Predictive Connectivity Management for Reliable Communication in Intelligent Edge Networks
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DOI:
https://doi.org/10.67228/30715725/IJIARE-V9I2P103Published 04-10-2026
Predictive Connectivity Management, Intelligent Edge Networks, Edge Computing, Machine Learning, Network Reliability, Mobility Prediction, Proactive Handover, Quality of Service, Internet of Things, Communication Resilience Issue
Section
ArticlesAbstract
This research proposes a Predictive Connectivity Management Framework to improve communication reliability in Intelligent Edge Networks supporting IoT, autonomous systems, industrial automation, and connected vehicles. Traditional reactive methods often struggle with dynamic network conditions, device mobility, and changing traffic demands. The proposed framework integrates machine learning, contextual network monitoring, mobility prediction, adaptive resource allocation, and proactive connection switching to reduce latency and maintain service continuity. Its performance will be evaluated using reliability, latency, handover performance, packet delivery ratio, and service continuity. The study provides a foundation for developing context-aware, low-latency, and resilient communication systems, with experimental validation required to confirm its effectiveness.
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