Reliable data dissemination for the Internet of Things using Harris hawks optimization
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Reliable data dissemination for the Internet of Things using Harris hawks optimization Ali Seyfollahi 1 & Ali Ghaffari 1 Received: 13 March 2020 / Accepted: 14 May 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract 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. Keywords Data dissemination . Reliable . Fuzzy clustering . Optimization . Metaheuristics
1 Introduction Interactions and communications in today’s world are not limited to Homo sapiens. It was thought that only humans would be able to connect with gadgets available through the Internet and take it in their control. Unaware of the fact the integration of heterogeneous physical devices and networks, even so, abstract entities to exchange data with the internet under the concept of IoT started in 2006 at 2 billion and will reach 200 billion by 2020 [1–3]. This marvelous perfection will pose a considerable challenge to accumulating and processing voluminous amounts of data temporal and spatial, especially for sensitive and real-time applications [4–6]. The large-scale deployment of entities, open architecture, and large volumes of confidential user data for processing make IoT a valuable subject for a variety of cyber threats. * Ali Ghaffari [email protected] Ali Seyfollahi [email protected] 1
Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran
Essential IoT security challenges include secure communications, privacy, access control, and safe data depository [7]. Likewise, the remarkable growth of appliances and the variety of services provided to users increase the potential vulnerability and insecurity of IoT-based apparatuses and data being collected or diffused [8–10]. Accordingly, despite a variety of attacks and vulnerabilities,
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