FCLR: Fuzzy Control-Based Layering Routing Protocol for Underwater Acoustic Networks

Han, Duoliang; Du, Xiujuan; Liu, Xiuxiu; Tian, Xiaojing

doi:10.1109/jsen.2022.3218136

Cited by 15 publications

(11 citation statements)

References 33 publications

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“…The considered 3D network model is shown in Figure 1, where one source deployed underwater and it is responsible for periodically collecting and sendin Numerous nodes (forwarding nodes) are randomly deployed underwater to re DATA packet and transmit it from the source node [17]. A sink node deployed water surface collects DATA packets and delivers the packets to the server in a data For understanding, we made the following assumptions.…”

Section: Network Modelmentioning

confidence: 99%

“…A HELLO packet is identified by using the sequence (HELLO_seq_num) and involves some key information of the sending node, suc layer, and residual energy. The information of the sending node is updated hopand the node receiving the HELLO packet updates its layer and neighbor infor table according to the information from the received packets, which is described la structure of a HELLO packet is shown in Table 1 [17], in which SN represents the node and RN represents the receiving node. S_ID and R_ID are the IDs of the node and receiving node, respectively.…”

Section: Network Initializationmentioning

confidence: 99%

“…In the TAFLRLR protocol, each node maintains a layer that represents the hop count from the node to the sink. The layer (L sink ) of the sink node is set to 0, and the layer (L cur ) of other nodes is initialized to 0xFF [17][18][19]. The layer is the only basis for determining whether a node is a candidate forwarding node.…”

Section: Layering Algorithmmentioning

confidence: 99%

See 2 more Smart Citations

Trust-Aware and Fuzzy Logic-Based Reliable Layering Routing Protocol for Underwater Acoustic Networks

Han,

Du,

Wang

et al. 2023

Sensors

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Routing protocols based on trust mechanisms have been widely investigated for wireless sensor networks, and the works have achieved good results, while there are few works on trusted routing for underwater acoustic networks (UANs). However, trust-aware routing is the key to improving the packet delivery rate and the energy efficiency of UANs. Therefore, inspired by the theory of trust evaluation, a trust-aware and fuzzy logic-based reliable layering routing protocol (TAFLRLR) is proposed. In the TAFLRLR protocol, to avoid the problem of the void area and improve the transmission reliability, the candidate nodes of the next-hop forwarding nodes are determined according to the layers of neighbor nodes. Moreover, a fuzzy logic-based trust evaluation mechanism (FLTEM) is provided, which employs the fuzzy comprehensive evaluation decision model to calculate the comprehensive trust value for underwater sensor nodes. Further, the node density of a candidate node and its comprehensive trust value are taken as the input of a fuzzy control system and the forwarding probability (FP) of the node is taken as the output, and the candidate node with the highest FP is selected as the best forwarding node. Simulation results illustrate the superiority and effectiveness of the TAFLRLR protocol in terms of energy efficiency, routing reliability, and transmission reliability.

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Section: Network Modelmentioning

confidence: 99%

Section: Network Initializationmentioning

confidence: 99%

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Trust-Aware and Fuzzy Logic-Based Reliable Layering Routing Protocol for Underwater Acoustic Networks

Han,

Du,

Wang

et al. 2023

Sensors

Self Cite

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“…The positions of IoUT nodes can shift over time owing to water movement, which causes different propagation delays. It is challenging to create an effective IoUT node transmission schedule due to these network characteristics 12 . For IoUT networks, a few articles suggest using random access protocols.…”

Section: Introductionmentioning

confidence: 99%

Improved geographic opportunistic routing protocol for void hole elimination in underwater IoTs: Parameter tuning by TSA optimization

