Effective Data Transmission in NDN-Assisted Edge-Cloud Computing Model

The proliferation of data generated by Internet of Things (IoT) devices has prompted the pursuit of streamlined data retrieval as a fundamental objective. Although Edge computing performs computations locally while significantly reducing cloud overhead, it lacks location anonymity while integrating multiple clouds. Named Data Networking (NDN) as a novel Internet architecture provides location anonymity and enhances the efficacy of data exchange through caching. In this paper, we develop an efficient data retrieval system that protects file location privacy across multiple-cloud platforms by leveraging NDN and edge computing. In our Edge-NDN architecture, consumers perform data queries on the local network without connecting to the cloud. Initially, consumers search for edge-cacheable data; if content cannot be located, it is retrieved via an external connection to the cloud. We estimate the performance of the new work using NDN Forwarding Daemon (NFD), ndn-cxx, and jNDN tools. The empirical findings indicate that the proposed framework for facilitating anonymous data communication outperforms the conventional cloud-centric approach.