An optimized DEEC approach for efficient packet transmission in sensor based IoTs network

Asha, A.; Srivastava, Ashish Kumar; Doohan, Nitika Vats; Sharma, Dharmendra; Bist, Ankur Singh; Neware, Rahul; Kumar, Sarvesh

doi:10.1016/j.micpro.2022.104714

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…Sun et al [2] introduced a cost function in the clustering phase to make clustering more reasonable, but it had certain shortcomings in terms of node cost and network stability. Asha et al [3] considered the remaining energy of nodes in cluster head selection, improving network lifespan. Nurlan et al [4] performed weighted calculations based on factors such as base station location, the remaining energy of cluster heads, and node energy changes, enhancing network lifespan and throughput.…”

Section: Related Statusmentioning

confidence: 99%

“…Traditional clustering routing algorithms mainly include the Low-Energy Adaptive Clustering Hierar-chy (LEACH) [2], the Distributed Energy-Efficient Clustering (DEEC) [3], the Stable Election Protocol (SEP) [4]. These algorithms in WSN have some deficiencies and limitations, such as overburdened cluster head nodes, unstable intra-cluster topology, and low communication efficiency between the controller and data plane.…”

Section: Introductionmentioning

confidence: 99%

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WSN Cluster Routing Method Based on Improved Whale Optimization Algorithm

Sun,

Ma,

Jiang

et al. 2023

Preprint

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To address the energy consumption issue in the cluster routing protocol of the wireless sensor network (WSN), a Whale Optimization Algorithm based on Nonlinear factors and Chaotic mapping (NC-WOA) is designed. This improves the quality of the initial population, enhancing the algorithm's capacity for global exploration and escaping local optima. Furthermore, an Efficient Distributed and Energy-Saving Clustering Routing Algorithm (EDESC) is designed based on the NC-WOA algorithm. Factors of node energy, node distance, and node density are incorporated into the threshold function, applying NC-WOA in the cluster head selection stage. Simulation results demonstrate that the performance of the NC-WOA surpasses that of other algorithms. In terms of the number of rounds for the half of the nodes to die, compared to the Distributed High-Efficiency Entropy Energy-Saving Cluster Routing Algorithm (DHEEC) and the Distributed Energy-Efficient Clustering with Firefly Algorithm (DEEC-FA), EDESC showed an improvement of 27.45% and 47.81%, respectively. The energy utilization ratio is enhanced by 16.63% compared to DHEEC and by 83.32% compared to DEEC-FA.

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Section: Related Statusmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

WSN Cluster Routing Method Based on Improved Whale Optimization Algorithm

Sun,

Ma,

Jiang

et al. 2023

Preprint

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A Load-Aware Energy-Efficient Clustering Algorithm in Sensor-Cloud

Zhao,

Wang,

Wang

et al. 2023

J Grid Computing

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MOMTA-HN: A Secure and Reliable Multi-Objective Optimized Multipath Transmission Algorithm for Heterogeneous Networks

Qi,

Yang,

et al. 2024

Electronics

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With the rapid development of heterogeneous network technologies, such as mobile edge computing, satellite communications, self-organizing networks, and the wired Internet, satisfying users’ increasingly diversified and complex communication needs in dynamic and evolving network environments has become a critical research topic. Ensuring secure and reliable information transmission is essential for stable network operation in these complex environments. Addressing this challenge, this study proposed a secure and reliable multi-objective optimized multipath transmission algorithm for heterogeneous networks to enhance security and reliability during data transmission. The core principle of this algorithm was that multipath transmission can provide additional protection through redundant paths. This redundancy ensured that even if one path is attacked or fails, alternative paths can maintain data integrity and reachability. In this study, we employed the Optimized Non-dominated Sorting Genetic Algorithm II (ONSGA-II) to determine the range of the initial population and filter suitable paths by optimizing them according to different demand objectives. In the path selection process, we introduced an innovative deletion graph method, which ensures that redundant paths do not share any common links with the original paths, except when there are unique links. This approach enhances the independence of transmission paths and improves the security of the transmission process. It effectively protects against security threats such as single points of failure and link attacks. We have verified the effectiveness of the algorithm through a series of experiments, and the proposed algorithm can provide decision-makers with high-reliability and low-latency transmission paths in heterogeneous network environments. At the same time, we verified the performance of the algorithm when encountering attacks, which is superior to other classical algorithms. Even in the face of network failures and attacks, it can maintain a high level of data integrity and security.

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An optimized DEEC approach for efficient packet transmission in sensor based IoTs network

Cited by 3 publications

References 25 publications

WSN Cluster Routing Method Based on Improved Whale Optimization Algorithm

WSN Cluster Routing Method Based on Improved Whale Optimization Algorithm

A Load-Aware Energy-Efficient Clustering Algorithm in Sensor-Cloud

MOMTA-HN: A Secure and Reliable Multi-Objective Optimized Multipath Transmission Algorithm for Heterogeneous Networks

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