A Dynamic Wireless Sensor Network Deployment Algorithm for Emergency Communications

Kubra Gundogan, Nuri Alperen Kose, Khushi Gupta, Damilola Oladimeji, Fan Liang
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Abstract

The Internet of Things (IoT) connects a huge number of IoT devices, including sensors, actuators, computing nodes, etc. Those IoT devices communicate with each other by using different communication techniques. Generally, LTE, 5G, and WiFi are involved in IoT to support communication. However, it needs considerable communication infrastructures to support wireless communication. An obvious issue is how to create a communication network in some regions that have less communication support. Wireless Sensor Network (WSN) is a kind of wireless ad hoc network, which organizes a huge number of wireless sensors to create a self-organized wireless network. Therefore, the WSN is a potential approach to providing communication in those regions. Since WSN is highly dynamic, how to create the wireless network to provide optimal coverage rate is still open. In this article, we propose a dynamic wireless sensor deployment scenarios that provide optimal coverage rate in a certain region. Our model proposes a coverage rate based on possible disaster scenarios for communication between Base Stations and UAVs. We optimize the Particle Swarm Optimization (PSO) algorithm and find the maximum coverage rate.
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面向应急通信的动态无线传感器网络部署算法
物联网(IoT)连接了大量的物联网设备,包括传感器、执行器、计算节点等。这些物联网设备通过使用不同的通信技术相互通信。通常,物联网涉及LTE、5G和WiFi来支持通信。然而,它需要大量的通信基础设施来支持无线通信。一个明显的问题是如何在一些通信支持较少的地区建立通信网络。无线传感器网络(WSN)是一种无线自组织网络,它将大量的无线传感器组织成一个自组织的无线网络。因此,无线传感器网络是在这些区域提供通信的潜在方法。由于无线传感器网络是高度动态的,如何创建无线网络以提供最佳的覆盖率仍然是一个开放的问题。在这篇文章中,我们提出了一个动态的无线传感器部署方案,在一定的区域提供最佳的覆盖率。我们的模型提出了一个基于基站和无人机之间通信可能发生的灾难场景的覆盖率。对粒子群算法(PSO)进行优化,求出最大覆盖率。
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