Fujitsu, University of Toronto optimize network transformation

Fujitsu has confirmed the effectiveness of Fujitsu's Quantum-inspired Digital Annealer technology for optimizing the transformation process of legacy telecommunications networks.

The project, the result of joint research conducted with the University of Toronto between April 2021 and February 2023, marks the first time in the world that quantum inspired technology has been applied to network modernization.

Fujitsu and University of Toronto

Fujitsu has derived a combinatorial optimization formula and developed a solution using the Digital Annealer to find the best circuit migration plan, which plays a crucial role in the rapid and cost efficient transformation of legacy networks.

This approach allows Fujitsu to help network operator customers reduce the operating costs of legacy facilities by up to 30% and the transportation costs of engineers by up to 80% during the migration period compared with conventional commercial optimization software.

Fujitsu, through its network business, will deliver this technology to network operator customers in North America, which leads the way in network modernization. Further research and development will be conducted on new applications of this technology. Fujitsu aims to leverage the Digital Annealer to create new value and enhance its customers' competitiveness across a number of industries, and ultimately contribute to greater sustainability for industry and society as a whole.

Details of the technology will be presented at the international conference The Optical Fiber Communication Conference and Exposition (OFC) 2023 to be held March 5 - March 9 in San Diego, United States.

Quantum-inspired optimization significantly streamlines network migration

Traditionally, network equipment has been regularly updated and replaced to maintain the integrity of networks. In many cases, however, this work has been for small networks, and network operators have conducted migration planning manually. For today's wide-area networks in countries and regions where the need to migrate is urgent, large numbers of circuits and network elements are complexly interrelated, and the combination of possible circuit migration sequences is 10 to the power of 150 or more even for a case of small network. This essentially renders it impossible to manually derive the optimum combination from these variables within a practical timeframe.

As part of joint research with Professor Shahrokh Valaee and his team at the University of Toronto, Fujitsu has derived combinatorial optimization formulation for searching the circuit migration sequences that minimize costs using the Digital Annealer and analyzed performance of multiple large-scale networks examples with dozens of network elements and hundreds of circuits. Digital Annealer significantly reduces the search space of variable combinations, making it possible to rapidly generate an optimal migration sequence. For the trial, Fujitsu has developed an algorithm that represents the optimization problem with two-way, one-hot constraints. This made it possible to carry out searches that take advantage of the strengths of the Digital Annealer, achieving significant improvement in speed to conduct the network modernization.