# Mobility-Aware Hybrid Flow Rule Cache Scheme in Software-Defined Access Networks
## 1 Introduction
In this case, if the flow rules for flows 1 and 2 are again installed by means of the reactive operation, the response delay for installation is required. In addition, if there are other flow rule installation requests at the same time, the delay becomes higher, which can result in quality of service (QoS) degradation, especially for the delay-sensitive flow (i.e., flow 1). Although the mobility management protocols have been applied in the SDN-based access networks, such as the distributed mobility management [14] and proxy mobile IPv6 [15], to preserve the IP address during mobility, the response delay issue is unavoidable because such protocols are operated in the control plane after the forwarding plane delivers the packet-in messages to the controller [16; 17]. To handle the response delay issue, several works on proactive flow rule caching considering the mobility features have been conducted [6; 11; 12; 18; 19; 20; 21; 22; 23; 24]. These works proactively cache the flow rules to the predicted target forwarding nodes, utilizing mobility prediction models such as the Markov predictor [12; 18; 19; 21] and machine learning [20]. Since these models naturally have a prediction error according to variable factors, some of the proactively cached rules can be a waste of resources, being repetitively cached with multiple forwarding nodes, and are not utilized at all. In addition, these works focused on the proactive rule cache method based on mobility prediction without considerations of the load status of the controller. This means that they proactively cache the flow rules even when the fast response delay of the controller is guaranteed. In other words, some proactively cached flow rules in these works can be uncertain, even though the controller can manage the rules with certainty based on the intelligence and network view. As mentioned above, because of the location prediction error, reactive flow rule placement can be more efficient than the proactive approach if the controller's response delay meets the delay requirements of the flows. To address the problems above, this paper proposes a hybrid flow rule cache scheme which proactively as well as reactively caches the flow rules based on the response delay of the controller and delay requirements of the flows. After we formulate the proposed hybrid flow rule cache problem to minimize the waste of resources, extensive simulation results are provided which show that the proposed scheme can reduce the waste of resources and enhance the flow rule hit ratio compared with the previous works. The key contributions of this paper are twofold: (1) to the best our knowledge, this is the first work to optimize the performance of the flow rule cache problem with the consideration of the response delay from the controller, which can be a key performance metric to determine whether the proactive flow rule cache is required or not, and (2) we evaluate the proposed hybrid flow rule cache scheme in terms of the flow table utilization ratio, flow rule installation delay, and flow rules hit ratio under various environments, which can provide valuable design guidelines for advanced software-defined access networks. The remainder of this paper is organized as follows. The related works on the rule placement problem are presented in Section 2. Then, the system model and proposed hybrid cache scheme are described in Sections 3 and 4, respectively. After Section 5 presents the performance evaluation, Section 6 concludes this paper.