Scalable Declarative IT System Update Automation by A* Search with Critical-Element Heuristics

2018 IEEE 7th International Conference on Cloud Networking (CloudNet) Pub Date : 2018-10-01 DOI:10.1109/CloudNet.2018.8549556

Takuya Kuwahara, T. Kuroda, Manabu Nakanoya, Yutaka Yakuwa, H. Shimonishi

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引用次数: 2

Abstract

As IT systems, including network systems using technologies of software defined networking (SDN) and network function virtualisation (NFV), become larger and more complicated, the cost of system management will also increase rapidly. Declarative system update with state space search is a promising approach to enable automation of consistent system update tasks; however, current algorithms is not scalable enough for practical systems. We propose a heuristic algorithm to greatly reduce computation time to solve the system update planning problem for practical systems. Our heuristic algorithm takes into account the structural bottleneck of system update and conducts advance search to resolve bottlenecks of current system states. We evaluated the proposed algorithm for two examples of NFV systems. The results show that computation time to solve system update planning problem for a system with 100 virtual machines does not exceed several minutes, whereas the conventional algorithm is only applicable for a very small system.

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基于关键元素启发式的A*搜索的可扩展声明式IT系统更新自动化

随着IT系统(包括采用软件定义网络(SDN)和网络功能虚拟化(NFV)技术的网络系统)变得越来越庞大和复杂，系统管理成本也将迅速增加。使用状态空间搜索的声明式系统更新是实现一致系统更新任务自动化的一种很有前途的方法;然而，目前的算法在实际系统中没有足够的可扩展性。针对实际系统的更新规划问题，提出了一种启发式算法，大大减少了计算时间。我们的启发式算法考虑了系统更新的结构性瓶颈，通过提前搜索来解决当前系统状态的瓶颈。我们在两个NFV系统的例子中评估了所提出的算法。结果表明，求解100台虚拟机系统的系统更新规划问题的计算时间不超过几分钟，而传统算法仅适用于非常小的系统。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2018 IEEE 7th International Conference on Cloud Networking (CloudNet)

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