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消息队列（MQ）的通用场景

一对多、多对多异步解耦

基于发布订阅模型，分布式应用异步解耦，可以增加应用的水平扩展性，增加前端应用快速客户反应能力。

削峰场景

大促等流量洪流突然来袭时，MQ可以缓冲突发流量，避免整个系统崩溃。

日志监控

做为重要日志的监控通信管道，将应用日志监控对系统性能影响降到最低。

消息队列（MQ）的性能报告

消息队列秉持开放、共享的原则拥抱开源生态，无技术绑定，2016年阿里巴巴正式宣布将 MQ 内核引擎 RocketMQ 捐赠给 Apache 软件基金会；与此同时，全面融合 kafka 生态，做到无缝迁移，打造更安全、更可靠、更易运维的 kafka 企业级消息服务。此次我们总结了几款业界主流消息中间件产品的对比报告：

MQ 推出微消息队列 LMQ

连接端（如移动设备、智能家电、汽车、机器人等）和云，实现双向通信，可支撑亿级设备连接与百万消息并发

一般来说车联网系统是一个端到云的多层体系，其数据流主要分为2类： 1. 数据上行采集：安装在车辆等执行部件上的传感器采集状态数据后，定期上传到服务端进行分析和应用。其特点是，车辆和传感器种类众多，基数大，移动数据网络大多走4G，不如固定网络稳定; 2. 指令下行推送：远程服务端根据设定，下行推送控制指令数据，控制指定的客户端进行某些行为。