Simon,

Kapileswar,

Phani Kumar

et al. 2023

Int J Communication

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SummaryUnderwater IoT is incredibly helpful in monitoring a variety of jobs, from instrument monitoring to climate recording, from pollution management to natural catastrophe forecasting. Nevertheless, there exist various issues that have an impact on a network's efficiency such as the formation of void holes, excessive EC, and low PDR. As a result, the IGOR protocol is suggested in this study to increase PDR by reducing the percentage of void hole occurrence. The developed routing protocols' scalability is also examined. Here, the parameter optimization for the EC minimization and PDR maximization is performed by a meta‐heuristic optimization algorithm referred to as TSA. In order to verify that the suggested protocol is EC‐optimal by calculating the viable areas. In addition, suggested protocols are evaluated against contemporaries' benchmark routing protocols. The outcomes of the simulations clearly demonstrate that the suggested routing protocols obtained greater PDR than the current techniques. Additionally, there exists a reduction in the ratio of void hole incidence. Comparative research reveals that suggested routing protocols outperformed benchmark routing protocols by 80–81% in PDR. Further, the suggested routing procedures reduced the frequency of void holes by around 30%.

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“…However, only the location factor is attributed to weighing credits of packet forwarding, which results in energy consumption among sensor nodes unevenly and abbreviates network lifespan. Moreover, the data transmission reliability is not assured in the circumstances of thinly distributed network Further, some MAC solutions (3,4) have been suggested for UASNs. In UASNs, the predetermined MAC protocols like TDMA, FDMA, or CDMA cannot be adopted because of limited bandwidth, high delay in propagation, complexity in lock synchronization, etc.…”

Section: Introductionmentioning

confidence: 99%

Secure Fuzzy Simple Shortest Path Routing Protocol (SF_SSP) for Underwater Communication

Shahapur,

Khanai,

Torse

et al. 2023

IJST

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Objectives: The primary objective of the protocol is to detect malicious nodes accurately and efficiently. Malicious nodes can disrupt communication, drop packets, or launch various attacks on the network. By using fuzzy logic, this protocol considers multiple parameters and behaviors of nodes to identify potential malicious activities. Methods: In this work, fuzzy logic rules are utilized for evaluating various parameters and behaviors for nodes. Fuzzy inference system with linguistic variables and fuzzy rules is also established. Findings: In UWSN, Security is one of the key points of consideration in implementing the protocol. However current routing protocols have not been designed to defend against security attacks that can degrade the network performance. Since the nodes in UWSN are susceptible to malicious attacks, it is easier for an adversary to operate and to select UWSN channel along with communication nodes. In the UWSN environment, the presence of selfish nodes degrades the performance of the confidence nodes. This presence of selfish nodes in UWSN also leads to connection letdown between communication nodes. In this research work, an intelligent routing technique is introduced to Simple Shortest Path (SSP) routing protocol. We have added fuzzy-based security to SSP that enhances the SSP performance. This research work proposes fuzzy-based selfish node detection and removing those selfish nodes from routing. The parameters which describe the behavior of individual nodes are extracted and evaluated using fuzzy rules. The proposed SF_SSP provides higher throughput and packet Delivery Ratio compared to VBF, and SSP. Novelty: The novelty of detecting malicious nodes in underwater communication lies in its adaptive and robust trust evaluation using fuzzy logic to handle uncertainty and dynamic underwater conditions effectively. In this work, we have strengthened the Simple Shortest Path (SSP) routing scheme by adding fuzzy-based security rules.

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FCLR: Fuzzy Control-Based Layering Routing Protocol for Underwater Acoustic Networks

Cited by 15 publications

References 33 publications

Trust-Aware and Fuzzy Logic-Based Reliable Layering Routing Protocol for Underwater Acoustic Networks

Trust-Aware and Fuzzy Logic-Based Reliable Layering Routing Protocol for Underwater Acoustic Networks

Improved geographic opportunistic routing protocol for void hole elimination in underwater IoTs: Parameter tuning by TSA optimization

Secure Fuzzy Simple Shortest Path Routing Protocol (SF_SSP) for Underwater Communication

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