当前位置: X-MOL 学术Int. J. Mach. Learn. & Cyber. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Routing protocol for low power and lossy network–load balancing time-based
International Journal of Machine Learning and Cybernetics ( IF 5.6 ) Pub Date : 2021-01-14 , DOI: 10.1007/s13042-020-01261-w
Muneer Bani Yassien , Shadi A. Aljawarneh , Mohammad Eyadat , Eman Eaydat

Abstract

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.



中文翻译:

低功耗和有损网络的路由协议-基于时间的负载平衡

摘要

最近,6G / IoT出现了面向面向6G / IoT的基础设施的传统无线传感器网络设备的最新技术。6G / IoT的构建利用网络层中的低功耗和有损网络(RPL)协议的路由协议。RPL是具有IPV6距离向量的主动路由协议。大量的已连接智能设备以及大量的公共信息和服务表明,迫切需要一种有效的负载平衡机制来在节点之间分配负载。这项研究的目的是观察一些负载平衡方面的挑战和问题并提出解决方案。本文提出了一种新的机制,称为基于负载平衡时间(LBTB)。提议的LBTB由邻居的节点数和剩余的节点功率组成。拟议的LBTB部署了修订版的modified流计时器算法,以充当目标定向有向无环图(DODAG)的构造函数,并控制节点之间的消息分发。在收到成功率(80%)的情况下,使用Cooja 2.7对不同网络密度(低,中和高)进行的实验仿真。部署了网格和随机网络拓扑。使用LBTB算法对RPL的性能进行了测量,包括收敛时间,数据包传输率(PDR),功耗和延迟。我们将结果与LBSR和标准算法进行了比较。仿真结果表明,平均性能提高如下:收敛时间为68%,功耗为16%,延迟为56%。此外,

更新日期:2021-01-14
down
wechat
bug