PriNergy: a priority-based energy-efficient routing method for IoT systems
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PriNergy: a priority‑based energy‑efficient routing method for IoT systems Fatemeh Safara1 · Alireza Souri2 · Thar Baker3 · Ismaeel Al Ridhawi4 · Moayad Aloqaily5
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The Internet of Things (IoT) devices gather a plethora of data by sensing and monitoring the surrounding environment. Transmission of collected data from the IoT devices to the cloud through relay nodes is one of the many challenges that arise from IoT systems. Fault tolerance, security, energy consumption and load balancing are all examples of issues revolving around data transmissions. This paper focuses on energy consumption, where a priority-based and energy-efficient routing (PriNergy) method is proposed. The method is based on the routing protocol for low-power and lossy network (RPL) model, which determines routing through contents. Each network slot uses timing patterns when sending data to the destination, while considering network traffic, audio and image data. This technique increases the robustness of the routing protocol and ultimately prevents congestion. Experimental results demonstrate that the proposed PriNergy method reduces overhead on the mesh, end-to-end delay and energy consumption. Moreover, it outperforms one of the most successful routing methods in an IoT environment, namely the quality of service RPL (QRPL). Keywords Internet of Things · Priority-based routing · Energy consumption · Lowpower and lossy networks
1 Introduction The Internet of Things (IoT) plays an increasingly significant role in our daily lives, as it maintains better service quality through continuous data collection [1, 2]. Sustainable IoT is a system of interconnected smart mechanical machines, computing devices, digital machines and objects with the capability of transmitting data on a network of connected intermediate nodes to a cloud data center. * Alireza Souri [email protected] Extended author information available on the last page of the article
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Stationary and mobile IoT devices aid in the provisioning of both simple and complex services for cloud environments and big data applications [3]. However, as the size of an IoT application grows, the limitations of such IoT devices can be noticed. Fault tolerance, security, energy consumption and load balancing are all examples of challenges that face data transmissions within large-scale IoT applications. Among these challenges, energy consumption has gained particular attention in the recent literature [4, 5]. Energy-aware IoT applications in the light of consumption, harvesting, computing as well as energy optimization are becoming a critical industry issue [6, 7]. IoT has paved the path for low-power devices to become part of the Internet and contribute to the collection and exchange of data to meet the requirements of the deployed systems. The deployment of such systems has revolutionized the exchange of information and services in a variety of fields including health and envi
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