A CPU Load-awared Virtual Router Placement Strategy in Cloud Network

With the increment of the scale of users and networks, network virtualization technology has been widely used by service providers in cloud networks to address elastic network demands. As a fundamental network virtualization component realizing cross-tenant traffic routing, the placement of virtual routers has become a considerable factor influencing the network performance. And through in-depth experiments, we also found that CPU load augments may well incur a significant degradation in network throughput performance, revealing the problems of the placement of virtual routers in existing cloud network modes: 1) Ignore the bandwidth loss caused by the CPU load variation. 2) Lack of theoretical support for the optimal scheme. Based on these above, we propose a CPU load-aware virtual router placement strategy, which balances the computing load situation of each virtual router, and adopts branch and bound algorithm and convex optimization to achieve the approximate optimal placement within 0.1% error. We have evaluated our strategy in our cloud testbed, and find a 20% improvement in terms of cross-tenant throughput compared with the worst case of existing strategies,