Minimizing Delay Cost Of Route Update And Flow Statistics Collection In SDN

Due to flow dynamics,a software defined network(SDN)may need to frequently update its data plane so as to optimize various performance objectives,such as load bal-ancing.Most previous solutions first determine a new route configuration based on the current flow status,and then update the forwarding paths of existing flows.However,due to slow update operations of Ternary Content Addressable Memory(TCAM)based flow tables,unacceptable update delays may occur,especially in a large or frequently changed network.According to recent studies,most flows have short duration and the workload of the entire network will vary significantly after a long duration.As a re-sult,the new route configuration may be no longer efficient for the workload after the update,if the update duration takes too long.Except for route update,the efficiency of flow statistics collection also significantly influences the performance of the entire net-work.In an SDN,the controller needs to frequently collect flow statistics measured at the data plane switches for different applications(e.g.network update,attack detection,etc.).However,existing solutions for flow statistics collection may result in long pro-cessing delay,which significantly interfere with those applications.Main contributions and innovation points of this dissertation are as follows:We address the real-time route update,which jointly considers the optimization of flow route selection in the control plane and update scheduling in the data plane.We formulate the delay-satisfied route update(DSRU)problem,and prove its NP-Hardness.Algorithms with bounded approximation factors are designed to solve this problem.We implement the proposed methods on our SDN testbed.The experimental results and extensive simulation results show that our method can reduce the route update delay by about 60%compared with previous route update methods while preserving a similar routing performance(with link load ratio increased less than 3%).We propose a Cost-Optimized Flow Statistics Collection(CO-FSC)scheme using wildcard-based requests.We present a rounding-based algorithm with an approx-imation factor f(f is the maximum number of switches visited by each flow),and a lower-complexity algorithm using primal-dual.The extensive simulation results show that the proposed algorithms can reduce delay cost by over 45%compared with the existing solutions.