Dynamic Orchestration of Distributed Streaming Analytics in Edge-Integrated Cloud Platforms for Real-Time Event Detection
Keywords:
Edge Computing, Cloud-Edge Integration, Real-Time Analytics, Stream Processing, Event Detection,, Dynamic Orchestration, Distributed Systems, Adaptive SchedulingAbstract
Edge-integrated cloud computing has emerged as a vital architecture for real-time analytics in smart infrastructure, healthcare, and industrial monitoring systems. However, managing streaming analytics across geographically dispersed and heterogeneous edge-cloud nodes presents new challenges. This research proposes a dynamic orchestration model that adapts dataflow task allocation in real time. The system leverages resource-aware scheduling policies, runtime monitoring, and lightweight migration mechanisms to ensure low latency, high throughput, and resilience. Our evaluation shows improved performance over static orchestration methods under real-time constraints.
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