IoT-Based Distributed Sensor Networks: A Comprehensive Survey

Abstract

Distributed sensor networks have become widely deployed due to the development of Internet of Things (IoT) devices. These networks are essential in many fields, such as smart cities, healthcare, agriculture, and environmental monitoring. The increasing use of intelligent Internet of Things (IoT) devices has spurred research into improving offline functionality, energy efficiency, scalability, and security. In this context, the combination of distributed ledger technology (DLT) and distributed intelligence (DI) emerges as a practical route toward decentralizing IoT architectures. This thorough overview article examines DI approaches in IoT, outlining the necessity of DI at the outset and offering a taxonomy of DI in IoT. Cloud computing, mist computing, distributed ledger technology, service-oriented computing, and hybrid approaches are the five divisions into which the taxonomy divides IoT DI techniques. The level of intelligence supported and related issues are considered when reviewing existing techniques. The survey evaluates over thirty research efforts, defining significant functionalities that DI frameworks should support. The advantages and drawbacks of various DI methodologies are discussed, motivating further research into automatic hybridization and DI mechanism modification. Lastly, open research questions about distributed intelligence in the Internet of Things are explored, offering insightful information to developers and system architects. The main features of Internet of Things-based distributed sensor networks, such as architecture, data fusion methods, energy efficiency, security, and communication protocols, are examined in this survey article. The study also addresses new developments and difficulties in this area.