Designing a context-aware model for RPL load balancing of low power and lossy networks in the internet of things

Royaee Zohreh; Mirvaziri Hamid; Khatibi Bardsiri Amid

摘要

The IPv6 routing protocol (RPL) for low power and lossy Networks (LLNs) was accepted as the standard routing protocol for the IoT by IETF in March 2012. Since then, it has been used for different IoT applications. Although the RPL deals considerably with IoT network requirements, there are still some open-ended problems to solve, for it was not initially designed for IoT applications. This paper addresses the RPL problems including load imbalance, which causes congestion in some nodes, significantly reduces the network performance, and decreases node energy and network lifetime. This paper proposes the automata-ant colony based multiple recursive RPL (AMRRPL), which is a modified version of the RPL for IoT networks, and uses a balancing model to avoid congestion. As a result, it will reduce network energy consumption, prolong the network lifetime, and reduce packet loss. The AMRRPL is evaluated in three steps. First, a multi-hop return objective function is presented based on the ant colony and computes the rank according to node context. The second step develops a new parent selection mechanism dynamically selected by stochastic automata and dynamic metrics for an optimal parent. General evaluation results show that this algorithm can make better decisions with regard to the optimal parent instead of making decisions simply based on the parent's rank. The third step resolve bottlenecks and swarm problems by managing the moving nodes through the heuristic flabellum algorithm inspired by physical and biological behaviour of flabella in the sea. Finally, the proposed algorithm performance is evaluated through the Cooja simulator. The proposed algorithm shows significant improvements in packet delivery and network lifetime, energy and convergence.

机译：2012年3月IETF的低功耗和有损网络（LLNS）的IPv6路由协议（RPL）被接受为IET的标准路由协议。从那时起，它已被用于不同的IOT应用程序。虽然RPL对物联网需求的大大涉及，但仍有一些开放式问题来解决，因为它没有最初为IOT应用程序设计。本文解决了包括负载不平衡的RPL问题，这导致某些节点中的拥塞，显着降低了网络性能，降低了节点能量和网络寿命。本文提出了基于自动数据库亚群的多递归RPL（AMRRRPL），其是IOT网络的RPL的修改版本，并使用平衡模型来避免拥塞。结果，它将降低网络能耗，延长网络寿命，减少丢包。 AMRRPL在三个步骤中进行评估。首先，基于蚁群呈现多跳回物目标函数，并根据节点上下文计算等级。第二步开发出通过随机自动机和最佳父级的动态度量动态选择的新父选择机制。一般评价结果表明，该算法可以在最佳父母方面做出更好的决策，而不是简单地根据父级排名做出决策。第三步通过通过在海中的物理和生物行为启发的启发式脆弱算法来解决移动节点来解决瓶颈和群问题。最后，通过Cooja模拟器评估所提出的算法性能。该算法显示分组传递和网络寿命，能量和收敛性的显着改进。

Designing a context-aware model for RPL load balancing of low power and lossy networks in the internet of things

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