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An Efficient Content Store-Based Forwarding Scheme for Internet of Things

Authors
Dinh, Ngoc-ThanhKim, Younghan
Issue Date
Nov-2021
Publisher
MDPI
Keywords
Internet of Things; wireless sensor networks; information centric networking; forwarding scheme; content store; information objects
Citation
SENSORS, v.21, no.22
Journal Title
SENSORS
Volume
21
Number
22
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/41644
DOI
10.3390/s21227607
ISSN
1424-8220
Abstract
One of the main advantages of information-centric networking (ICN) is that a requested piece of content can be retrieved from a content store (CS) at any intermediate node, instead of its original content producer. In existing ICN designs, nodes forward Interest packets mainly based on forwarding information base (FIB). FIB is constructed from name prefixes registered by content producers with a list of next hops to the name prefixes. The ICN forwarding engine uses those information to forward Interest packets towards corresponding content producers. CS information of a node is currently used only for checking the availability of cached content objects at the node and is not considered in the data plane of existing ICN forwarding mechanisms. This paper highlights the importance of CS information in an ICN forwarding mechanism and enables neighbor CS information in the data plane to improve the cache hit ratio and forwarding efficiency, especially for resource-constraint Internet of Things (IoT). We propose an efficient CS-based forwarding scheme for IoT. The proposed forwarding scheme exploits CS information of neighbors to find efficient routes to forward Interest packets toward nearby nodes with corresponding cached content. For that, we carefully design an efficient way for CS information sharing using counting bloom filter. We implement the proposed scheme and compare with state-of-the-art ICN forwarding schemes in IoT. Experimental results indicate that the proposed forwarding scheme achieves a significant improvement in terms of cache hit ratio, energy efficiency, content retrieval latency, and response rate.
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