A SURVEY ON OPTIMIZING DATA AGGREGATION AND SCHEDULING STRATEGIES FOR EFFICIENT MULTI-HOP IOT COMMUNICATION

Abstract

Internet of Things (IoT) has been raised as a fundamental component of making intelligent infrastructures of the next generation, whereby billions of devices can be interconnected to produce, share and process immense amounts of data. With the current development of the scale and complexity of the IoT networks, the development of efficient data aggregation, scheduling and routing mechanisms is critical to assure the reliability of the communication, low-energy consumption and responsiveness in real-time. The given survey is concerned with aggregation of data and optimization of the timeline of the deployment of multi-hop IoT networks, especially with the goal of enhancing Age of Information (AoI), minimizing consumption of power and ensuring data freshness. Energy efficient and clustering based aggregation strategies, trust based and secure routing mechanism, energy harvesting and resource allocation models, protocol level optimization and link scheduling techniques are all examined. The survey then proceeds to the IoT in the vehicular and industrial environments, where automated processes, operational safety and smart infrastructure require timely and reliable delivery of data. Various types of approaches are examined concerning reduction in latency, prolongation of network lifetime and reliability of its communication. New directions, such as adaptive AI-centered scheduling, cross-layer optimization and edge intelligence have been mentioned as some of the enablers of sustainable and reactive IoT communication. The survey further emphasizes the need to have context-sensitive, scalable and energy efficient architectures that have the potential to satisfy the dynamic requirements of the next-generation 6G-enabled IoT infrastructure and real-time intelligent applications.