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Original scientific paper

https://doi.org/10.17559/TV-20220829132003

Novel Geodetic Fuzzy Subgraph-Based Ranking for Congestion Control in RPL-IoT Network

Mohamed Sithik M, ; Department of Computer Science and Engineering, Mohamed Sathak Engineering College, Sathak Nagar, SH 49, Keelakarai, Tamil Nadu, 623806, India *
Muthu Kumar B ; Department of Computer Science and Engineering, School of Computing and Information Technology, REVA University, Kattigenahalli, SH 104, Srinivasa Nagar, Bengaluru, Karnataka, 560064, India

* Corresponding author.


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Abstract

Congestion control is among the most challenging tasks in enhancing QoS in the Internet of Things (IoT). Currently, wireless networks are able to have a large number of connections but with a limited amount of network resources. Consequently, congestion occurs, which adversely affects throughput, transmission delay, packet losses, power consumption management, and the lifespan of a network. This is certainly relevant in networks where transmissions are controlled by the Routing Protocol for Low-Power and Lossy Networks (RPL), which is commonly employed in the Internet of Things network. To solve this problem, a novel Geodetic fuzzy subgraph-based ranking (GFSR-RPL) for congestion control is proposed. Initially, the proposed GFSR-RPL selects the cluster head using K-means clustering. Then the rank calculation can be done via the final route setting for data transmission. A route setup scheme consists of three elements: 1) a Round Trip Time (RTT) estimator that assesses congestion conditions in a variety of ways; 2) a trend and relative strength indicator analysis; and 3) a geodetic fuzzy subgraph rank calculation method that calculates initial RTO (initial retransmission timeouts) accurately. The proposed GFSR-RPL method reduces the energy consumption of up to 43.58%, 25.8%, 14.82% and 6.85% than existing methods such as RPR, CBR-RPL, ACW and ECLRPL.

Keywords

clustering; geodetic fuzzy subgraph; internet of things; routing protocol for low-power and lossy networks; routing

Hrčak ID:

316381

URI

https://hrcak.srce.hr/316381

Publication date:

23.4.2024.

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