A FineGrained SDN Rule Table Partitioning and Distribution In SoftwareDefined Networking (SDN) it is important to efficiently partition the rule table into subtables and distribute them to the switches over the network in order to reduce storage size of each switch. In this paper we propose a finegrained rule table partitioning, where the original rule table is partitioned into n subtables and every switch has k subtables. We formulate the problem as a satisfiability (SAT) problem, and use SAT solver to obtain an optimal subtable allocation that minimize the storage size under a given k. Results indicate that the proposed scheme with k  2 can reduce the storage size required to switches in comparison to the conventional scheme, that corresponds to k  1.

Optimization Strategy of OpenFlow Flow Table Storage Based on the Idea of xe2x80x9cBetweenness Centralityxe2x80x9d Since the advent of the Internet, its scale has expanded rapidly. Traditional network architecture is increasingly difficult to support this huge business. At this time, the clean slate team at Stanford University in the United States defined a new network architecture, SDN (Software Defined Network). The introduction of this network architecture has brought about tremendous changes in the development of todayxe2x80x99s networks. The separation of control layer from data layer through SDN enables network administrators to plan the network programmatically without changing network devices, realizing flexible configuration of network devices and fast forwarding of data flows. The controller sends the flow table down to the switch, and the data flow is forwarded through matching flow table items. However, the current flow table resources of the SDN switch are very limited. Therefore, this paper studies the technology of the latest SDN Flow table optimization at home and abroad, proposes an efficient optimization scheme of Flow table item on the betweenness centrality through the main road selection algorithm, and realizes related applications by setting up experimental topology.