Sensors and Materials
ISSN 0914-4935

Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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Load-balanced Resource Directory Architecture for Large-scale Internet of Things Local Networks

Sol-Bee Lee, Jung-Hyok Kwon, Jaehoon Park, and Eui-Jik Kim

(Received March 30, 2017; Accepted April 12, 2018)

Keywords: CoAP, Internet of things, IoT local network, resource directory, scalability

This paper presents a load-balanced resource directory (LB-RD) architecture based on the constrained application protocol (CoAP), and is aimed at addressing the scalability issue with the centralized resource discovery approach in large-scale Internet of Things (IoT) local networks. To balance the traffic load due to a large number of messages concentrated on the resource directory (RD), the LB-RD serves as an intermediary agent between the servers and the RD. Its architecture includes the following three essential functional blocks: server group management (SGM), message aggregation (MA), and message forwarding scheduling (MFS). The SGM manages the uniform resource identifier (URI) list for a group of servers associated with the LB-RD. The MA aggregates the registration/update messages received from the servers into a single aggregated message. Finally, the MFS determines the forwarding time for the LB-RD to send its aggregated message to the RD. To verify the effectiveness of the LB-RD architecture, an experimental simulation is conducted under various scenarios. The results show that the LB-RD architecture achieves better performance than the existing RD approach in terms of the number of lost messages and the message loss rate.

Corresponding author: Eui-Jik Kim




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