In software-defined networking (SDN), the overlapping among the matching fields of rules complicates flow table updates. One update often triggers the movement of multiple ternary content addressable memory (TCAM) entries, which increases the update times. In addition, the TCAMs in existing SDN switches are mostly designed with a single port. The TCAM update suspends the packet lookup which affects the packet forwarding in the data plane. Therefore, how to achieve fast update while supporting wire-speed packet lookup is an important research topic to improve network performance. This paper presents a TCAM-based SDN switch with a flow table update system. When multiple network application updates are integrated at the front end and simultaneously sent to the switch, the system can efficiently detect the dependencies between rules and prioritize the rules which need to be quickly updated, so that they can respond quickly. The update algorithm does not need to block the TCAM search operation and can provide interleaved execution of the packet lookups and rule updates. Tests show that these scheduling strategies improve the system performance by balancing the lookup first algorithm and the update first algorithm.

As a promising approach to improve network reliability, proactive failure recovery (PFR) re-routes failure affected traffic to backup paths without waiting for the completion of IP routing convergence. However, the failure affected traffic may cause congestion if it is not carefully allocated over the backup paths according to their available capacity. A post failure traffic engineering (PostTE) scheme is proposed to balance the load in the PFR scheme. Loop-free backup paths are prepared in advance to cover all the potential single-link failures. The failure affected load is locally allocated to the backup paths through solving a linear programming (LP) problem. Most of the time, the maximum link utilization (MLU) of the network is minimized under both the failure and failure-free cases. For the tested education networks, the LP problem can be solved within milliseconds.