使用萤火虫群算法和混合安全算法为物联网-无线局域网选择簇头和安全路由

Prakash M., Prakash A.
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摘要

无线传感器网络(WSN)因其自配置性、维护简便性和扩展能力,在许多行业受到广泛关注。WSN 配置了额外的节点,以便在网络中传输数据。传感器网络的通常特点是低带宽、低能耗、电力供应有限和内存空间小,这使得这些网络的安全性特别困难。簇中的 CH(簇首)比其他簇节点承受更重的流量负荷。这就导致了热点问题。因此,在面向集群的路由方案中,选择合适的 CH 至关重要。本研究建议采用两级安全来保障 WSN 的数据传输。本文提出了一种新颖的 CH 选择方法,以提高网络的寿命和能效。这项研究还结合了基于适配性的果蝇算法(FGF)和萤火虫群算法(GSA),以选择最佳 CH。为了保护网络免受攻击,它采用了一种混合安全方法,该方法结合了 Diffie-Hellman 密钥交换机制和 ECC(椭圆曲线加密)算法。所建议的 GSA-HSA 协议在 MSR(信息成功率)、E2E(端到端)延迟、NT(网络吞吐量)和网络吞吐量以及平均 AEE(能效)方面始终保持着良好的性能。所建议的方法为无线传感器网络提供了安全、优化覆盖和节能的综合优势,优于之前的所有研究。
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Cluster Head Selection and Secured Routing Using Glowworm Swarm Algorithm and Hybrid Security Algorithm for Over IoT-WSNs
WSNs (Wireless Sensor Networks) have received a lot of attention in a number of industries due to its self-configurability, simplicity in maintenance, and scaling capacities. WSN is configured with extra nodes in order to transport data around the network. The usual characteristics of sensor networks are low bandwidth, low energy, constrained power supply, and little memory space, which makes security particularly difficult in these networks. CH (Cluster heads) in a cluster experience heavier traffic loads than other cluster nodes. This results in the hotspot problems. Therefore, in a cluster-oriented routing scheme, picking the right CH is crucial. The two-level security is recommended in this research to safeguard data transmission via the WSN. A novel CH selection methodology is presented in order to increase the network's lifespan and energy effectiveness. This work also combines the fruit fly algorithm (FGF) with the GSA (firefly swarm algorithm) based on fitness to choose the optimal CH. To defend the network from assaults, it employs a hybrid security method that combines the Diffie-Hellman key exchange mechanism and the ECC (elliptic curve cryptography) algorithm. The suggested GSA-HSA protocol consistently produces good performance results in terms of MSR (Message Success Rate), E2E (End-to-End) Latency, NT (Network Throughput), and network throughput. average AEE (energy efficiency). The suggested approach outperforms all prior research by giving the wireless sensor network combination security, optimised coverage, and energy savings.
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