A Game Theoretic Optimization of RPL for Mobile Internet of Things Applications
A Game Theoretic Optimization of RPL for Mobile Internet of Things Applications
复制标题
移动物联网应用 RPL 的博弈论优化
作者：
Harith Kharrufa;Hayder A. A. Al;A. Kemp
任何无线网络中移动节点的存在都会影响网络的性能，导致更高的数据包丢失和能耗增加。然而，许多最近的应用需要移动性的支持，并且处理移动节点的有效方法至关重要。本文提出了一个博弈场景，节点以自私的方式竞争网络资源，将数据包发送到汇聚节点。每个节点都算作非合作博弈中的一个玩家。游戏的最佳解决方案是使用独特的纳什均衡（NE）找到的，其中当其他玩家使用当前策略时，节点无法改善其支付函数。所提出的解决方案旨在提出一种控制移动节点（或移动环境中的静态节点）的不同参数（包括传输速率、定时器和操作模式）的策略，以优化移动条件下低功耗有损网络（RPL）路由协议在数据包传送率、吞吐量、能耗和端到端延迟方面的性能。所提出的解决方案基于接收到的信号强度指示读数来监视节点的移动性，并且它还考虑不同节点的优先级和当前的噪声水平，以便选择优选的传输速率。一种称为基于博弈论的移动 RPL (GTM-RPL) 的优化协议在具有不同物联网应用网络要求的多个场景中实施和测试。仿真结果表明，在存在移动性的情况下，GTM-RPL 提供了一种灵活且适应性强的解决方案，可以提高吞吐量，同时保持较低的能耗，与相关工作相比，能耗提高了 10% 以上。对于吞吐量要求较高的应用，GTM-RPL显示出显着的优势，吞吐量提高16%以上，能耗提高20%以上。
The presence of mobile nodes in any wireless network can affect the performance of the network, leading to higher packet loss and increased energy consumption. However, many recent applications require the support of mobility and an efficient approach to handle mobile nodes is essential. In this paper, a game scenario is formulated, where nodes compete for network resources in a selfish manner, to send their data packets to the sink node. Each node counts as a player in the non-cooperative game. The optimal solution for the game is found using the unique Nash equilibrium (NE), where a node cannot improve its pay-off function while other players use their current strategy. The proposed solution aims to present a strategy to control different parameters of mobile nodes (or static nodes in a mobile environment) including transmission rate, timers, and operation mode, in order to optimize the performance of routing protocol for low-power and lossy networks (RPL) under mobility in terms of packet delivery ratio, throughput, energy consumption, and end-to-end-delay. The proposed solution monitors the mobility of nodes based on received signal strength indication readings, and it also takes into account the priorities of different nodes and the current level of noise in order to select the preferred transmission rate. An optimized protocol called game-theory based mobile RPL (GTM-RPL) is implemented and tested in multiple scenarios with different network requirements for Internet of Things applications. Simulation results show that in the presence of mobility, GTM-RPL provides a flexible and an adaptable solution that improves throughput whilst maintaining lower energy consumption showing more than 10% improvement compared to related work. For applications with high throughput requirements, GTM-RPL shows a significant advantage with more than 16% improvement in throughput and 20% improvement in energy consumption.