| Abstrakt: |
Many devices are connected to each other using Internet of Things (IoT) technology today. The capabilities of this technology have highlighted its importance, but significant challenges can affect the quality of these capabilities. One of the most important challenges is routing. A good and appropriate routing for data transfer makes the network service quality very satisfactory and the network life time increases. In this research, using multi-criteria decision making techniques in the fuzzy environment, a method called F-EVM is proposed, which is specifically a combination of the fuzzy eigenvector method and the fuzzy Multi-attribute Ideal-Real Comparative Analysis method. Ad-hoc On-demand Distance Vector protocol is also used for route discovery. The results of the proposed approach have been compared from two viewpoints of network stability and network clustering with ALOC, DECR and MT-MAC approaches. The obtained results show improvement in routing according to criteria such as average energy consumption, packet delivery ratio, and end-to-end delay. For example, the experimental results show the average energy consumption improvements of F-EVM compared to ALOC, DECR and MT-MAC are 30.26%, 18.52% and 58.20%, respectively. [ABSTRACT FROM AUTHOR] |
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