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Dr. Zhiming
Zhao home page |
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Multiscale
Networked Systems (MNS) University of
Amsterdam Email: z.zhao[at]uva.nl Tel: +31
638560996 Office: Room L5.40, Lab
42 Science
Park 900, 1098XH Amsterdam
the Netherlands |
We
are looking for 1. Part time programmers 2. Post doctors 3. PhD students... |
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Recent activities 1. IEEE DAPPS 2022 |
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I am an assistant professor
at University of Amsterdam (UvA). I lead a team on “Quality Critical
Distributed Computing” in the context of Multiscale Networked Systems (MNS) research group,
Informatics Institute (IvI). My
research focuses on innovative
programming and control models for quality critical systems on
programmable infrastructures such as Clouds, Edges, and Software Defined
Networking using optimization, semantic linking, blockchain, and artificial
intelligence technologies. I am specifically interested in big data
management, infrastructure optimization for data-intensive applications, and
trustworthy service level agreements. Since 2014, I have obtained
more than 3M euro funding from the EU H2020 research program to support my
research activities in UvA. I coordinated the project SWITCH (Software
Workbench for interactive time-critical and highly self-adaptive cloud
applications). I led the Data for Science theme in the
environmental science cluster project ENVRIPLUS, and the technical
development work package in its follow up project ENVRI-FAIR.
I also lead the UvA effort in ARTICONF, CLARIFY, BLUECLOUD, and VRE4EIC projects.
I am also the technical manager of the LifeWatch ERIC Virtual Lab & Innovation
Centre (VLIC)
in Amsterdam. |
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Research: Quality Critical Applications on Programmable
Infrastructures |
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In both
scientific and industrial contexts, there are distributed application systems
which 1. have very high
business value (e.g., on-demand business collaboration platforms), or social
impact (e.g., for early warning of disasters); and 2. have very critical requirements
for Quality of Service (QoS) (e.g., tsunami emergency response time) or
quality of experience (QoE) (e.g., delivery of ultra-high definition
television or collaborative business interactions); but 3. are very difficult to
develop and operate because of their distributed nature and the high
requirements for the runtime environment, and in particular, the
sophisticated optimization mechanisms needed for developing and integrating
the system components. Cloud
environments provide virtualized, elastic, controllable, and quality
on-demand services for supporting complex application systems. However,
developing, deploying, and executing quality-critical applications in
programmable infrastructure is still difficult and challenging due to a lack of
effective programming and control mechanisms. My research
interests have revolved around modeling, developing, controlling, and
optimizing such Distributed Quality-Critical Systems.
I specifically focus on novel models for programming, executing, and optimizing
such applications on programmable infrastructures, such as Cloud-
and software-defined networking technologies. My basic approach is to use
autonomous agent technologies to decompose system complexity, to develop
distributed control and optimization intelligence by combining both
application logic and infrastructure programmability, and to investigate
self-adaptable cooperative control models for Cloud-based quality-critical
systems. |
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Leader: Dr. Zhiming Zhao Researchers: ·
J.M. van der Stoep NaaVRE developer (2022-) ·
Dr. Uraz Odyurt, AI and cloud computing (2021-) ·
Dr. Spiros Koulouzis, DRIP, CONF, VRE and
use cases (2017-) Ph.D. students: ·
Yuandou Wang, Distributed data processing (2020-) ·
Na Li, Knowledge discovery (2020-) ·
HongYun Liu, Cloud resource management (2019-) ·
Zhengqiu Zhu, Incentive models in crowd applications
(2020-) ·
Ruyue Xin, Virtual Infrastructure control and
adaptation (2019-) Visiting scholars: Former members ·
Zeshun Shi, Trustworthy Virtual infrastructure
(2018-2022) [thesis] ·
Mr. Ning Chen, Sensor network and robustness
(2021-2022) ·
Riccardo Bianchi (M.Sc), DevOps (2020-2022) ·
Dr. Siamak Farshidi, Knowledge base and data set
search (2020-2022) ·
Dr. Peng Chen, Cloud infrastructure optimization
(2020-2021) ·
Dr. Xiaofeng Liao, Alignment, annotation
(2017-2020) ·
Dr. Paul Martin, Semantic information linking
(2015-2018) ·
Dr. Arie Taal, Time critical applications
(2016-2019) ·
Junchao Wang, Virtual Infrastructure planning
(2015-2020) ·
Hu Yang, Time critical application deployment
(2015-2019) [thesis] ·
Huan Zhou, Virtual infrastructure provisioning
and DevOps (2015-2019)[thesis] |
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Funding and
projects
(PI) |
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1.
