EconPapers    
Economics at your fingertips  
 

OpenFlow arbitrated programmable network channels for managing quantum metadata

Venkat R Dasari and Travis S Humble

The Journal of Defense Modeling and Simulation, 2019, vol. 16, issue 1, 67-77

Abstract: Quantum networks must classically exchange complex metadata between devices in order to carry out information for protocols such as teleportation, super-dense coding, and quantum key distribution. Demonstrating the integration of these new communication methods with existing network protocols, channels, and data forwarding mechanisms remains an open challenge. Software-defined networking (SDN) offers robust and flexible strategies for managing diverse network devices and uses. We adapt the principles of SDN to the deployment of quantum networks, which are composed from unique devices that operate according to the laws of quantum mechanics. We show how quantum metadata can be managed within a software-defined network using the OpenFlow protocol, and we describe how OpenFlow management of classical optical channels is compatible with emerging quantum communication protocols. We next give an example specification of the metadata needed to manage and control quantum physical layer (QPHY) behavior and we extend the OpenFlow interface to accommodate this quantum metadata. We conclude by discussing near-term experimental efforts that can realize SDN’s principles for quantum communication.

Keywords: Software-defined networks; optical communication; quantum communication; quantum networks (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1548512916661781 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:joudef:v:16:y:2019:i:1:p:67-77

DOI: 10.1177/1548512916661781

Access Statistics for this article

More articles in The Journal of Defense Modeling and Simulation
Bibliographic data for series maintained by SAGE Publications ().

 
Page updated 2025-03-19
Handle: RePEc:sae:joudef:v:16:y:2019:i:1:p:67-77