面向雾环境的自适应点对点监测

Vera Colombo, Alessandro Tundo, M. Ciavotta, L. Mariani
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引用次数: 8

摘要

监控是雾环境中的一个关键组件:它可以及时提供有关系统行为的见解,揭示违反服务水平协议(sla)的情况,支持服务和平台的自治编排,要求操作人员进行干预,并触发自修复操作。在这样的环境中,监控解决方案必须应对雾中设备和平台的异构性、网络边缘有限的可用资源以及整个云到物连续体的高度动态性。本文通过自适应点对点(P2P)监测解决方案解决了准确有效地监测雾的挑战,该解决方案可以利用基于规则的轻量级专家系统根据收集的数据机会性地调整其行为。实证结果表明,自适应可以提高监测精度,同时以更高的内存消耗为代价减少网络和功耗消耗。•计算机系统组织→自组织自主计算;点对点架构;•信息系统→专家系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Self-Adaptive Peer-to-Peer Monitoring for Fog Environments
Monitoring is a critical component in fog environments: it promptly provides insights about the behavior of systems, reveals Service Level Agreements (SLAs) violations, enables the autonomous orchestration of services and platforms, calls for the intervention of operators, and triggers self-healing actions. In such environments, monitoring solutions have to cope with the heterogeneity of the devices and platforms present in the Fog, the limited resources available at the edge of the network, and the high dynamism of the whole Cloud-to-Thing continuum. This paper addresses the challenge of accurately and efficiently monitoring the Fog with a self-adaptive peer-to-peer (P2P) monitoring solution that can opportunistically adjust its behavior according to the collected data exploiting a lightweight rule-based expert system.Empirical results show that adaptation can improve monitoring accuracy, while reducing network and power consumption at the cost of higher memory consumption. CCS CONCEPTS • Computer systems organization → Self-organizing autonomic computing; Peer-to-peer architectures; • Information systems → Expert systems.
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