Simulating Distributed Wireless Sensor Networks for Edge-AI

Ambar Prajapati, Bonny Banerjee
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引用次数: 2

Abstract

This paper presents the simulation of distributed wireless sensor networks (WSNs) consisting of autonomous mobile nodes that communicate, with or without a central/root node, as desired for edge artificial intelligence (edge-AI). We harness the high-resolution and multidimensional sensing characteristics of IEEE 802.15.4 standard and Routing Protocol for Low-Power and Lossy Networks (RPL) to implement dynamic, asynchronous, event-driven, targeted communication in distributed WSNs. We choose Contiki-NG/Cooja to simulate two WSNs, one with and the other without a root node. The simulations are assessed on the network Quality of Service (QoS) parameters such as throughput, network lifetime, power consumption, and packet delivery ratio. The simulation outputs show that the sensor nodes at the edge communicate successfully with the specific targets responding to particular events in an autonomous and asynchronous manner. The performance is slightly degraded when using the RPL WSN with a root node. This work shows how to simulate and evaluate distributed WSNs using the Cooja simulator which would be useful for designing such networks for edge-AI applications, such as visual surveillance, monitoring in assisted living facilities, intelligent transportation with connected vehicles, automated factory floors, immersive social media experience, and so on.
基于Edge-AI的分布式无线传感器网络仿真
本文介绍了分布式无线传感器网络(wsn)的仿真,该网络由自主移动节点组成,这些节点可以根据边缘人工智能(edge- ai)的需要进行通信,无论有无中心/根节点。我们利用IEEE 802.15.4标准和低功耗和有损网络路由协议(RPL)的高分辨率和多维感知特性,在分布式wsn中实现动态、异步、事件驱动、目标通信。我们选择Contiki-NG/Cooja来模拟两个wsn,一个有根节点,另一个没有根节点。仿真评估了网络服务质量(QoS)参数,如吞吐量、网络生存期、功耗和数据包传送率。仿真结果表明,边缘传感器节点以自主和异步的方式与响应特定事件的特定目标成功通信。当使用带有根节点的RPL WSN时,性能略有下降。这项工作展示了如何使用Cooja模拟器模拟和评估分布式wsn,这将有助于为边缘人工智能应用设计此类网络,如视觉监控、辅助生活设施监控、联网车辆的智能交通、自动化工厂车间、沉浸式社交媒体体验等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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