Efficient Content Distribution in Fog-Based CDN: A Joint Optimization Algorithm for Fog-Node Placement and Content Delivery

Efficient content distribution to end-users poses a significant challenge in content distribution networks (CDNs). Traditional CDNs rely on cloud-based architectures, which may not be optimal for delivering content in densely populated areas due to increased network latency and bandwidth limitations. These problems can be mitigated by adopting fog/edge computing, which deploys computing nodes near end-users to reduce latency and improve content delivery. Although factors such as deployment and distribution are often considered separately, there are relatively few studies on how node deployment affects content distribution. Moreover, current research on fog-based content distribution networks (fog-based CDNs) does not often address formal methods for key challenges, such as (R1) optimal fog node placement; (R2) providing efficient content distribution to end-users; and (R3) minimizing the overall fog-based CDN cost. Therefore, we propose an algorithm to jointly optimize the placement of fog nodes and the content distribution, called the joint optimization algorithm for the fog-node placement and content distribution (JFnP-CDA). The algorithm uses a two-step procedure including clustering and Voronoi method, and nonlinear programming to optimize R1, R2, and R3. We consider four parameters for this: 1) a given geographical region; 2) locations of open public Wi-Fi access points (OPWAPs) in that region; 3) Quality of Service (QoS, with delivery in delay as the measure); and 4) cost to generate optimal service subregions (and, thereby, distribute content to edge-network hot spots). We evaluated the effectiveness of the proposal by implementing real-world OPWAP data, and the results show that the algorithm JFnP-CDA outperforms the baseline methods.