TY - GEN
T1 - Online Entanglement Routing in Quantum Networks
AU - Yang, Lan
AU - Zhao, Yangming
AU - Xu, Hongli
AU - Qiao, Chunming
N1 - Publisher Copyright: © 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Quantum Data Networks (QDNs) typically leverage teleportation to reliably send data quantum bits (called qubits) to their destinations. To teleport a data qubit from Alice to Bob, one entanglement connection between Alice and Bob needs to be established. Accordingly, we have to establish as many entanglement connections as possible with limited quantum resources in order to maximize the network throughput. Conventional methods assume a known traffic matrix and calculate the paths to establish entanglement connections in one batch using a centralized algorithm. However, these methods are not scalable in large scale QDNs since it is time consuming to optimize the entanglement paths for a batch of requests, which may result in a long time slot duration and significantly reduce the network throughput. To address this issue, we propose an Online Entanglement Routing (OER) scheme which determines the entanglement paths for each request when it arrives. In addition, OER pursues work conservation and fairness among all requests in the QDNs. Through extensive simulations, we demonstrate that OER not only outperforms two representative heuristics by up to 61.27% and 52.79%, respectively, in terms of average request completion time, but also achieves a better fairness performance than these two counterparts.
AB - Quantum Data Networks (QDNs) typically leverage teleportation to reliably send data quantum bits (called qubits) to their destinations. To teleport a data qubit from Alice to Bob, one entanglement connection between Alice and Bob needs to be established. Accordingly, we have to establish as many entanglement connections as possible with limited quantum resources in order to maximize the network throughput. Conventional methods assume a known traffic matrix and calculate the paths to establish entanglement connections in one batch using a centralized algorithm. However, these methods are not scalable in large scale QDNs since it is time consuming to optimize the entanglement paths for a batch of requests, which may result in a long time slot duration and significantly reduce the network throughput. To address this issue, we propose an Online Entanglement Routing (OER) scheme which determines the entanglement paths for each request when it arrives. In addition, OER pursues work conservation and fairness among all requests in the QDNs. Through extensive simulations, we demonstrate that OER not only outperforms two representative heuristics by up to 61.27% and 52.79%, respectively, in terms of average request completion time, but also achieves a better fairness performance than these two counterparts.
UR - https://www.scopus.com/pages/publications/85135372103
U2 - 10.1109/IWQoS54832.2022.9812920
DO - 10.1109/IWQoS54832.2022.9812920
M3 - Conference contribution
T3 - 2022 IEEE/ACM 30th International Symposium on Quality of Service, IWQoS 2022
BT - 2022 IEEE/ACM 30th International Symposium on Quality of Service, IWQoS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 30th IEEE/ACM International Symposium on Quality of Service, IWQoS 2022
Y2 - 10 June 2022 through 12 June 2022
ER -