Routing protocol for low power and lossy network–load balancing time-based

• Published in: International journal of machine learning and cybernetics 2021-11, Vol.12 (11), p.3101-3114
• Main Authors: Yassien, Muneer Bani, Aljawarneh, Shadi A., Eyadat, Mohammad, Eaydat, Eman
• Format: Article
• Language: English
• Subjects: Algorithms; Artificial Intelligence; Communication; Complex Systems; Computational Intelligence; Control; Convergence; Engineering; Internet of Things; Literature reviews; Load; Load balancing; Mechatronics; Network topologies; Nodes; Original Article; Pattern Recognition; Power consumption; Power management; Robotics; Routing (telecommunications); Sensors; Systems Biology; Wireless sensor networks
• ISSN: 1868-8071; 1868-808X
• DOI: 10.1007/s13042-020-01261-w

Recently 6G/IoT emerged the latest technology of traditional wireless sensor network devices for 6G/IoT-oriented infrastructure. The construction of 6G/IoT utilizes the routing protocol for low power and lossy networks (RPL) protocol in the network layer. RPL is a proactive routing protocol with an IPV6 distance vector. The enormous number of connected smart devices and a huge amount of common information and services have shown the important need for an effective load balancing mechanism to distribute the load between nodes. The motivation of this research is to observe some of the load balancing challenges and problems and propose a solution. This paper proposes a new mechanism called Load Balancing Time Based (LBTB). The proposed LBTB is composed of the node count of neighbors and the remaining node power. The proposed LBTB deployed a modified edition of trickle timer algorithm to act as the constructor of the Destination Oriented Directed Acyclic Graph (DODAG) and controls the messages distribution between nodes. The simulation of the experiments performed using Cooja 2.7 on different network densities (low, medium, and high) under reception of success ratios (80%). Grid and random network topologies were deployed. The performance of RPL using the LBTB algorithm was measured using metrics including convergence time, the packet delivery ratio (PDR), power consumption, and delay. We compared the results with the LBSR and the standard algorithms. The results of the simulation showed that the average enhancement of the performance as follows: 68% convergence time, 16% power consumption, and 56% delay. In addition, the results showed that the PDR in some cases were better using the LBTB algorithm.