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一个优化的物联网支持的大数据分析架构,用于边缘云计算
Muhammad Babar1, Mian Ahmad Jan2, Xiangjian He3
1Department of Computer Science, Allama Iqbal Open University (AIOU), Islamabad, Pakistan.
概括
边缘计算通过引入边缘智能模块来提高物联网 (IoT) 数据分析,以实现高效的处理和存储. 这种优化的架构解决了物联网环境中的大数据挑战.
科学领域:
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
- 网络工程 网络工程
背景情况:
- 边缘计算对于物联网 (IoT) 非常重要,因为它具有可扩展性和延迟需求.
- 现有的物联网大数据分析框架与大规模,异质的数据,存储,处理和通信开销作斗争.
- 目前的解决方案缺乏有效的并行数据加载和强大的通信处理机制.
研究的目的:
- 提出一个优化的物联网支持的大数据分析架构,用于边缘云计算,使用机器学习.
- 引入一个边缘智能模块,用于高效的边缘数据处理和存储,与云技术集成.
- 解决物联网大数据分析中数据量,异质性和处理时间的挑战.
主要方法:
- 一个优化的两层架构:物联网边缘和云处理.
- 实施边缘智能模块,以在网络边缘有效处理数据.
- 使用优化的MapReduce并行算法进行数据注入和存储.
- 员工优化了另一个资源谈判员 (YARN),以实现高效的集群管理.
- 实验模拟了使用Apache Spark与真实数据集的拟议设计.
主要成果:
- 拟议的架构证明了大数据在网络边缘的高效处理和存储.
- 优化的MapReduce和YARN有助于有效的数据处理和集群管理.
- 实验模拟验证了拟议的边缘云架构的效率.
- 对比分析显示,与现有提案和传统机制相比,其表现优越.
结论:
- 拟议的优化物联网支持的大数据分析架构有效地解决了边缘云计算的挑战.
- 边缘智能和云技术的整合增强了物联网应用程序的大数据分析.
- 该架构为处理大规模和异质物联网数据提供了一个高效,可扩展和强大的解决方案.
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