Reliability Of Control Plane Research Articles

Predictive Switch-Controller Association and Control Devolution for SDN Systems

For software-defined networking (SDN) systems, to enhance the scalability and reliability of control plane, existing solutions adopt either multi-controller design with static switch-controller association, or static control devolution by delegating certain request processing back to switches. Such solutions can fall short in face of temporal variations of request traffics, incurring considerable local computation costs on switches and their communication costs to controllers. So far, it still remains an open problem to develop a joint online scheme that conducts dynamic switch-controller association and dynamic control devolution. In addition, the fundamental benefits of predictive scheduling to SDN systems still remain unexplored. In this paper, we identify the non-trivial trade-off in such a joint design and formulate a stochastic network optimization problem which aims to minimize time-averaged total system costs and ensure long-term queue stability. By exploiting the unique problem structure, we devise a predictive online switch-controller association and control devolution (POSCAD) scheme, which solves the problem through a series of online distributed decision making. Theoretical analysis shows that without prediction, POSCAD can achieve near-optimal total system costs a tunable trade-off for queue stability. With prediction, POSCAD can achieve even better performance with shorter latencies. We conduct extensive simulations to evaluate POSCAD. Notably, with mild-value of future information, POSCAD incurs a significant reduction in request latencies, even when faced with prediction errors.

A novel stateful PCE-cloud based control architecture of optical networks for cloud services

The next-generation optical network is a service oriented network, which could be delivered by utilizing the generalized multi-protocol label switching (GMPLS) based control plane to realize lots of intelligent features such as rapid provisioning, automated protection and restoration (P&R), efficient resource allocation, and support for different quality of service (QoS) requirements. In this paper, we propose a novel stateful PCE-cloud (SPC) based architecture of GMPLS optical networks for cloud services. The cloud computing technologies (e.g. virtualization and parallel computing) are applied to the construction of SPC for improving the reliability and maximizing resource utilization. The functions of SPC and GMPLS based control plane are expanded according to the features of cloud services for different QoS requirements. The architecture and detailed description of the components of SPC are provided. Different potential cooperation relationships between public stateful PCE cloud (PSPC) and region stateful PCE cloud (RSPC) are investigated. Moreover, we present the policy-enabled and constraint-based routing scheme base on the cooperation of PSPC and RSPC. Simulation results for verifying the performance of routing and control plane reliability are analyzed.