# Joint Switch Upgrade and Controller Deployment in Hybrid Software-Defined Networks

## TL;DR

This paper addresses the joint deployment of SDN switches and controllers in hybrid networks, optimizing for flow control capacity and delay, using a formulated NP-hard problem and proposing efficient solutions validated by simulations.

## Contribution

It introduces a novel joint deployment optimization model for hybrid SDNs, considering both switch and controller placement under budget constraints, with tailored algorithms for different network sizes.

## Key findings

- Heuristic algorithm manages many flows with few controllers.
- Proposed techniques accelerate optimization for small networks.
- Simulation shows high flow management efficiency with low delay.

## Abstract

To improve traffic management ability, Internet Service Providers (ISPs) are gradually upgrading legacy network devices to programmable devices that support Software-Defined Networking (SDN). The coexistence of legacy and SDN devices gives rise to a hybrid SDN. Existing hybrid SDNs do not consider the potential performance issues introduced by a centralized SDN controller: flow requests processed by a highly loaded controller may experience long tail processing delay; inappropriate multi-controller deployment could increase the propagation delay of flow requests. In this paper, we propose to jointly consider the deployment of SDN switches and their controllers for hybrid SDNs. We formulate the joint problem as an optimization problem that maximizes the number of flows that can be controlled and managed by the SDN and minimizes the propagation delay of flow requests between SDN controllers and switches under a given upgrade budget constraint. We show this problem is NP-hard. To efficiently solve the problem, we propose some techniques (e.g., strengthening the constraints and adding additional valid inequalities) to accelerate the global optimization solver for solving the problem for small networks and an efficient heuristic algorithm for solving it for large networks. The simulation results from real network topologies illustrate the effectiveness of the proposed techniques and show that our proposed heuristic algorithm uses a small number of controllers to manage a high amount of flows with good performance.