EU H2020 CLARIFY (CLoud ARtificial
Intelligence For pathologY). Grant No. 860627. H2020-MSCA-ITN-2019 call.
Duration: Nov 2019-Oct 2023. 2.
EU H2020 BLUECLOUD (Blue-Cloud: Piloting
innovative services for Marine Research & the Blue
Economy).H2020-BG-2018-2020. Grant No. 862409. Duration: Nov 2019-Oct 2022. 3.
EU H2020 ENVRIFAIR (ENVironmental Research
Infrastructures building Fair services Accessible for society, Innovation and
Research). Grant No 824068. H2020-INFRAEOSC-2018-2 call. Duration: January
2019-December 2022. Finished projects 4.
EU H2020 ARTICONF (smART socIal media eCOsytstem in
a blockchaiN Federated environment). Grant No 825134.
H2020-ICT-2018-2 call. Duration: January 2019-December 2021. 5.
EU H2020 ENVRIPLUS (ENVironmental Research
Infrastructures Providing shared soLUtions for Science and
society). Leader of the Data for Science Theme. Grant No. 654182 (Newsletter in IvI, ENVRIPLUS, EGI). Duration: May 2015- April 2019, Project
website: www.envriplus.eu. 6.
EU H2020 VRE4EIC (A Europe-wide interoperable
Virtual Research Environment to Empower multidisciplinary research
communities and accelerate Innovation and Collaboration). Grant number
676247. H2020-EINFRA-2015-1. Duration
October 2015- September 2018. 7. EU H2020 SWITCH (Software
Workbench for Interactive, Time Critical and Highly self-adaptive cloud
applications). Grant No 643963. H2020-ICT 9-2014-1 call: Tools and methods
for software development. Duration: February 2015- January 2018. (SWITCH project). Participated
projects 8. EU FP7 ENVRI. Task
leader, task 3.4: linking data and infrastructure - Common operations of
Environmental Research Infrastructure (ENVRI). Grant number 283465. 9. EU FP7 Geysers,
Researcher Generalised Architecture for Dynamic Infrastructure Services 10. Gigaport/CineGrid, Researcher.
Including network QoS in planning Workflows. 11. Dutch Virtual Laboratory for
e-Science (VL-e), 2005-2009 12. EU FP 6 CrossGrid,
2004-2005 |
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Please feel
free contact me for
details. 1. We are looking for part
time programmers. 2. Open PhD/post doc
positions in big data infrastructures and applications. 3. We welcome CSC (Chinese
Scholar Council) funded students |
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Community |
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Editorial board 1.
Managing editor, Journal of cloud computing,
advances, systems and applications 2.
International journal of: Blockchains:
research and applications 3.
Journal of Circuits,
Systems and Computers Organizer/co-organizer
1. Special session: Using heterogeneous environmental
data for system-level science, 2018, Vienna, EGU
1. in Digital
Infrastructure for research 2016, Krakow, Poland 2. in Digital Infrastructure for research 2017,
Brussels, Belgium
Summer school 1. International summer school on data
management in environmental and earth sciences (2018
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chair
Program
committee
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Journals 1.
Shi,
Z., de Laat, C., Grosso, P., Zhao, Z.: Integration of Blockchain and
Auction Models: A Survey, Some Applications, and Challenges. IEEE Commun.
Surv. Tutorials. 1–1 (2022). https://doi.org/10.1109/COMST.2022.3222403. 2.
Zhu,
Z., Ai, C., Chen, H., Chen, B., Duan, W., Qiu, X., Lu, X., He, M., Zhao,
Z., Liu, Z.: Understanding the Necessity and Economic Benefits of
Lockdown Measures to Contain COVID-19. IEEE Trans. Comput. Soc. Syst. 1–13
(2022). https://doi.org/10.1109/TCSS.2022.3194639
3.
Xiao,
H., Li, P., Zeng, H., Liang, T., Jiang, W., Zhao, Z.: Metric
learning-based whole health indicator model for industrial robots. Int J of
Intelligent Sys. int.23008 (2022). https://doi.org/10.1002/int.23008
4.
