  Quantum cloud computing (QCC) offers a promising approach to efficiently
provide quantum computing resources, such as quantum computers, to perform
resource-intensive tasks. Like traditional cloud computing platforms, QCC
providers can offer both reservation and on-demand plans for quantum resource
provisioning to satisfy users' requirements. However, the fluctuations in user
demand and quantum circuit requirements are challenging for efficient resource
provisioning. Furthermore, in distributed QCC, entanglement routing is a
critical component of quantum networks that enables remote entanglement
communication between users and QCC providers. Further, maintaining
entanglement fidelity in quantum networks is challenging due to the requirement
for high-quality entanglement routing, especially when accessing the providers
over long distances. To address these challenges, we propose a resource
allocation model to provision quantum computing and networking resources. In
particular, entangled pairs, entanglement routing, qubit resources, and
circuits' waiting time are jointly optimized to achieve minimum total costs. We
formulate the proposed model based on the two-stage stochastic programming,
which takes into account the uncertainties of fidelity and qubit requirements,
and quantum circuits' waiting time. Furthermore, we apply the Benders
decomposition algorithm to divide the proposed model into sub-models to be
solved simultaneously. Experimental results demonstrate that our model can
achieve the optimal total costs and reduce total costs at most 49.43\% in
comparison to the baseline model.
