Efficient Migration to the Next Generation of Networks Based on Digital Annealing

Abstract

Networks are frequently changing due to new technologies. The growing demand for bandwidth is forcing many carriers to migrate their existing network to a network with a new technology in order to increase network performance. Telecommunication companies are looking for optimization algorithms to efficiently manage their network migration. In this paper, the network migration problem is considered as a set of circuit migration problems in which two technicians simultaneously migrate the two ends of a circuit in order to minimize the total accumulated sites in-service and total technician travels. While total accumulated sites in-service indicates how fast the sites can be upgraded during the migration process, total technician travels estimates the required cost. We first formulate our target problem as a constrained binary quadratic program which is NP-hard in general. Our approach for solving the derived optimization problem is based on converting it to a quadratic unconstrained binary optimization problem (QUBO) using the penalty method. Subsequently, we exploit Digital Annealer which is a massively parallel hardware architecture to minimize the derived QUBO. To evaluate our proposed method, we study extensive network migration instances on the 75-node CONUS network topology.

Efficient and Scalable Architecture for Multiple-Chip Implementation of Simulated Bifurcation Machines

“…Combinatorial optimization problems have many applications in finance [1], [2], wireless communications [3], [4], network infrastructure [5], and power distribution [6]. Many of them can be mapped onto an energy minimization problem of Ising spin models [7], which are systems of binary variables having pairwise interactions and individual biases.…”