无线传感器网络中OMIEEPB路由协议容错特性的集成

I. Nasurulla, R. Kaniezhil
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引用次数: 1

摘要

鉴于人工操作员很难连续观察网络基础设施及其功能,无线传感器网络(WSN)节点必须克服故障并将感知到的数据路由到接收器/基站(BS)。本文研究的主要目标是保证系统的容错能力,特别是保证传感数据无故障地传输到目的地的容错能力。因此,通过本文,引入了基于模糊的从属支持(FSS)系统,作为现有的优化移动sink改进的基于PEGASIS (Power-Efficient Gathering in Sensor Information Systems)的路由协议(OMIEEPB)的附加功能,该协议缺乏对相应链中所选领导者的FT能力的保证。FSS的中心重点是防止故障的发生,特别是簇头故障的发生。设计/方法/方法由于随机事件或不同原因,如能量耗尽、部署区域的负面影响、信号干扰、供电路线不平衡、由于不对准和碰撞导致的motes不稳定等,wsn会遇到一些问题,最终导致网络的失败。在过去的调查期间,研究人员了解了容错策略,这些策略可以提高数据完整性或可靠性、精度、能源效率、系统的预期寿命,并减少/防止部署组件的故障。如果是这种情况,需要可靠而准确地将数据包(感知到的)传输到汇聚节点或BS的最大机会就会降低。FSS系统利用模糊逻辑概念,已被证明是有益的,因为它允许几个参数有效地组合和评估。这里,近点、剩余能量、总操作时间和过去的平均处理时间被认为是重要的参数。此外,FSS系统保证了网络的关键性能活动,如优化响应时间,提高数据传输的可靠性和准确性。通过Mannasim框架进行了基于仿真的实验。经过多次实验执行,通过与现有先进系统的详细比较,分析了所提出系统的效果。最后,观察到FSS系统不仅将FT特征增强到OMIEEPB,而且在leader与正常节点之间的数据通信中,以优化的响应时间(<0.09 s)保证了提高的精度水平(>95%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integration of fault-tolerant feature to OMIEEPB routing protocol in wireless sensor network
PurposeWhereas a human operator is hard to observe the networking infrastructure and its functions on a continuous basis, wireless sensor network (WSN) nodes must overcome faults and route the perceived data to the sink/base stations (BS). The main target of this research article is to ensure the fault-tolerance (FT) capability, especially for transmission of sensed data to its destination without failure. Thus, through this paper, a fuzzy-based subordinate support (FSS) system is introduced as an additional feature to the existing optimized mobile sink improved energy efficient Power-Efficient Gathering in Sensor Information Systems (PEGASIS)-based (OMIEEPB) routing protocol, which lacks focus on ensuring the FT capabilities to the selected leaders of the corresponding chain. The central focus of FSS is to prevent the incident of fault, especially to the cluster heads.Design/methodology/approachWSNs encounter several issues owing to random events or different causes such as energy exhaustion, negative influences of the deployed region, signal interference, unbalanced supply routes, instability of motes due to misalignments and collision, which ultimately intends the failure of the network. Throughout the past investigation periods, researchers gain an understanding of fault-tolerant strategies that may improve the data integrity or reliability, precision, energy efficiency, the life expectancy of the system and reduce/prevent the failure of deployed components. If that is the case, the maximum chances of data packets (sensed) needed to be transferred reliably and accurately to the sink node or BS are degraded.FindingsThe FSS system utilizes the fuzzy logic concepts that have been proved to be beneficial since it permits several parameters to be combined effectively and evaluated. Here, near-point, residual energy, total operation time and past average processing time are considered as vital parameters. Moreover, the FSS system ensures the key performance activities of the network, such as optimization of response time, enhancing the data transmission reliability and accuracy. Simulation-based experiments are carried out through the Mannasim framework. After several experimental executions, the outcome of the proposed system is analyzed through elaborated comparison with the advanced existing systems.Originality/valueFinally, it has been observed that the FSS system not only enhanced the FT features to OMIEEPB but also assures the improved accuracy level (>95%) with optimized response time (<0.09 s) during data communication between leaders and the normal nodes.
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