Title of article
Improving the Performance of RPL Routing Protocol for Internet of Things
Author/Authors
Aslani, Zahra Faculty of Computer and Information Technology Engineering - Qazvin Branch Islamic Azad University, Qazvin Department of Computer Engineering and IT - Parand Branch Islamic Azad University, Parand, Iran , Sargolzaey, Hadi Faculty of Computer and Information Technology Engineering - Qazvin Branch Islamic Azad University, Qazvin Department of Computer Engineering and IT - Parand Branch Islamic Azad University, Parand, Iran
Pages
7
From page
69
To page
75
Abstract
The emerging Internet of Things (IoT) connects the physical world to the digital one and composes large networks of smart devices to support various applications. In order to provide a suitable communication in such networks, a reliable routing protocol is needed. In this paper, a modified version of an IPv6 Routing Protocol for Low-Power and Lossy networks (RPL), which has been standardized by IETF is proposed. It is used in Low power and Lossy Networks (LLNs) that consist of lossy links and electronic devices use a set of novel Internet of Things technologies. RPL protocol is based on the constructional concept of Directed Acyclic Graphs (DAGs) that is constructed using a scalar value called rank. The default metric which is commonly used in low power and lossy networks to compute rank of Expected Transmission Count (ETX) based on the number of re-transmission. While the results represent that this method of calculation is not effective enough. Therefore, we introduce a new method of ETX computation which is used to construct the DAGs with better rank computation and selected routes. The simulation results show that our proposed idea has better performance in contrast with the basic RPL and AODV protocols in terms of Packet Delivery Ratio (PDR), number of re-transmission, end to end delay, and throughput.
Keywords
Internet of Thing (IoT) , RPL , Routing Protocol , Low Power and Lossy Networks (LLNs) , Link Reliability Metric
Serial Year
2017
Record number
2494706
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