Soft Partitioning Flow Tables for Virtual Networking in Multi-Tenant Software Defined Networks

In a multi-tenancy software defined network (SDN) environment, physical devices such as switches are shared among tenants. In addition to a centralized controller, each tenant has his own controller that manages resources allocated to the tenant. Hence, the centralized controller performs SDN resource virtualization among tenants and acts as proxy between physical resources and tenant controllers. In order to manage the flow tables of the SDN switches, two partitioning strategies are considered. Hard partitioning of flow tables allocates a fixed amount of flow entries to each tenant, but flow tables are wasted if the tenant does not actually use them. On the other hand, soft partitioning strategy shares available flow entries among tenants, resulting in higher utilization but a resource monopoly problem, i.e., flow entries dominated by some greedy tenants. To achieve high flow table utilization and avoid the resource monopoly problem, we propose a soft-partitioning resource manager (SPRM) to manage the flow table resources in a multi-tenancy SDN environment. In SPRM, the allowed number of flow entries for each tenant ranges from a lower bound which equals to the tenant's quota to an upper bound which is dynamically adjusted according to the tenant's past usage. If an incoming flow request of a tenant is beyond his lower bound but under his upper bound, it could be temporarily accepted when there are free entries available. These borrowed flow entries will later be replaced if needed. If a request of a tenant is beyond his upper bound, SPRM will select a least-recently used flow entry of the tenant and replace it with the new request. In addition, SPRM monitors flow table resources and submits modify flow entry messages directly to SDN switches without checks by the management plane as possible in order to reduce flow modification latency. As a result, SPRM could reach higher flow table utilization and lower both flow entry miss rate and Packet_in events. Experimental results show that 100% flow rejections, and 95% Packet_in events are reduced while flow modification latency is decreased by 30%, as compared to hard partitioning.