Variational Quantum Algorithms for the Allocation of Resources in a Cloud/Edge Architecture
Modern cloud/edge architectures need to orchestrate multiple layers of heterogeneous computing nodes, including pervasive sensors/actuators, distributed edge/fog nodes, centralized data centers, and quantum devices. The optimal assignment and scheduling of computation on the different nodes is a ver...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Transactions on Quantum Engineering |
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| Online Access: | https://ieeexplore.ieee.org/document/10522849/ |
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| author | Carlo Mastroianni Francesco Plastina Jacopo Settino Andrea Vinci |
| author_facet | Carlo Mastroianni Francesco Plastina Jacopo Settino Andrea Vinci |
| author_sort | Carlo Mastroianni |
| collection | DOAJ |
| description | Modern cloud/edge architectures need to orchestrate multiple layers of heterogeneous computing nodes, including pervasive sensors/actuators, distributed edge/fog nodes, centralized data centers, and quantum devices. The optimal assignment and scheduling of computation on the different nodes is a very difficult problem, with NP-hard complexity. In this article, we explore the possibility of solving this problem with variational quantum algorithms, which can become a viable alternative to classical algorithms in the near future. In particular, we compare the performance, in terms of success probability, of two algorithms, i.e., quantum approximate optimization algorithm and variational quantum eigensolver (VQE). The simulation experiments, performed for a set of simple problems, show that the VQE algorithm ensures better performance when it is equipped with appropriate circuit <italic>ansatzes</italic> that are able to restrict the search space. Moreover, experiments executed on real quantum hardware show that the execution time, when increasing the size of the problem, grows much more slowly than the trend obtained with classical computation, which is known to be exponential. |
| format | Article |
| id | doaj-art-c31b0b4a2d3a4e1a8493790f20fb67d6 |
| institution | Kabale University |
| issn | 2689-1808 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Transactions on Quantum Engineering |
| spelling | doaj-art-c31b0b4a2d3a4e1a8493790f20fb67d62025-01-28T00:02:26ZengIEEEIEEE Transactions on Quantum Engineering2689-18082024-01-01511810.1109/TQE.2024.339841010522849Variational Quantum Algorithms for the Allocation of Resources in a Cloud/Edge ArchitectureCarlo Mastroianni0https://orcid.org/0000-0001-6269-4931Francesco Plastina1https://orcid.org/0000-0001-9615-8598Jacopo Settino2https://orcid.org/0000-0002-7425-4594Andrea Vinci3https://orcid.org/0000-0002-1011-1885Institute for High-Performance Computing and Networking, National Research Council of Italy, Rende, ItalyDipartimento di Fisica, Università della Calabria, Arcavacata, ItalyInstitute for High-Performance Computing and Networking, National Research Council of Italy, Rende, ItalyInstitute for High-Performance Computing and Networking, National Research Council of Italy, Rende, ItalyModern cloud/edge architectures need to orchestrate multiple layers of heterogeneous computing nodes, including pervasive sensors/actuators, distributed edge/fog nodes, centralized data centers, and quantum devices. The optimal assignment and scheduling of computation on the different nodes is a very difficult problem, with NP-hard complexity. In this article, we explore the possibility of solving this problem with variational quantum algorithms, which can become a viable alternative to classical algorithms in the near future. In particular, we compare the performance, in terms of success probability, of two algorithms, i.e., quantum approximate optimization algorithm and variational quantum eigensolver (VQE). The simulation experiments, performed for a set of simple problems, show that the VQE algorithm ensures better performance when it is equipped with appropriate circuit <italic>ansatzes</italic> that are able to restrict the search space. Moreover, experiments executed on real quantum hardware show that the execution time, when increasing the size of the problem, grows much more slowly than the trend obtained with classical computation, which is known to be exponential.https://ieeexplore.ieee.org/document/10522849/Cloud/edge computingquantum computingresource assignment |
| spellingShingle | Carlo Mastroianni Francesco Plastina Jacopo Settino Andrea Vinci Variational Quantum Algorithms for the Allocation of Resources in a Cloud/Edge Architecture IEEE Transactions on Quantum Engineering Cloud/edge computing quantum computing resource assignment |
| title | Variational Quantum Algorithms for the Allocation of Resources in a Cloud/Edge Architecture |
| title_full | Variational Quantum Algorithms for the Allocation of Resources in a Cloud/Edge Architecture |
| title_fullStr | Variational Quantum Algorithms for the Allocation of Resources in a Cloud/Edge Architecture |
| title_full_unstemmed | Variational Quantum Algorithms for the Allocation of Resources in a Cloud/Edge Architecture |
| title_short | Variational Quantum Algorithms for the Allocation of Resources in a Cloud/Edge Architecture |
| title_sort | variational quantum algorithms for the allocation of resources in a cloud edge architecture |
| topic | Cloud/edge computing quantum computing resource assignment |
| url | https://ieeexplore.ieee.org/document/10522849/ |
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