IoT and Wireless Communication: Computer Science Approaches to Scalability and Reliability

Abstract

The rapid expansion of the Internet of Things (IoT) has significantly increased the demand for robust, scalable, and reliable wireless communication systems. As billions of interconnected devices generate vast volumes of data in real-time, ensuring efficient communication while maintaining system integrity has become a major challenge. This review explores the critical role of computer science in addressing these issues, focusing on key strategies and technologies that enhance the scalability and reliability of wireless IoT networks. The paper investigates algorithmic solutions for efficient routing, congestion control, and resource allocation, alongside architectural innovations such as edge computing, fog networking, and cloud-IoT integration. It also examines the role of artificial intelligence and machine learning in predictive maintenance, fault detection, and adaptive network optimization. Furthermore, the review discusses communication standards and protocols (e.g., LoRaWAN, Zigbee, NB-IoT) and their suitability for large-scale deployments. By integrating insights from distributed systems, cybersecurity, and software engineering, the paper offers a comprehensive overview of how computer science contributes to the development of resilient and scalable IoT wireless communication frameworks. This synthesis aims to guide future research and deployment strategies across smart cities, healthcare, agriculture, and industrial automation.