[en] Quantum Internet (QI) is a system of interconnected quantum computers able to exchange information encoded in the so called quantum bits (qubits). Differently from the classical counterpart, qubits benefit from a manifold properties guaranteed by quantum mechanics, such as superposition and entanglement. Despite the fact that quantum networks bring significant advantages, several phenomena can negatively impact the overall system, potentially hindering communication. In order to evaluate the network performance, a comprehensive probability expression is derived in this work to ultimately determine how many qubits are expected to be successfully received by nodes. On this basis, a Mixed-Integer Non-Linear Programming (MINLP) problem is formulated to fairly maximize the qubits exchanged between node pairs and jointly optimize 1) the position of the quantum source, and 2) the entanglement distribution plan. To cope with the non-convexity of the problem, an iterative optimization algorithm, leveraging Block Coordinate Descendent (BCD) and Successive Convex Approximation (SCA) techniques, is proposed. A thorough simulation campaign is conducted to corroborate the theoretical findings. Numerical results demonstrates, under different parameter setups, that the proposed algorithm provides superior performance with respect to a baseline approach.
Disciplines :
Ingénierie électrique & électronique
Auteur, co-auteur :
IACOVELLI, Giovanni ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
Vista, Francesco ; The Department of Electrical and Information Engineering, Politecnico di Bari, Bari, Italy ; Consorzio Nazionale Interuniversitario per le Telecomunicazioni, Parma, Italy
Cordeschi, Nicola ; The Department of Electrical and Information Engineering, Politecnico di Bari, Bari, Italy ; Consorzio Nazionale Interuniversitario per le Telecomunicazioni, Parma, Italy
Grieco, Luigi Alfredo ; The Department of Electrical and Information Engineering, Politecnico di Bari, Bari, Italy ; Consorzio Nazionale Interuniversitario per le Telecomunicazioni, Parma, Italy
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
A Probability-Based Optimization Approach for Entanglement Distribution and Source Position in Quantum Networks
Date de publication/diffusion :
juillet 2024
Titre du périodique :
IEEE Journal on Selected Areas In Communications
ISSN :
0733-8716
Maison d'édition :
Institute of Electrical and Electronics Engineers Inc.
L. Gyongyosi and S. Imre, “A survey on quantum computing technology,” Comput. Sci. Rev., vol. 31, pp. 51–71, Feb. 2019.
A. W. Harrow and A. Montanaro, “Quantum computational supremacy,” Nature, vol. 549, no. 7671, pp. 203–209, Sep. 2017.
G. T. Byrd and Y. Ding, “Quantum computing: Progress and innovation,” Computer, vol. 56, no. 1, pp. 20–29, Jan. 2023.
A. S. Cacciapuoti, M. Caleffi, F. Tafuri, F. S. Cataliotti, S. Gherardini, and G. Bianchi, “Quantum internet: Networking challenges in distributed quantum computing,” IEEE Netw., vol. 34, no. 1, pp. 137–143, Sep. 2020.
M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information: 10th Anniversary Edition. Cambridge, U.K.: Cambridge Univ. Press, 2010.
J. Preskill, “Quantum computing in the NISQ era and beyond,” Quantum, vol. 2, p. 79, Aug. 2018.
H. J. Kimble, “The quantum internet,” Nature, vol. 453, no. 7198, pp. 1023–1030, Jun. 2008.
M. Caleffi, A. S. Cacciapuoti, and G. Bianchi, “Quantum internet: From communication to distributed computing!” in Proc. 5th ACM Int. Conf. Nanosc. Comput. Commun. New York, NY, USA: Association for Computing Machinery, 2018, pp. 1–4.
S. Wehner, D. Elkouss, and R. Hanson, “Quantum internet: A vision for the road ahead,” Science, vol. 362, no. 6412, Oct. 2018.
F. Vista, V. Musa, G. Piro, L. A. Grieco, and G. Boggia, “Network intelligence with quantum computing in 6G and B6G: Design principles and future directions,” in Proc. IEEE Globecom Workshops, Dec. 2021, pp. 1–6.
D. Cuomo, M. Caleffi, and A. S. Cacciapuoti, “Towards a distributed quantum computing ecosystem,” IET Quantum Commun., vol. 1, no. 1, pp. 3–8, Jul. 2020.
R. Horodecki, P. Horodecki, M. Horodecki, and K. Horodecki, “Quantum entanglement,” Rev. Mod. Phys., vol. 81, p. 865, Jun. 2009.
