Bilevel Optimization for Provisioning Heterogeneous Traffic in Deterministic Networks

Due to the capabilities of providing extremely low packet loss and bounded end-to-end latency, deterministic networking (DetNet) has been considered as a promising technology for emerging time-sensitive applications (e.g., industrial control and smart grids) in IP networks. To provide deterministic services, the operator needs to address the routing and scheduling problem. In this work, we study the problem from a novel prospective, i.e., the problem should be optimized not only for deterministic traffic, but also for normal traffic to coexist with the former. Specifically, we redefine the problem as bandwidth allocation, routing and scheduling (BaRS), and model this problem as a bilevel optimization which consists of an upper-level optimization and a lower-level optimization. The upper-level optimization allocates link bandwidth between deterministic and normal traffic to maximize the available bandwidth for normal traffic on the premise of accepting a certain portion of deterministic bandwidth; the lower-level optimization determines specific routing and scheduling solutions for deterministic traffic to maximize the number of accepted deterministic flows. We first formulate the bilevel optimization as a bilevel mixed integer linear programming (BMILP). Then, we propose an exact algorithm based on cutting planes to solve it exactly, and propose an approximation algorithm based on two-level relaxations and randomized rounding to solve it effectively and time-efficiently. Extensive simulations are conducted and the results verify the effectiveness of our proposals in balancing the tradeoff between the available bandwidth for normal traffic and the number of accepted deterministic flows.