Survivable Deployments of Optical Sensor Networks against Multiple Failures and Disasters: A Survey

Author:

Zhang Yongjun,Xin Jingjie

Abstract

Optical sensing that integrates communication and sensing functions is playing a more and more important role in both military and civil applications. Incorporating optical sensing and optical communication, optical sensor networks (OSNs) that undertake the task of high-speed and large-capacity applications and sensing data transmissions have become an important communication infrastructure. However, multiple failures and disasters in OSNs can cause serious sensing provisioning problems. To ensure uninterrupted sensing data transmission, survivability has always been an important research emphasis. This paper focuses on the survivable deployment of OSNs against multiple failures and disasters. We first review and evaluate the existing survivability technologies developed for or applied to OSNs, such as fiber bus protection, self-healing architecture, and 1 + 1 protection. We then elaborate on the disaster-resilient survivability requirement of OSNs. Moreover, we propose a new k-node (edge) sensing connectivity concept, which ensures the connectivity between sensing data and users. Based on k-node (edge) sensing connectivity, the disaster-resilient survivability technologies are developed. The key technologies necessary to implement k-node (edge) sensing connectivity are also elaborated. Recently, artificial intelligence (AI) has developed rapidly. It can be used to improve the survivability of OSNs. This paper details potential development directions of survivability technologies of optical sensing in OSNs employing AI.

Funder

National Natural Science Foundation of China

National Science Foundation for Outstanding Youth Scholars of China

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3