C. H. Bennett, G. Brassard, C. Crépeau, R. Jozsa, A. Peres, and W. K. Wootters, “Teleporting an unknown quantum state via dual classical and Einstein-Podolsky-Rosen channels,” Phys. Rev. Lett., vol. 70, no. 13, pp. 1895–1899, Mar. 1993.
J. Illiano, M. Caleffi, A. Manzalini, and A. S. Cacciapuoti, “Quantum internet protocol stack: A comprehensive survey,” Comput. Netw., vol. 213, Aug. 2022, Art. no. 109092.
W. Kozlowski, A. Dahlberg, and S. Wehner, “Designing a quantum network protocol,” in Proc. Int. Conf. Emerg. Netw. Exp. Technol. (CoNEXT). New York, NY, USA: Association for Computing Machinery, 2020, pp. 1–16.
K. Chakraborty, D. Elkouss, B. Rijsman, and S. Wehner, “Entanglement distribution in a quantum network: A multicommodity flow-based approach,” IEEE Trans. Quantum Eng., vol. 1, pp. 1–21, 2020.
C. Li, T. Li, Y.-X. Liu, and P. Cappellaro, “Effective routing design for remote entanglement generation on quantum networks,” npj Quantum Inf., vol. 7, no. 1, p. 10, Jan. 2021.
J. Li et al., “Fidelity-guaranteed entanglement routing in quantum networks,” IEEE Trans. Commun., vol. 70, no. 10, pp. 6748–6763, Oct. 2022.
Y. Zhao, G. Zhao, and C. Qiao, “E2E fidelity aware routing and purification for throughput maximization in quantum networks,” in Proc. IEEE Int. Conf. Comput. Commun. (INFOCOM), 2022, pp. 480–489.
W. Dai, T. Peng, and M. Z. Win, “Quantum queuing delay,” IEEE J. Sel. Areas Commun., vol. 38, no. 3, pp. 605–618, Mar. 2020.
W. Dai, T. Peng, and M. Z. Win, “Optimal remote entanglement distribution,” IEEE J. Sel. Areas Commun., vol. 38, no. 3, pp. 540–556, Mar. 2020.
C. Cicconetti, M. Conti, and A. Passarella, “Request scheduling in quantum networks,” IEEE Trans. Quant. Eng., vol. 2, pp. 2–17, 2021.
L. Chen et al., “A heuristic remote entanglement distribution algorithm on memory-limited quantum paths,” IEEE Trans. Commun., vol. 70, no. 11, pp. 7491–7504, Nov. 2022.
M. Chehimi and W. Saad, “Entanglement rate optimization in heterogeneous quantum communication networks,” in Proc. 17th Int. Symp. Wireless Commun. Syst. (ISWCS), Sep. 2021, pp. 1–6.
C. Qiao, Y. Zhao, G. Zhao, and H. Xu, “Quantum data networking for distributed quantum computing: Opportunities and challenges,” in Proc. IEEE INFOCOM IEEE Conf. Comput. Commun. Workshops (INFOCOM WKSHPS), May 2022, pp. 1–6.
S. P. Boyd and L. Vandenberghe, Convex Optimization. Cambridge, U.K.: Cambridge Univ. Press, 2004.
J.-W. Pan, C. Simon, C. Brukner, and A. Zeilinger, “Entanglement purification for quantum communication,” Nature, vol. 410, no. 6832, pp. 1067–1070, Apr. 2001.
A. S. Cacciapuoti, M. Caleffi, R. Van Meter, and L. Hanzo, “When entanglement meets classical communications: Quantum teleportation for the quantum internet,” IEEE Trans. Commun., vol. 68, no. 6, pp. 3808–3833, Jun. 2020.
J. Illiano, A. S. Cacciapuoti, A. Manzalini, and M. Caleffi, “The impact of the quantum data plane overhead on the throughput,” Proc. Eight Annu. ACM Int. Conf. Nanosc. Comput. Commun., pp. 1–6, 2021.
L. Gyongyosi, S. Imre, and H. V. Nguyen, “A survey on quantum channel capacities,” IEEE Commun. Surveys Tuts., vol. 20, no. 2, pp. 1149–1205, 2nd Quart., 2018.
G. Vardoyan, S. Guha, P. Nain, and D. Towsley, “On the stochastic analysis of a quantum entanglement distribution switch,” IEEE Trans. Quantum Eng., vol. 2, pp. 1–16, 2021.
Z. Babar et al., “Duality of quantum and classical error correction codes: Design principles and examples,” IEEE Commun. Surveys Tuts., vol. 21, no. 1, pp. 970–1010, 1st Quart., 2019.
G. Scutari and Y. Sun, Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization. Cham, Switzerland: Springer, 2018.