The Fusion of Edge Computing and Cloud Computing

Abstract

Edge computing, by moving data processing closer to the source, compensates for the latency issues of centralized cloud computing. The integration of both paradigms is steering IT architectures toward more efficient, low-latency solutions.

 

Main Text

Traditional cloud computing processes data in centralized data centers; although resource-rich, this approach suffers from high latency, making it unsuitable for real-time applications. Edge computing deploys smaller data centers near the network’s edge, offloading certain computing tasks locally to achieve rapid responses. Several cities in the United States, Europe, and China have already begun experimenting with models that combine edge and cloud computing.

This fusion model shows clear advantages in IoT, autonomous driving, smart surveillance, and other areas, yet it also faces technical challenges related to distributed management and data consistency. In the future, as 5G becomes more widespread and edge devices gain in power, the integration of edge and cloud computing will become increasingly seamless, forming an efficient platform for real-time data processing.

 

Conclusion

The convergence of edge and cloud computing offers a new approach to real-time data processing by compensating for the limitations of each individual model. With continuous technological improvements and standardized frameworks, this integration will drive industries into a smarter, more efficient era.

 

References

 

Zhao Min, “Fusion of Edge and Cloud Computing: A New Model for Real-Time Response”, Net World, March 2023.

David Lee, “Edge and Cloud Convergence for Real-Time Processing,” InfoQ, 2022.