Journal Article10.1371/journal.pone.0289173
A cluster-tree-based trusted routing algorithm using Grasshopper Optimization Algorithm (GOA) in Wireless Sensor Networks (WSNs)
Mehdi Hosseinzadeh,Omed Hassan Ahmed,Jan Lánský,Stanislava Mildeová,Mohammad Sadegh Yousefpoor,Efat Yousefpoor,Joon Yoo,Lilia Tightiz,Amir Masoud Rahmani +8 more
TL;DR: A cluster-tree-based trusted routing algorithm using Grasshopper Optimization Algorithm (GOA) in Wireless Sensor Networks (WSNs) proposes a comprehensive routing scheme that guarantees security and energy efficiency simultaneously.
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Abstract: In wireless sensor networks (WSNs), existing routing protocols mainly consider energy efficiency or security separately. However, these protocols must be more comprehensive because many applications should guarantee security and energy efficiency, simultaneously. Due to the limited energy of sensor nodes, these protocols should make a trade-off between network lifetime and security. This paper proposes a cluster-tree-based trusted routing method using the grasshopper optimization algorithm (GOA) called CTTRG in WSNs. This routing scheme includes a distributed time-variant trust (TVT) model to analyze the behavior of sensor nodes according to three trust criteria, including the black hole, sink hole, and gray hole probability, the wormhole probability, and the flooding probability. Furthermore, CTTRG suggests a GOA-based trusted routing tree (GTRT) to construct secure and stable communication paths between sensor nodes and base station. To evaluate each GTRT, a multi-objective fitness function is designed based on three parameters, namely the distance between cluster heads and their parent node, the trust level, and the energy of cluster heads. The evaluation results prove that CTTRG has a suitable and successful performance in terms of the detection speed of malicious nodes, packet loss rate, and end-to-end delay.
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Figures
Table 1. Comparison of the related works. 
Fig 12. Comparison of PLR in different schemes. 
Fig 11. Comparison of the detection speed of different methods in FA attack. 
Fig 14. Comparison of energy consumption in different methods. 
Fig 13. Comparison of delay in different methods. 
Fig 4. Comparison of the trust changes of GH nodes in different schemes.
Citations
A Q-learning-based smart clustering routing method in flying Ad Hoc networks
Mehdi Hosseinzadeh,Jawad Tanveer,Amir Masoud Rahmani,Khursheed Aurangzeb,Efat Yousefpoor,Mohammad Sadegh Yousefpoor,Aso Mohammad Darwesh,Mahmood Fazlali,Sang-Woong Lee +8 more
TL;DR: This paper proposes QSCR, a Q-learning-based smart clustering routing method for flying ad hoc networks, which adapts to dynamic topologies, optimizes energy efficiency, and improves network lifetime, while achieving high packet delivery rates and reduced isolated clusters.
11
Efficient cluster-based routing protocol for wireless sensor networks by using collaborative-inspired Harris Hawk optimization and fuzzy logic
Huangshui Hu,Xinji Fan,Chuhang Wang +2 more
TL;DR: CHHFO, a new protocol that combines a fuzzy logic system with the collaborative Harris Hawks optimization algorithm to enhance the lifetime of networks, is presented.
4
DCFH: A dynamic clustering approach based on fire hawk optimizer in flying ad hoc networks
Mehdi Hosseinzadeh,Saqib Ali,Husham Jawad Ahmad,Faisal Alanazi,Mohammad Sadegh Yousefpoor,Efat Yousefpoor,Aso Mohammad Darwesh,Amir Masoud Rahmani,Sang-Woong Lee +8 more
4
A novel Q-learning-based secure routing scheme with a robust defensive system against wormhole attacks in flying ad hoc networks
Mehdi Hosseinzadeh,Saqib Ali,Husham Jawad Ahmad,Faisal Alanazi,Mohammad Sadegh Yousefpoor,Efat Yousefpoor,Omed Hassan Ahmed,Amir Masoud Rahmani,Sang-Woong Lee +8 more
TL;DR: A novel Q-learning-based secure routing scheme (QSR) is proposed for flying ad hoc networks (FANETs) to counter wormhole attacks through encapsulation and packet relay, achieving better performance than existing schemes in terms of accuracy and malicious node detection.
2
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