Research Area:  Internet of Things

Abstract:

Internet of Things (IoT) has seen a lot of traction over the last few years and is expected to play a major role in controlling devices and communication. IoT network involves sensors with constrained memory, limited processing and power capabilities. The process of network formation largely decides the Quality of service in these networks. IPv6 Routing Protocol for LLNs (RPL) is specially designed by the IETF ROLL working group to cater to routing requirements in such networks. In RPL, an Objective function specifies a set of metrics or constraints which can be used as criteria for best parent and path selection, ensuring a faster route to the destination. In our work, we propose a novel objective function OF-FZ, which uses four metrics to make routing decisions. Fuzzy Logic is used to combine the metrics hop count (HC), ETX, delay and node residual energy (RE) to obtain a single decision metric termed as Quality Assurance (QA) score. During routing, a neighbor node having the highest QA score is chosen as the best parent. The proposed Objective Function leads to significant savings in energy consumption (EC) (9% lower), Packet Delivery Ratio (PDR) (3% higher), End-to-end Delay (8% lower) as compared to existing OFs. Controlling advertisement messages circulating in the network leads to a significant reduction in control overhead to the tune of 45%. Performance evaluation and deep dive of OF-FZ is done in three configurations: network scalability, increasing packet transmission rates and multi-sink scenarios using Contiki OS and COOJA network simulator.

Keywords:  

Author(s) Name:  Sonia Kuwelkar,Hassanali Gulamali Virani

Publisher name:  Taylor and Francis

DOI:  10.1080/03772063.2021.1990139

Volume Information:  Volume 67, Issue 5, 2021 pages 585-734

Paper Link:   https://www.tandfonline.com/doi/abs/10.1080/03772063.2021.1990139?scroll=top&needAccess=true&journalCode=tijr20