A fine-grained rule partition algorithm in cloud data centers

A fine-grained rule partition algorithm in cloud data centers
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云数据中心细粒度规则划分算法

DOI:
10.1016/j.jnca.2018.03.025
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发表时间:
2018-07
影响因子:
8.7
通讯作者:
Wang Jianxin
Wang Jianxin
中科院分区:
计算机科学2区
文献类型:
--
作者:
Jiang Wei;Jiang Wanchun;Wang Weiping;Wang Haodong;Pan Yi;Wang Jianxin

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为了更好地控制云中的单个数据流,流量管理策略需要增加细粒度的规则,从而导致规则的急剧增加。在大规模数据中心中使用这些策略时,服务器上有限的CPU或内存资源成为瓶颈。为了克服这些资源限制,规则划分算法是必不可少的,分解的规则集,使一些规则可以迁移。本文表明,目前的规则划分算法的vCRIB可能会导致高流量开销和高规则膨胀在某些情况下。基于这一观察,我们提出了一个细粒度的规则划分(FRP)算法。与vCRIB以同一源地址内的规则为单位划分规则集不同,FRP将单个规则视为一个单元,从而通过保留更多的拒绝规则来减少流量开销。此外,FRP还通过优化重定向规则的数量来控制规则膨胀。仿真结果证实了FRP优于vCRIB,特别是当资源严重受限时。
To better control the individual data flow in the cloud, traffic management policies are in need of increasing fine-grained rules, causing a dramatic increase in rules. The limited CPU or memory resources at the servers become the bottleneck when those policies are employed in large-scale data centers. To overcome these resource constraints, the rule partition algorithm is indispensable to decompose the rule set so that some rules can be migrated away. This paper shows that the current rule partition algorithm of vCRIB may lead to a high traffic overhead and high rule inflation in certain cases. Motivated by this observation, we propose a Fine-grained Rule Partition (FRP) algorithm. Different from vCRIB which divides the rule set based on the unit of rules within the same source address, FRP treats the individual rule as a unit, and thus reduce the traffic overhead by retaining more deny rules. In addition, FRP controls the rule inflation by optimizing the number of redirection rules as well. The simulation results confirm that FRP outperforms vCRIB, especially when the resources are severely constrained.
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