Reliable data dissemination for the Internet of Things using Harris hawks optimization

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.