ArticleScientific reports2023
A cluster-based trusted routing method using fire hawk optimizer (FHO) in wireless sensor networks (WSNs).
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 54 citations in OpenAlex.
- High-Value Patents Recognition with Random Forest and Enhanced Fire Hawk Optimization Algorithm.Biomimetics (Basel, Switzerland) · 2025Article
- A dual layer secure and energy-efficient model for border surveillance using sea lion inspired strategy in wireless sensor networks.Scientific reports · 2025Article
- Hybrid Reliable Clustering Algorithm with Heterogeneous Traffic Routing for Wireless Sensor Networks.Sensors (Basel, Switzerland) · 2025Article
- Optimal parameter identification of solid oxide fuel cell using modified fire Hawk algorithm.Scientific reports · 2024Article
- Energy efficient clustering and routing protocol based on quantum particle swarm optimization and fuzzy logic for wireless sensor networks.Scientific reports · 2024Article
- A local filtering-based energy-aware routing scheme in flying ad hoc networks.Scientific reports · 2024Article
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Authors and funding
9 authors at 7 institutions in 7 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Today, wireless sensor networks (WSNs) are growing rapidly and provide a lot of comfort to human life. Due to the use of WSNs in various areas, like health care and battlefield, security is an important concern in the data transfer procedure to prevent data manipulation. Trust management is an affective scheme to solve these problems by building trust relationships between sensor nodes. In this paper, a cluster-based trusted routing technique using fire hawk optimizer called CTRF is presented to improve network security by considering the limited energy of nodes in WSNs. It includes a weighted trust mechanism (WTM) designed based on interactive behavior between sensor nodes. The main feature of this trust mechanism is to consider the exponential coefficients for the trust parameters, namely weighted reception rate, weighted redundancy rate, and energy state so that the trust level of sensor nodes is exponentially reduced or increased based on their hostile or friendly behaviors. Moreover, the proposed approach creates a fire hawk optimizer-based clustering mechanism to select cluster heads from a candidate set, which includes sensor nodes whose remaining energy and trust levels are greater than the average remaining energy and the average trust level of all network nodes, respectively. In this clustering method, a new cost function is proposed based on four objectives, including cluster head location, cluster head energy, distance from the cluster head to the base station, and cluster size. Finally, CTRF decides on inter-cluster routing paths through a trusted routing algorithm and uses these routes to transmit data from cluster heads to the base station. In the route construction process, CTRF regards various parameters such as energy of the route, quality of the route, reliability of the route, and number of hops. CTRF runs on the network simulator version 2 (NS2), and its performance is compared with other secure routing approaches with regard to energy, throughput, packet loss rate, latency, detection ratio, and accuracy. This evaluation proves the superior and successful performance of CTRF compared to other methods.
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Registered trials
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