PbCP: A profit-based cache placement scheme for next-generation IoT-based ICN networks

Abstract

The large number of connected devices generating a massive amount of data in the emerging technologies such as the Internet of Things (IoT), will surpass the capabilities of the current Internet infrastructure. Therefore, it is essential to design a new communication paradigm to meet the demands and requirements of new applications. Information-Centric Networking (ICN) is a new candidate for future Internet architecture that aims at addressing different challenges in the currently used host-centric Internet. In ICN, the data/content is searched, routed, located, and retrieved through the name of the content rather than the address of data source. ICN also enables in-network caching where the intermediate nodes can cache the content. In-network caching helps in improving the network scalability and reduces the content retrieval delay. To date, multiple caching schemes have been designed for IoT data management in ICN; however, most of them suffer from scalability or ignore constraints on the IoT devices. Moreover, the placement of content in a large-scale environment needs further improvement and optimization since it impacts overall network performance. To fill the gaps, in this paper, we combine various metrics that affect caching performance. We formulate the content placement as an optimization problem and then propose a profit-based caching scheme that harnesses the benefits of the Tabu local search algorithm. The simulation results and comparative analysis show that the proposed strategy outperforms the existing state-of-art schemes, notably in terms of memory resources utilization, data transmission time, content diversity ratio, and cache replacement operations.