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Grouping Service Chains of Multiple Flows in NFV-Based Networks

机译:基于NFV的网络中多个流的分组服务链

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摘要

In Software Defined Networks (SDNs), flows usually request to be processed by a service chain (an ordered set of virtualized network services). SDN-enabled networks manage the routing and processing of flows by a large number of associated finer-granularity rules. These rules are maintained by switches in their local hardware such as Ternary Content Addressable Memories (TCAMs), which support high-speed parallel lookup on wildcard patterns. However, the capacity of hardware switches is limited to thousands because of their high requirements for cost and power. In order to avoid much slower matching by using software switches or even packet loss, we can group flows so that all matching rules can be placed in hardware switches. In such a grouping, all flows in each group match only one rule and will be forwarded to the same routing path, instead of each flow matching one rule. This will result in a longer delay because of processing by the longer newly-grouped service chain. In this paper, we efficiently group flows to minimize the total cost while satisfying the capacity constraint of the forwarding tables in hardware switches. We first prove the submodularity of our objective function and propose a corresponding performance-guaranteed solution. Additionally, we design an efficient heuristic solution based on the classic k-means algorithm. Furthermore, we include discussions on dynamic network situations (insertion, deletion, and update of flows) and an alternative objective. We also conduct real experiments on our testbed to indicate the practicality of our motivation. Extensive simulations are conducted to evaluate the performance of our proposed algorithms.
机译:在软件定义的网络(SDNS)中,流程通常请求由服务链(有序的虚拟化网络服务集)处理。支持SDN的网络通过大量相关的更精细的粒度规则管理流量的路由和处理。这些规则由当地硬件中的交换机维护,例如三元内容可寻址存储器(TCAM),支持通配符模式的高速并行查找。然而,由于其对成本和功率的高要求,但硬件交换机的容量限制为数千个。为了通过使用软件交换机甚至数据包丢失来避免速度较慢匹配,我们可以组流量,以便所有匹配规则都可以放在硬件交换机中。在这样的分组中,每个组中的所有流程只匹配一个规则,并且将转发到相同的路由路径,而不是匹配一个规则的每个流。由于更长的新分组的服务链处理,这将导致更长的延迟。在本文中,我们有效地组流动,以最小化总成本,同时满足硬件交换机中转发表的容量约束。我们首先证明了我们的目标职能的子系统,并提出了相应的性能保证解决方案。此外,我们根据经典的K均值算法设计一种高效的启发式解决方案。此外,我们包括关于动态网络情况的讨论(插入,删除和更新流量)和替代目标。我们还对我们的测试平台进行了真实的实验,以表明我们的动机的实用性。进行广泛的模拟以评估我们所提出的算法的性能。

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