Control and Data Planes in Software Defined Data Center Networks: A Scalable and Resilient Approach

Abstract

The single central controller of Software Defined Network (SDN) eases network management, but leads to scalability problems. It is therefore ideal to have a logically centralized but physically distributed set of controllers. As part of this work we developed a novel placement metric called subgraph-survivability and designed an algorithm for controller placement using this metric, such that the control plane is not only scalable but also resilient to failure of the controller itself. The controller collects the network statistics information and also communicates the forwarding rules to the switches. This lead to the Edge-Core SDN architecture, where the edge and core network have their own edge and core controller. For such networks, we have developed a separate edge and core controller placement algorithms using suitable metrics for each. The scalability problem of the data plane is due to the limited switch memory and increased size of SDN forwarding rule. Using source routing to forward packets, not only alleviates this problem but also complements the Edge-Core SDN model. Here, we have proposed a source routing mechanism that is scalable, is fair to both elephant and mice traffic, and is resilient to link failures, thus making the data plane scalable and resilient. The algorithm and routing mechanism are validated, through both analytical and empirical methods. The performance metrics of Average Inverse Shortest Path Length (AISPL) and Network Disconnectedness (ND) are used to evaluate our placement algorithms. An improvement of 55.88% for the AISPL metric and 49.22% for ND metric, was observed with our proposed algorithm as compared to the random controller placement. With our source routing mechanism we observe a reduction, in the number of flow table entries and the flow set up time, that is proportional to the number of hops along the path of the packet.