Within the hierarchy of the Software Defined Network (SDN) network stack, the control layer operates as the critical middleware facilitator of interactions between the data plane and the network applications, which govern flow routing decisions. In the OpenFlow implementation of the SDN model, the control layer, commonly referred to as a network operating system (NOS), has been realized by a range of competing implementations that offer various performance and functionality advantages: Floodlight, POX, NOX, and ONIX. In this paper we focus on the question of control layer resilience, when rapidly developed prototype network applications go awry, or third-party network applications incorporate unexpected vulnerabilities, fatal instabilities, or even malicious logic. We demonstrate how simple and common failures in a network application may lead to loss of the control layer, and in effect, loss of network control. To address these concerns we present the ROSEMARY controller, which implements a network application containment and resilience strategy based around the notion of spawning applications independently within a micro-NOS. ROSEMARY distinguishes itself by its blend of process containment, resource utilization monitoring, and an application permission structure, all designed to prevent common failures of network applications from halting operation of the SDN Stack. We present our design and implementation of ROSEMARY, along with an extensive evaluation of its performance relative to several of the mostly well-known and widely used controllers. Rather than imposing significant performance costs, we find that with the integration of two optimization features, ROSEMARY offers a competitive performance advantage over the majority of other controllers.

We present a novel control-theoretic explicit rate (ER) allocation algorithm for the max-min flow control of elastic traffic services with minimum rate guarantee in the context of the ATM ABR service. The proposed ER algorithm is simple in that the number of operations required to compute it at a switch is minimized, scalable in that per-VC (virtual circuit) operations including per-VC queueing, per-VC accounting and per-VC state management are virtually removed, and stable in that by employing it the user transmission rates and the network queues are asymptotically stabilized at a unique equilibrium point at which max-min fairness with minimum rate guarantee and target queue lengths are achieved respectively. To improve the speed of convergence we normalize the controller gains of the algorithm by the estimate of the number of locally-bottlenecked VCs. The estimation scheme is also computationally simple and scalable since it does not require per-VC accounting either. We analyze the theoretical performance of the proposed algorithm and verify its agreement with the practical performance through simulations in the case of multiple bottleneck nodes. We believe that the proposed algorithm will serve as an encouraging solution to the max-min flow control not only in the context of ATM ABR service but also in general elastic traffic services.

We present a novel control-theoretic explicit rate (ER) allocation algorithm for the max-min flow control of elastic traffic services with minimum rate guarantee in the setting of the ATM available bit rate (ABR) service. The proposed ER algorithm is simple in that the number of operations required to compute it at a switch is minimized, scalable in that per-virtual-circuit (VC) operations including per-VC queueing, per-VC accounting, and per-VC state management are virtually removed, and stable in that by employing it, the user transmission rates and the network queues are asymptotically stabilized at a unique equilibrium point at which max-min fairness with minimum rate guarantee and target queue lengths are achieved, respectively. To improve the speed of convergence, we normalize the controller gains of the algorithm by the estimate of the number of locally bottlenecked VCs. The estimation scheme is also computationally simple and scalable since it does not require per-VC accounting either. We analyze the theoretical performance of the proposed algorithm and verify its agreement with the practical performance through simulations in the case of multiple bottleneck nodes. We believe that the proposed algorithm will serve as an encouraging solution to the max-min flow control of elastic traffic services, the deployment of which has been debated long due to their lack of theoretical foundation and implementation complexity.