A Quantum Approximate Optimization Algorithm for Resource Allocation in Database System
Jakub Kołota · IEEE Access · 2026
This paper presents a novel approach for partitioning database sessions into groups using the quantum MaxCut problem solved by the Quantum Approximate Optimization Algorithm (QAOA). Each session is represented as a node in a graph, with edges indicating the degree of resource contention between sessions. By defining a comprehensive resource demand function that accounts for CPU time, memory usage, and input/output operations, the problem is formulated as a graph partitioning task aimed at optimally distributing sessions to minimize overlap and enhance resource utilization. The paper outlines the implementation of the QAOA algorithm using Cirq, including the construction of the quantum circuit, the optimization of parameters, and the measurement of results. The results are visualized through graphs and heatmaps that illustrate the division of sessions and the reduction in resource contention. As its main contribution, the paper demonstrates the practical application of quantum algorithms to resource allocation in database systems, indicating a promising approach for improving system performance and mitigating resource conflicts.