Internet of Things (IoT) entities compile a massive volume of sensing data and transmit it to the cloud for processing and reasoning. Reliable and secure data aggregation and forwarding in IoT incorporates resource-constrained low-power and lossy devices that served diverse and sensitive applications with special obligations is a significant challenge for IoT. This paper proposes Reliable Data Dissemination for the Internet of Things Using Harris Hawks Optimization (RDDI) scheme, which is a secure data diffusion mechanism that accoutered a fuzzy hierarchical network model for Wireless Sensor Networks (WSN) based IoT. RDDI discloses attacks and monitors the behavior of nodes information exchange processes. Our scheme prowls to synthesize routing capabilities, energy-aware and geographic data circulation, and fuzzy clustering to provide a reliable, nature-inspired optimized routing called Harris Hawks Optimization (HHO) algorithm for IoT. The performance of RDDI, under five metrics of reliability, end-to-end delay, energy consumption, computational overhead as well as packet forwarding distance in multi-cluster scenarios, is evaluated with three comparative approaches. Findings of simulations reveal that RDDI achieves a reliable strategy and preferable achievement over the other three disposals.

物联网（IoT）实体会编译大量传感数据，并将其传输到云中进行处理和推理。物联网中可靠，安全的数据聚合和转发结合了资源受限的低功耗有损设备，这些设备以特殊的义务服务于各种敏感的应用程序，这对物联网是一项重大挑战。本文提出了使用Harris Hawks Optimization（RDDI）进行物联网的可靠数据分发方案，这是一种安全的数据扩散机制，为基于无线传感器网络（WSN）的物联网提供了模糊层次网络模型。RDDI公开攻击并监视节点信息交换过程的行为。我们的方案致力于综合路由功能，能源感知和地理数据流通以及模糊聚类，以提供一种可靠的，受自然启发的优化路由，称为Harris Hawks Optimization（HHO）物联网的算法。使用三种比较方法评估了RDDI的性能，这些性能在可靠性，端到端延迟，能耗，计算开销以及包转发距离等五个指标下进行了评估。模拟的结果表明，RDDI实现了可靠的策略，并且比其他三种处理方法更可取。