在分布式边缘计算网络中使用雾辅助的非重复数据交换
Ghawar Said1,2, Anwar Ghani3,4, Ata Ullah5
1Department of Computer Science, International Islamic University, Islamabad, 44000, Pakistan.
Scientific reports
|September 4, 2024
概括
新的控制切割点识别算法 (CCIA) 改善了物联网 (IoT) 传感器的数据删复. 通过提高物联网系统中的数据传输和存储效率,CCIA优化了资源使用.
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:
- 物联网 (IoT) 系统产生大量的传感器数据,这给资源稀缺的设备带来了挑战.
- 物联网中的数据处理效率低下导致通信和存储成本增加,原因是来自重叠的传感器区域的冗余传输.
- 现有的数据去复制方案,如非对称极端 (AE) 和快速非对称最大 (RAM),在最佳窗口大小选择方面存在困难,导致缺少去复制率.
研究的目的:
- 在资源有限的物联网环境中解决现有数据脱复制技术的局限性.
- 提出一种新的算法,即控制切点识别算法 (CCIA),用于高效的数据分割和复制.
- 为了提高数据收集,传输和存储在物联网支持的医疗保健服务和其他应用程序的效率.
主要方法:
- 开发了可控切割点识别算法 (CCIA),该算法具有限制的可变大小窗口到定义的值.
- 确保值确定指数值大于固定窗口大小的一半,以最大限度地检测重复.
- 实施上限偏移以防止过大的窗口和减轻计算开销.
- 使用在Azure云平台上部署的Windows通信基金会服务进行了广泛的模拟.
主要成果:
- 与AE和RAM相比,CCIA在多个指标上表现优越,包括块数,平均块大小和最小块大小.
- 在总块数 (比竞争对手优于6.81%和14.17%) 和平均块数 (比竞争对手优于4.39%和18.45%) 中,CCIA取得了显著的改进.
- 该算法在最小块大小 (153%和190%的改进) 中显示出显著的收益,表明更有效的数据压缩和复制.
结论:
- 控制切点识别算法 (CCIA) 有效地优化了物联网系统中的数据传输和存储.
- CCIA为物联网应用提供了更好的资源利用和更低的运营成本,特别是在像医疗保健这样的数据密集型领域.
- 拟议的算法代表了对资源有限的物联网环境有效数据管理的重大进步.
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