无线传感器网络的安全路由模型和均衡负载模型

Julianto Agus Prabowo, Harry Dhika
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引用次数: 2

摘要

无线传感器网络在为大数据和互联网提供实时数据访问方面发挥着非常重要的作用。然而,无线传感器网络的开放部署、能量限制以及缺乏集中管理使得其极易受到各种恶意攻击。在无线传感器网络中,识别恶意传感器设备并消除其感知信息在关键任务应用中起着非常重要的作用。由于传感器设备的资源约束特性,标准的加密和认证方案不能直接用于无线传感器网络。因此,需要节能和低延迟的方法来最大限度地减少恶意传感器设备的影响。提出了一种基于异构集群的wsn安全负载均衡路由(SLBR)方案。SLBR提供了一种更好的基于信任的安全度量,克服了传感器从好状态到坏状态振荡的问题,SLBR还平衡了CH之间的负载。因此,有助于实现更好的安全性、数据包传输和能效性能。通过实验,评估了所提出的SLBR模型与现有的基于信任的路由模型即指数猫群优化(ECSO)的性能。结果表明,SLBR模型在能效(即考虑到第一个传感器设备死亡和总传感器设备死亡的网络寿命)、通信开销、吞吐量、数据包处理延迟、恶意传感器设备误分类率和识别方面比ECSO具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SAFE ROUTING MODEL AND BALANCED LOAD MODEL FOR WIRELESS SENSOR NETWORK
Wireless Sensor Networks (WSNs) play a very important role in providing realtime data access for Big Data and Internet. However, the open deployment, energy constraint, and lack of centralized administration make WSNs very vulnerable to various kinds of malicious attacks. In WSNs identifying malicious sensor devices and eliminating their sensed information plays a very important role for mission critical applications. Standard cryptography and authentication schemes cannot be directly used in WSNs because of the resource constraint nature of sensor devices. Thus, energy efficient and low latency methodology is required for minimizing the impact of malicious sensor devices. This paper presents a Secure and Load Balanced Routing (SLBR) scheme for heterogeneous clustered based WSNs. SLBR presents a better trust-based security metric that overcomes the problem when sensors keep oscillating from good to bad state and vice versa, and also SLBR balances load among CH. Thus, aids in achieving better security, packet transmission, and energy efficiency performance. Experiments are conducted to evaluate the performance of proposed SLBR model over existing trust-based routing model namely Exponential Cat Swarm Optimization (ECSO). The result attained shows SLBR model attains better performance than ECSO in terms of energy efficiency (i.e., network lifetime considering first sensor device death and total sensor device death), communication overhead, throughput, packet processing latency, malicious sensor device misclassification rate and identification.
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