WSN 的增强型 CH 选择和节能路由算法

Aarti Sharma, Ankush Kansal
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摘要

如今,无线传感器网络(WSN)已被广泛应用于战场监控、工业过程控制、管道监控、国防和军事事务等众多领域。在开展各种节能工作的同时,并没有解决数据传输过程的安全问题。将数据高效、安全地传输到所需位置是一项极具挑战性的任务。在这一领域已经开展了多项研究,但还存在一些局限性,比如没有考虑恶意节点,而且使用了非常复杂的加密和密钥管理等认证系统。本文提出了一种安全的高能效算法,利用改进的 LEACH 算法、Fire Fly 算法(FFA)和人工神经网络(ANN)进行优化,以克服上述所有问题。与仅使用基于概率的随机数进行簇头选择的现有 LEACH 相比,簇头选择使用了新的阈值,同时考虑了节点的剩余能量、平均能量和覆盖距离。由于路由中存在恶意节点,网络性能会下降,数据丢失率会增加,因此需要高能效和安全的路由协议。为了满足这一要求,我们使用了萤火虫算法来获取优化节点的属性作为输出,然后将这些数据传递给 ANN,以提供现有路由中的通信节点和非通信节点,以及攻击者节点。在区分节点的基础上,通过消除路由中的恶意节点,开发出从源头到目的地的优化路由。仿真结果表明,与现有方法相比,网络的各种服务质量参数都有所改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Enhanced CH selection and energy efficient routing algorithm for WSN

These days, Wireless Sensor Networks (WSNs) have been broadly utilized in numerous areas such as battlefield surveillance, industrial process control, pipeline monitoring, defence and military affairs, and so forth. Various energy efficient works are conducted without addressing the secured data transmission process. It is very challenging task to transfer data efficiently and securely to the desired location. Various researches has been done in this field but there are few limitations like malicious nodes are not considered and very complex systems are used for authentication like encryption and key management. In this paper a secure energy efficient algorithm using improved LEACH in optimization with Fire Fly algorithm (FFA) and Artificial neural network (ANN) to overcome all above said issues has been proposed. Cluster head selection is done using a new threshold value taking into account residual energy, average energy and covering distance of the nodes as compared to existing LEACH which uses only a probability based random number for CH selection. Due to the presence of malicious nodes in the route network performance degrades and data drop rate increases so there is need of energy efficient along with secure routing protocol. To fulfil this requirement firefly algorithm is used to get optimized node properties as output then this data is passed to ANN to provide communicating and non-communicating nodes as a result and attacker node in the existing route. Based on this differentiation of nodes an optimized route is developed from source to destination by eliminating the malicious nodes from the route. Simulation results demonstrate that there is an improvement in various Qos parameters of network as compared to existing approaches.

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