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Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of Things

机译:物联网中基于QoS的基于分层的集群的QCM(查询控制机制)的性能评估和验证

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摘要

Internet of Things (IoT) facilitates a wide range of applications through sensor-based connected devices that require bandwidth and other network resources. Enhancement of efficient utilization of a heterogeneous IoT network is an open optimization problem that is mostly suffered by network flooding. Redundant, unwanted, and flooded queries are major causes of inefficient utilization of resources. Several query control mechanisms in the literature claimed to cater to the issues related to bandwidth, cost, and Quality of Service (QoS). This research article presented a statistical performance evaluation of different query control mechanisms that addressed minimization of energy consumption, energy cost and network flooding. Specifically, it evaluated the performance measure of Query Control Mechanism (QCM) for QoS-enabled layered-based clustering for reactive flooding in the Internet of Things. By statistical means, this study inferred the significant achievement of the QCM algorithm that outperformed the prevailing algorithms, i.e., Divide-and-Conquer (DnC), Service Level Agreements (SLA), and Hybrid Energy-aware Clustering Protocol for IoT (Hy-IoT) for identification and elimination of redundant flooding queries. The inferential analysis for performance evaluation of algorithms was measured in terms of three scenarios, i.e., energy consumption, delays and throughput with different intervals of traffic, malicious mote and malicious mote with realistic condition. It is evident from the results that the QCM algorithm outperforms the existing algorithms and the statistical probability value “P” < 0.05 indicates the performance of QCM is significant at the 95% confidence interval. Hence, it could be inferred from findings that the performance of the QCM algorithm was substantial as compared to that of other algorithms.
机译:物联网(IoT)通过需要带宽和其他网络资源的基于传感器的连接设备,促进了广泛的应用。异构物联网网络的有效利用的提高是一个开放的优化问题,网络泛洪通常会给它带来很大的痛苦。冗余,不需要和泛滥的查询是导致资源利用效率低下的主要原因。文献中的几种查询控制机制声称可以解决与带宽,成本和服务质量(QoS)有关的问题。这篇研究文章介绍了不同查询控制机制的统计性能评估,这些机制解决了能耗,能源成本和网络泛滥的最小化问题。具体而言,它评估了用于物联网中基于QoS的基于分层的集群的查询控制机制(QCM)的性能指标,该集群用于基于QoS的反应式泛洪。通过统计手段,本研究推断出QCM算法的重大成就,该成就优于主流算法,即分而治之(DnC),服务水平协议(SLA)和物联网的混合能源感知群集协议(Hy-物联网),用于识别和消除冗余泛洪查询。针对算法性能评估的推断分析是在三种情况下进行测量的,即能耗,延迟和具有不同流量间隔的吞吐量,恶意节点和具有实际情况的恶意节点。从结果可以明显看出,QCM算法的性能优于现有算法,并且统计概率值“ P” <0.05表明,在95%置信区间内,QCM的性能显着。因此,从发现中可以推断出,与其他算法相比,QCM算法的性能非常重要。

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