Ngoc-Thanh Dinh, Young-Han Kim: An Efficient Correlation-Based Cache Retrieval Scheme at the Edge for Internet of Things
2/12/2020 – 08:07
School of Electronic Engineering, Soongsil University, Sangdo-dong, Dongjak-Gu, Seoul 06978, Korea
This paper is an extended version of the paper “Sensing Content Correlation-Aware In-Network Caching Scheme at the Edge for Internet of Things” written by N.-T Dinh, N.-N. Dao, Y. Kim, published in Proceedings of the 6th ACM Conference on Information-Centric Networking, Macao, China, 24–26 September 2019.
Sensors 2020, 20(23), 6846; https://doi.org/10.3390/s20236846
Existing caching mechanisms considers content objects individually without considering the semantic correlation among content objects. We argue that this approach can be inefficient in Internet of Things due to the highly redundant nature of IoT device deployments and the data accuracy tolerance of IoT applications. In many IoT applications, an approximate answer is acceptable. Therefore, a cache of an information object having a high semantic correlation with the requested information object can be used instead of a cache of the exact requested information object. In this case, caching both of the information objects can be inefficient and redundant. This paper proposes a caching retrieval scheme which considers the semantic information correlation of information objects of nodes for cache retrieval. We illustrate the benefits of considering the semantic information correlation in caching by studying IoT data caching at the edge. Our experiments and analysis show that semantic correlated caching can significantly improve the efficiency, cache hit, and reduce the resource consumption of IoT devices.