Design for Improving the Architectural Capabilities of Complex Network Intensive and Scalable Early Warning Release System

In order to solve the problems of high coupling and poor scalability of the traditional monomer early warning release system architecture, multi-level deployment in a complex network environment will lead to high investment in software and hardware and cannot achieve intensive multi-level deployment. This paper realizes the goal of system scalability by introducing micro service architecture and technology stack and realizes the goal of resource intensification by introducing the idea of a data forwarding agent. The designed architecture scheme has been practically applied in the “Jiangxi emergency early warning information release system software platform (phase I) project” (hereinafter referred to as “provincial emergency”), which meets the needs of flexible deployment of multi-level applications across meteorological wide area network (Wan), business private network of other commissions, offices, and bureaus, government extranet, Internet and other complex networks, and fully verifies the scientificity and rationality of the scheme. It has achieved the goal of intensive and scalable construction of provincial emergencies under the complex network environment, greatly improved the early warning capacity and communication capacity of emergencies and comprehensive disasters, provided a reliable guarantee for disaster prevention and reduction, and provided a reference for the construction of current and future early warning release system and capacity improvement project.

Authors

Institutions

Publication Details

Journal
Journal of Electronic Research and Application
Published
2025-02-13
DOI
https://doi.org/10.26689/jera.v9i1.9452
Citations
1
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
1.49
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design for Improving the Architectural Capabilities of Complex Network Intensive and Scalable Early Warning Release System

Yao Wang, Rui Ma, Guan Peng
1 citations
Journal of Electronic Research and Application
Network Security and Intrusion Detection
1.49
article

Design for Improving the Architectural Capabilities of Complex Network Intensive and Scalable Early Warning Release System

Yao Wang, Rui Ma, Guan Peng
article en
1 citations

Abstract

In order to solve the problems of high coupling and poor scalability of the traditional monomer early warning release system architecture, multi-level deployment in a complex network environment will lead to high investment in software and hardware and cannot achieve intensive multi-level deployment. This paper realizes the goal of system scalability by introducing micro service architecture and technology stack and realizes the goal of resource intensification by introducing the idea of a data forwarding agent. The designed architecture scheme has been practically applied in the “Jiangxi emergency early warning information release system software platform (phase I) project” (hereinafter referred to as “provincial emergency”), which meets the needs of flexible deployment of multi-level applications across meteorological wide area network (Wan), business private network of other commissions, offices, and bureaus, government extranet, Internet and other complex networks, and fully verifies the scientificity and rationality of the scheme. It has achieved the goal of intensive and scalable construction of provincial emergencies under the complex network environment, greatly improved the early warning capacity and communication capacity of emergencies and comprehensive disasters, provided a reliable guarantee for disaster prevention and reduction, and provided a reference for the construction of current and future early warning release system and capacity improvement project.

Journal of Electronic Research and ApplicationVol. 9(1)
Beijing Founder Electronics (China) (CN), Beijing International Studies University (CN)
Openalex Percentile: Top 20%
Network Security and Intrusion Detection
1.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Design for Improving the Architectural Capabilities of Complex Network Intensive and Scalable Early Warning Release System — Yao Wang, Rui Ma, et al. · Journal of Electronic Research and Application (2025) | TGRS Research Map | TGRS