Big-Data Platform for Performance Monitoring of Telecom-Service-Provider Networks

Author:

Simakovic MilanORCID,Cica ZoranORCID,Drajic DejanORCID

Abstract

Large telecom-service-provider networks are typically based on complex communications infrastructures comprising millions of network devices. The performance monitoring of such networks is a very demanding and challenging task. A large amount of data is collected and processed during performance monitoring to obtain information that gives insights into the current network performance. Using the obtained information, providers can efficiently detect, locate, and troubleshoot weak spots in the network and improve the overall network performance. Furthermore, the extracted information can be used for planning future network expansions and to support the determination of business-strategy decisions. However, traditional methods for processing and storing data are not applicable because of the enormous amount of collected data. Thus, big-data technologies must be used. In this paper, a big-data platform for the performance monitoring of telecom-service-provider networks is proposed. The proposed platform is capable of collecting, storing, and processing data from millions of devices. Typical challenges and problems in the development and deployment process of the platform, as well as the solutions to overcome them, are presented. The proposed platform is adjusted to HFC (Hybrid Fiber-Coaxial) network and currently operates in the real HFC network, comprising millions of users and devices.

Funder

Ministry of Education, Science and Technological Development of the Republic of Serbia

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Cited by 2 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