ICN-edge caching scheme for handling multimedia big data traffic in smart cities

Today, the rapid development, large volume, and global access of multimedia applications have demanded the shifting of network functionality from the central server to the near user. In recent times, Edge Computing (EC) and Information Centric Networking (ICN) have been presented as arising advances for content dissemination near the end user. The EC aims to provide content locally by reducing the burden of the core networks, while ICN allows content routing and forwarding based on content names directly. The inherent in-network caching feature of ICN facilitates caching by intermediate network nodes. The combined use of EC and ICN can efficiently handle content dissemination and ultimately improves user experience. In this regards, an ICN based edge caching scheme has been proposed for handling multimedia big data traffic in IoT based smart cities, while incorporating four caching attributes in its proposed design. Firstly, a layered network architecture has been presented that offers Device-to-Device (D2D) communication and ICN support at the application layer of Base station (BS) for utilizing caching of the requested content at edge of the network. Secondly, a decision on caching of contents at network nodes in layered network architecture has been presented based on various centrality measures, which supports efficient caching. Thirdly, this work offers caching of content near the delivery path in ICN network tiers, while leveraging near path caching for fast content dissemination. Lastly, reproactive caching where proactive caching is followed by reactive caching for controlling the network traffic during peak hours has been integrated in to the design model. The performance of the proposed scheme has been evaluated by conducting simulations in Icarus- an ICN caching simulator against various caching benchmark schemes. The results received from the experiments have shown significant performance improvement of our proposed scheme for different performance metrics including cache hit ratio, content retrieval delay, content path stretch, and internal link load.