Adaptive Congestion Control in Information-Centric Networking for the IoT Sensor Network

Abstract

In order to diminish the network congestion rate and enhance the network performance of ICN (Information-Centric Networking) architecture, especially in the IoT (Internet of Things) era, this research proposes an adaptive congestion control mechanism for the IoT sensor network. Particularly, the proposal can response the content requests from the consumers by caching an appropriate number of content chunks at the ICN router according to the content popularity and priority levels. We also utilize both content popularity and priority-based ranking delay time for the data transmission from sensors to the data server. The evaluation results show that the proposal with the dynamic control/adaptive mechanism can provide higher network performance efficiency for the future Internet by achieving higher throughput with lower request (Interest) packet drop rate and higher cache hit rate as we increase the number of IoT sensors, then solving the network congestion issue in ICN.