Information-Centric Networking (ICN) is a new Internet architecture design, which is considered as the global-scale Future Internet (FI) paradigm. Though ICN offers considerable benefits over the existing IP-based Internet architecture, its practical deployment in real life still has many challenges, especially in the case of high congestion and limited power in a sensor enabled-network for the Internet of Things (IoT) era. In this paper, we propose a smart congestion control mechanism to diminish the network congestion rate, reduce sensor power consumptions, and enhance the network performance of ICN at the same time to realize a complete green and efficient ICN-based sensor networking model. The proposed network system uses the chunk-by-chunk aggregated packets according to the content popularity to diminish the number of exchanged packets needed for data transmission. We also design the sensor power-based cache management strategy, and an adaptive Markov-based sensor scheduling policy with selective sensing algorithm to further maximize power savings for the sensors. The evaluation results using ndnSIM (a widely-used ICN simulator) show that the proposed model can provide higher network performance efficiency with lower energy consumption for the future Internet by achieving higher throughput with higher cache hit rate and lower Interest packet drop rate as we increase the number of IoT sensors in ICN.

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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.