Balancer: A Traffic-Aware Hybrid Rule Allocation Scheme in Software Defined Networks

Abstract

In Software Defined Networking (SDN), the severe conflict between rule number and memory size has attracted considerable academic attention. Ternary Content Addressable Memory (TCAM), generally used to guarantee the query speed, is a scarce and expensive resource, which limits the number of rules that the switch can support. However, the table miss may increase processing burden of the controller and cause latency issues. Therefore, it is significantly important to improve the efficiency of TCAM in SDN switches. In this paper, we propose BALANCER, a traffic-aware hybrid rule allocation scheme. In BALANCER, we logically split TCAM into two parts: reactive and proactive, which can be dynamically adjusted according to network traffic behavior. Also, we propose an algorithm to generate proactive rules with high entropy in the proactive part, and for the reactive part, we provide a rule caching approach and an efficient rule replacement algorithm, Multi-Bucket. To evaluate BALANCER, we conduct comprehensive experiments with both synthetic and real-world routing policies. Compared with the reactive mode and the proactive mode, results show that BALANCER achieves the least update costs while the number of table misses is extremely close to that in the proactive mode.