than the benchmark techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3639-3662
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• 2020

The network capability to accomplish its functions in a timely fashion under failures and attacks is known as survivability. Ad hoc routing protocols have been studied and extended to various domains, such as Intelligent Transport Systems (ITSs), Unmanned Aerial Vehicles (UAVs), underwater acoustic networks, and Internet of Things (IoT) focusing on different aspects, such as security, QoS, energy. The existing solutions proposed in this domain incur substantial overhead and eventually become burden on the network, especially when there are fewer attacks or no attack at all. There is a need that the effectiveness of these routing protocols be analyzed in the presence of Denial of Service (DoS) attacks without any intrusion detection or prevention system. This will enable us to establish and identify the inherently stable routing protocols that are capable to survive longer in the presence of these attacks. This work presents a DoS attack case study to perform theoretical analysis of survivability on node and network level in the presence of DoS attacks. We evaluate the performance of reactive and proactive routing protocols and analyse their survivability. For experimentation, we use NS-2 simulator without detection or prevention capabilities. Results show that proactive protocols perform better in terms of throughput, overhead and packet drop.