A Framework for Real-Time, Adaptive Mobile Agents for Data Aggregation in Edge Computing Environment

With the increased proliferation of Internet of Things (IoT) devices and cloud-based applications like Smart Cities, Surveillance, Weather Monitoring, Industrial IoT, Healthcare, Smart Agriculture, Smart Power Grids, etc., Edge Computing is emerging as a promising paradigm to mitigate the challenges posed by traditional cloud computing models to reduce latency and optimize communication. Data aggregation plays a pivotal role in realizing the full potential of edge computing. Efficient data aggregation is a significant challenge that is to be addressed in achieving the benefits of edge computing. This research proposes “A Framework for Real-Time, Adaptive Mobile Agents for Data Aggregation in Edge Computing Environment” to realize the reduced latency, bandwidth usage, and energy consumption. Mobile agents, which autonomously migrate across nodes to perform localized data collection for aggregation, present a efficient solution for efficient data aggregation by incorporating real time, adaptive behaviour. This research provides an adaptive solution for latency-sensitive and resource constrained applications in Health Care, Smart Cities, Industrial IoT, and autonomous systems like Self-Driving Vehicles.