Imperial College London
Alternate

ProfessorKinLeung

Faculty of Engineering, Department of Electrical and Electronic Engineering

Tanaka Chair in Internet Technology
 
 
 
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Contact

 

+44 (0)20 7594 6238kin.leung Website

 
 
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Assistant

 

Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267

 
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Location

 

810aElectrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Zhang:2021:10.1117/12.2587874,
author = {Zhang, Z and Mudgerikar, A and Singla, A and Leung, KK and Bertino, E and Verma, D and Chan, K and Melrose, J and Tucker, J},
doi = {10.1117/12.2587874},
pages = {1--11},
publisher = {SPIE-INT SOC OPTICAL ENGINEERING},
title = {Reinforcement and transfer learning for distributed analytics in fragmented software defined coalitions},
url = {http://dx.doi.org/10.1117/12.2587874},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - By extending the Software Defined Networking (SDN), the Distributed Analytics and Information Sciences International Technology Alliance (DAIS ITA) https://dais-ita.org/pub has introduced a new architecture called Software Defined Coalitions (SDC) to share communication, computation, storage, database, sensor and other resources among coalition forces. Reinforcement learning (RL) has been shown to be effective for managing SDC. Due to link failure or operational requirements, SDC may become fragmented and reconnected again over time. This paper shows how data and knowledge acquired in the disconnected SDC domains during fragmentation can be used via transfer learning (TL) to significantly enhance the RL after fragmentation ends. Thus, the combined RL-TL technique enables efficient management and control of SDC despite fragmentation. The technique also enhances the robustness of the SDC architecture for supporting distributed analytics services.
AU  - Zhang,Z
AU  - Mudgerikar,A
AU  - Singla,A
AU  - Leung,KK
AU  - Bertino,E
AU  - Verma,D
AU  - Chan,K
AU  - Melrose,J
AU  - Tucker,J
DO  - 10.1117/12.2587874
EP  - 11
PB  - SPIE-INT SOC OPTICAL ENGINEERING
PY  - 2021///
SN  - 0277-786X
SP  - 1
TI  - Reinforcement and transfer learning for distributed analytics in fragmented software defined coalitions
UR  - http://dx.doi.org/10.1117/12.2587874
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000705912400043&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11746/2587874/Reinforcement-and-transfer-learning-for-distributed-analytics-in-fragmented-software/10.1117/12.2587874.full?SSO=1
UR  - http://hdl.handle.net/10044/1/93947
ER  -
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