Dynamic Partitioning and Popularity based Caching for Optimized Performance in content-centric fog networks: DPPCOP

Abstract

With the massive growth of information generation, processing, and distribution in the Internet of Things (IoT), the existing cloud architectures need to be designed more effectively using fog networks. The current IP-address-based Internet architecture is unable to deliver the desired Quality-of-Service (QoS) towards the increasing demands of fog networking-based applications. To this end, Content-Centric Networking (CCN) has been developed as the potential future Internet architecture. CCN provides name-based content delivery and is established as an architecture for next-generation fog applications. The CCN-based fog environment uses the cache of in-network fog nodes to place the contents near the end-user devices. Generally, the caching capacity of the fog nodes is very small as compared to the content catalog size. Therefore, efficient content placement decisions are vital for improving the network performance. To enhance the content retrieval performance for the end-users, a novel content caching scheme named “Dynamic Partitioning and Popularity based Caching for Optimized Performance (DPPCOP)” has been proposed in this paper. First, the proposed scheme partitions the fog network by grouping the fog nodes into non-overlapping partitions to improve content distributions in the network and to ensure efficient content placement decisions. During partitioning, the scheme uses the Elbow method to obtain the “good” number of partitions. Then, the DPPCOP scheme analyzes the partition’s information along with the content popularity and distance metrics to place the popular contents near the end-user devices. Extensive simulations on realistic network topologies demonstrate the superiority of the DPPCOP caching strategy on existing schemes over various performance measurement parameters such as cache hit ratio, delay, and average network traffic load. This makes the proposed scheme suitable for next-generation CCN-based fog networks and the futuristic Internet architectures for industry 4.0.