Secured cross‐layer cross‐domain routing in dense wireless sensor network: A new hybrid based clustering approach

Lahane, Shivaji R.; Jariwala, Krupa N.

doi:10.1002/int.22438

Cited by 12 publications

(7 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…𝐵 𝑗 (𝑡)+(𝑈𝐵 𝑗 −𝐿𝐵 𝑗 )+𝜖′ (5) Where, the 𝑀(𝑦 𝑖 ) represents the average positions that are shown in Eq. (6). 𝐿𝐵 𝑗 and 𝑈𝐵 𝑗 denotes the lower and upper limits of the M-TCRSA and the 𝛼 is fixed as 0.1. are satisfied, the M-TCRSA is processed with hunting coordination; Else, the hunting cooperation is performed as shown in Eq.…”

Section: 𝑃 (𝑖𝑗) = 𝛼 + 𝑦 (𝑖𝑗) −𝑀(𝑦 𝑖 )mentioning

confidence: 99%

See 1 more Smart Citation

Secure Cluster based Routing Using Multiobjective Trust Centric Reptile Search Algorithm for WSN

2023

IJIES

View full text Add to dashboard Cite

Wireless sensor networks (WSN) is self-organizing network that has numerous tiny sensor nodes used to track and monitor applications in an extensive range. However, security and energy consumption are considered two important issues, because of the open medium and restricted energy resources. In this paper, the multiobjective-trust centric reptile search algorithm (M-TCRSA) is proposed to perform the secure cluster based routing for WSN. The M-TCRSA is used to ensure the secure cluster head (SCH) and secure route discovery to achieve reliable communication over the WSN. Hence, the developed M-TCRSA method provides improved security against malicious attacks while enhancing energy efficiency. The main objective of the M-TCRSA is to achieve secure data transmission while increasing the life expectancy of the WSN. The performance of M-TCRSA is analyzed by means of packet delivery ratio (PDR), throughput, end to end delay (EED), jitter and life expectancy. The existing research such as trust-based routing using adaptive genetic algorithm (TAGA), trusted cluster based energy and lifetime aware routing (TCELR), secure clustering and routing using IMFO (SCRIMFO) and cost centric cuckoo search algorithm (CCCSA) are compared with the M-TCRSA. The PDR of the M-TCRSA is 99.27% for 400 nodes which is high when compared to the TAGA, TCELR, SCRIMFO and CCCSA.

show abstract

Section: 𝑃 (𝑖𝑗) = 𝛼 + 𝑦 (𝑖𝑗) −𝑀(𝑦 𝑖 )mentioning

confidence: 99%

“…WSNs are positioned in various application fields because of their less cost and ease of deployment features. The WSN applications are familiar in areas such as health care, smart buildings, railway monitoring, home security, military supervision, remote monitoring, and the agricultural field [6].…”

Section: Introductionmentioning

confidence: 99%

Secure Cluster based Routing Using Multiobjective Trust Centric Reptile Search Algorithm for WSN

2023

IJIES

View full text Add to dashboard Cite

show abstract

“…Lahane S R proposed WSNs lifetime extending model by extending the life cycle of message routing. The model was shown to outperform existing models [9]. Pedrycz W et al noticed the lack of accuracy in the DV-Hop localization and proposed a new algorithm.…”

Section: Related Workmentioning

confidence: 99%

Improved Sparrow Search Algorithm Optimized DV-Hop for Wireless Sensor Network Coverage

Kou

Wei

2023

IEEE Access

View full text Add to dashboard Cite

With the continuous improvement and development of wireless sensor network, it have been enriched to a great extent. Monitoring, processing and transmitting all kinds of sensing data is its main function, so their coverage issues have received widespread attention. Among them, the WSN coverage based on DV-Hop node positioning technology has low cost and power consumption with high scalability, and is extremely widely used. However, the current error control and WSN coverage of DV-Hop node positioning are not enough for practical applications. This research innovatively adopts an improved sparrow search pattern to optimise the DV-Hop localisation algorithm. The study introduces a deviation correction factor to adjust the minimum number of node hops and uses the minimum mean squared error criterion to correct the calculation error to reduce error. In addition, the study improved the sparrow search algorithm by means of a GPS optimisation population initialisation. In the algorithm performance comparison, GSSA showed the best convergence efficiency compared to other algorithms. The average error of the GSSADV-Hop localisation constructed in the study is 0.72 m, which is 77.71% less than the traditional DV-Hop error.The study provides a reference idea for the application of DV-Hop in WSN coverage, and offers a novel solution for the optimization of DV-Hop.

show abstract

“…The cross-layer approach is used for relay node selection by enabling interation between MAC and routing layers. Lahane et al [27] proposed a cross-layer routing approach based on hybrid clustering. In this approach the optimal selection of cluster head is achieved by moth flame integrated dragonfly algorithm taking consideration of parameters as energy consumption, throughput, delay etc.…”

Section: Related Workmentioning

confidence: 99%

A Novel Duty Cycle Based Cross Layer Model for Energy Efficient Routing in IWSN Based IoT Application

2022

KSII TIIS

View full text Add to dashboard Cite

Wireless Sensor Network (WSN) is considered as an integral part of the Internet of Things (IoT) for collecting real-time data from the site having many applications in industry 4.0 and smart cities. The task of nodes is to sense the environment and send the relevant information over the internet. Though this task seems very straightforward but it is vulnerable to certain issues like energy consumption, delay, throughput, etc. To efficiently address these issues, this work develops a cross-layer model for the optimization between MAC and the Network layer of the OSI model for WSN. A high value of duty cycle for nodes is selected to control the delay and further enhances data transmission reliability. A node measurement prediction system based on the Kalman filter has been introduced, which uses the constraint based on covariance value to decide the scheduling scheme of the nodes. The concept of duty cycle for node scheduling is employed with a greedy data forwarding scheme. The proposed Duty Cycle-based Greedy Routing (DCGR) scheme aims to minimize the hop count, thereby mitigating the energy consumption rate. The proposed algorithm is tested using a real-world wastewater treatment dataset. The proposed method marks an 87.5% increase in the energy efficiency and reduction in the network latency by 61% when validated with other similar pre-existing schemes.

show abstract

Secured cross‐layer cross‐domain routing in dense wireless sensor network: A new hybrid based clustering approach

Cited by 12 publications

References 43 publications

Secure Cluster based Routing Using Multiobjective Trust Centric Reptile Search Algorithm for WSN

Secure Cluster based Routing Using Multiobjective Trust Centric Reptile Search Algorithm for WSN

Improved Sparrow Search Algorithm Optimized DV-Hop for Wireless Sensor Network Coverage

A Novel Duty Cycle Based Cross Layer Model for Energy Efficient Routing in IWSN Based IoT Application

Contact Info

Product

Resources

About