Modeling flow setup time for controller placement in SDN: Evaluation for dynamic flows

Abstract

Software-Defined Networking (SDN) controllers are network entities that act as strategic control points in an SDN network. Controller placement studies mostly aim at optimizing network performance in terms of control latency, reliability and resilience, given network characteristics that are static. Yet dynamic traffic conditions, if not adapted by the controller placement properly, may cause high end-to-end flow setup time. For reactive controllers, the end-to-end flow setup time of a flow implies the difference between sending time at the source and receiving time at the sink of the first packet in that flow. Therefore, end-to-end flow setup time indicates the amount of time needed to set up forwarding rules in all involved switches and acts as a primary concern in terms of service establishment of network operators. In this paper, we analyze the controller placement for dynamic traffic flows based on a combined controller placement model: controller locations and switch-to-controller assignments are simultaneously optimized for minimum average flow setup time with respect to different traffic conditions inside the network. Linearization method is applied to transform the problem into a Mixed Integer Programming (MIP) problem which can be solved optimally. Two derivatives are also presented for comparison, one optimizing only controller locations and the other optimizing only switch-to-controller assignments. Our simulations cover two real network topologies and we explain the effects of the models have on the flow setup time with respect to dynamic flows. For low flow densities, the controller placement that adapts to flows could reduce the average flow setup time by about 50% compared to the static placement. However, when densities are high, the need of changing controller placement to guarantee flow setup performance is marginal.

Toward a Flexible Design of SDN Dynamic Control Plane: An Online Optimization Approach

“…Dyn. Main Optimization Metrics(s) [14] Average control latency [11] Average flow setup time [31] Control plane operational cost [15] Control latency & load imbalance [32] Controller utilization and operational cost [16] Average control latency [17] Max. control latency upon controller failures [18] Avg.…”

“…The control path latency of a switch v, i.e., l (t) V (v), is defined as the shortest path latency between the switch v and the respective controller instance φ on node c, which is described in Constraint (10). For every two switches, Constraint (11) states that they are in the same control domain if they are assigned to the same controller. To derive variable d (16) and (17), defined as:…”

“…In order to be able to solve the offline optimization problem with linear optimizer, such as Gurobi and CPLEX, we need to linearize the non-linear equations in Problem P. The high order constraints, i.e., Constraints (11), (13), (15), (16) and (17), can be linearized without loss of optimality [11]). For the definition (18), however, we need to apply piecewise linear approximation and define the following linear relationship between μ (t) Φ (φ) (the expected processing time of a flow setup request at a controller) and λ (t) Φ (φ) (the total number of flow setup requests the controller needs to process),…”

“…The advantages of SD-WAN, its flexibility in particular, do not come at no cost: the flow setup time overhead [11] and the controller synchronization [12] are two major factors that worth consideration. Working in the reactive mode, a switch needs to contact the controller for each new flow before it knows where to forward the packets.…”

How flexible is dynamic SDN control plane?

“…The linear optimization model, which is presented in our previous work [16], takes flow profiles as input and minimizes Binary variable representing whether a switch v ∈ V is assigned to a controller c ∈ C clv Non-negative variable representing the control latency of a switch v ∈ V ddu,v Binary variable representing whether two switches u ∈ V and v ∈ V are in different control domains nru,v…”