A distributed monitoring system and method based on streaming media service cluster

Abstract

The present invention provides a distributed monitoring system and method based on a streaming media service cluster, wherein the system includes: a Hadoop-based data distributed processing architecture, extracting data from a data source and analyzing it, and pre-processing the analyzed data Processing and distributed computing; Memcached, a distributed memory cache module, caches common and temporary data in the server memory; relational data management module, realizes information query, storage, management, and calculation of access devices on the monitoring system platform; non-relational Data management module, combined with non-relational No-SQL data storage system fragmentation computing method to achieve distributed deployment; streaming media service cluster module, to achieve distributed cluster processing of streaming media information transmission; load balancing module, monitoring system platform The load is balanced and the WEB container is expanded horizontally. The invention combines the load balancing mechanism and the database fragmentation calculation, improves the horizontal expansion capability, reduces the platform configuration and management workload, and maintains stability.

Description

technical field [0001] The invention relates to the field of distributed computing technology, in particular to a streaming media service cluster based on a real-time monitoring platform for mobile terminals using distributed memory cache, distributed non-relational No-SQL database combined with streaming media clustering and TCP long connection communication technology Distributed monitoring system and method. Background technique [0002] In the system application based on TCP / IP network communication to monitor the mobile terminal, the data transmission between the mobile terminal and the monitoring platform requires high real-time performance, and there are a large number of computing tasks such as data exchange, data query, and data storage. At the same time, when the number of client connections increases, the scale of monitoring becomes larger and the business involved becomes more and more complex, which will easily cause network congestion and a sharp decline in sys...

AI Technical Summary

Problems solved by technology

[0004] First, the response speed and concurrency capability of the TCP communication platform are low;

[0005] Second, the horizontal expansion capability of the TCP communication platform is low, the configuration and management workload of the platform is heavy, and the stability is not high;

[0006] Third, there is no fault tolerance mechanism for system failures, and the impact of failure points is large;

[0007] Fourth, the resources of network distributed computing cannot be fully utilized, the load of the system is uneven, and the stability of the system cannot be guaranteed

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