Network efficient topology for low power and lossy networks in smart corridor design using RPL

Abstract

Purpose This paper aims to determine the network efficient topology for low power and lossy networks (LLNs) using routing protocol for LLN (RPL) with respect to the increase in network size and propose a novel approach to overcome the shortcomings of the existing models. Design/methodology/approach The authors have used Contiki OS/Cooja simulator to conduct experiments on primarily four topologies (star, bus/linear, ring/eclipse and random). They have implemented RPL protocol using Sky motes for each topology from 10, 20, 30 and up to 70 nodes. Consequently, after 24 h of experimentation, the readings have been noted and, alongside, a comprehensive comparative analysis has been performed based on the network density and metric parameters: packet delivery ratio (PDR), expected transmission (ETX) and power consumption. Further, a hybrid model is proposed where the additional factors of mobility, multiple sink and a combination of static and mobile nodes are introduced. The proposed model is then compared with the star model (all static nodes and star topology) and the dynamic model (all mobile nodes) to analyze the efficiency and network performance for different network sizes (28, 36, 38 and 44 nodes). The mobility is introduced using BonnMotion tool in Contiki OS. Findings Simulation results have shown that the star topology is most network efficient when compared with bus/linear, ring/eclipse and random topologies for low density and high scalable network. But when the same setup is compared with the proposed hybrid model, the proposed model shows a significant improvement and gives the best and efficient network performance with highest PDR (average improvement approximately 44.5%) and lowest ETX (average improvement approximately 49.5%) comparatively. Practical implications Also, these findings will benefit the deployment of smart devices used in advanced metering infrastructure, road side units and in various industrial applications such as traffic monitoring system, electronic toll collection and traffic analysis in the smart grid infrastructure. Originality/value The impact of topology is significant and detailed analysis is required to understand the impact of different topologies of the nodes in the network for the present and the future scenarios. As very few research studies have discussed this gap, this research paper is quintessential and shall open novel future potential direction. Also, the proposed approach of hybrid model with mobility has not been considered in the literature yet.

Optimal Feature Selection to Improve Vehicular Network Lifetime

“…Therefore, it is necessary to optimize LLN issues concerning IoV. Since several studies [3][4] [5] are available in the literature that has targeted LLNbased IoT network and only a few works [6] [7] can be located that have explored IoV for LLNs, it still remains contemporary distress.…”

Clustering Based Optimal Cluster Head Selection Using Bio-Inspired Neural Network in Energy Optimization of 6LowPAN

“…The devices added to IoT are growing in leaps and bounds every day. Homes, classrooms and cities are becoming smart with IoT [2,3].…”