IoT data management for caching performance improvement in NDN

Abstract

Abstract Connected devices in IoT continuously generate monitoring and measurement data to be delivered to application servers or end-users. Transmitting IoT data through networks would lead to congestion and long delay. NDN is an emerging network paradigm based on name-identified data known to be an appropriate architecture in supporting IoT networks. In-network caching is one of the main advantages of NDN, a major issue discussed in many studies. One of the significant challenges for some IoT data is the transiency nature, making the data caching mechanism different. In this study, the cache placement and data placement are considered together. Data placement is decided upon based on the data lifetime and node position. Data lifetime is an essential property that must be involved in caching methods to prevent invalid data delivery; consequently, the data are classified based on the data lifetime, and specific nodes are selected for caching according to defined classes and nodes position in topology. The objective is to reduce redundancy caused by data caching on all nodes of the data delivery path. By considering both the cache and data placements for transient data, a more comprehensive view is grasped in improving the caching performance. This issue, which has not been addressed in the available studies run on IoT data caching, can lead to the appropriate use of available storage and also reduce redundancy. The obtained results indicate that this method can improve the transient data caching efficiency.