Yuan,
S., Wang, Y., Liang, T., Jiang, W., Lin, S., Zhao, Z.: Real-time
recognition and warning of mask wearing based on improved YOLOv5 R6.1. Int J
of Intelligent Sys. int.22994 (2022). https://doi.org/10.1002/int.22994
5.
Shi,
Z., Ivankovic, V., Farshidi, S., Surbiryala, J., Zhou, H., Zhao, Z.:
AWESOME: an auction and witness enhanced SLA model for decentralized cloud
marketplaces. J Cloud Comp. 11, 27 (2022). https://doi.org/10.1186/s13677-022-00292-8 6.
Zhu,
Z., Chen, B., Chen, H., Qiu, S., Fan, C., Zhao, Y., Guo, R., Ai, C., Liu, Z.,
Zhao, Z., Fang, L., Lu, X.: Strategy evaluation and optimization with
an artificial society toward a Pareto optimum. The Innovation. 3, 100274
(2022). https://doi.org/10.1016/j.xinn.2022.100274
7.
Chen,
P., Liu, H., Xin, R., Carval, T., Zhao, J., Xia, Y., Zhao, Z.:
Effectively Detecting Operational Anomalies In Large-Scale IoT Data
Infrastructures By Using A GAN-Based Predictive Model. The Computer Journal.
65, 2909–2925 (2022). https://doi.org/10.1093/comjnl/bxac085
8.
Shi,
Z., Zhou, H., de Laat, C., Zhao, Z.: A Bayesian game-enhanced auction
model for federated cloud services using blockchain. Future Generation
Computer Systems. S0167739X22001881 (2022). https://doi.org/10.1016/j.future.2022.05.017.
9.
Zhao,
Z., Koulouzis, S., Bianchi, R.,
Farshidi, S., Shi, Z., Xin, R., Wang, Y., Li, N., Shi, Y., Timmermans, J.,
Kissling, W.D.: Notebook-as-a-VRE (NaaVRE): From private notebooks to a
collaborative cloud virtual research environment. Softw Pract Exp. spe.3098
(2022). https://doi.org/10.1002/spe.3098. 10. Wang, Y., Koulouzis, S., Bianchi, R., Li, N., Shi,
Y., Timmermans, J., Kissling, W.D., Zhao, Z.: Scaling Notebooks as
Re-configurable Cloud Workflows. Data Intelligence. 4, 409–425 (2022). https://doi.org/10.1162/dint_a_00140. 11. Wittenburg, P., Hardisty, A., Franc, Y.L.,
Mozaffari, A., Peer, L., Skvortsov, N.A., Zhao, Z., Spinuso, A.:
Canonical Workflows to Make Data FAIR. Data Intelligence. 1–20 (2022). https://doi.org/10.1162/dint_a_00132 12. Jiang, W., Pan, S., Lu, C., Zhao, Z., Lin,
S., Xiong, M., He, Z.: Label entropy-based cooperative particle swarm
optimization algorithm for dynamic overlapping community detection in complex
networks. Int J Intell Syst. int.22673 (2021). https://doi.org/10.1002/int.22673. 13. Farshidi, S., Liao, X., Li, N., Goldfarb, D.,
Magagna, B., Stocker, M., Jeffery, K., Thijsse, P., Pichot, C., Petzold, A., Zhao,
Z.: Knowledge sharing and discovery across heterogeneous research
infrastructures. Open Res Europe. 1, 68 (2021). https://doi.org/10.12688/openreseurope.13677.1.
14. Karandikar, N., Abhishek, R., Saurabh, N., Zhao,
Z., Lercher, A., Marina, N., Prodan, R., Rong, C., Chakravorty, A.:
Blockchain-based prosumer incentivization for peak mitigation through
temporal aggregation and contextual clustering. Blockchain: Research and
Applications. 2, 100016 (2021). https://doi.org/10.1016/j.bcra.2021.100016 15. Saurabh, N., Rubia, C., Palanisamy, A., Koulouzis,
S., Sefidanoski, M., Chakravorty, A., Zhao, Z., Karadimce, A., Prodan,
R.: The ARTICONF Approach to Decentralized Car-Sharing. Blockchain: Research
and Applications. 100013 (2021). https://doi.org/10.1016/j.bcra.2021.100013.
16. Zhou, H., Shi, Z., Ouyang, X. Zhao, Z.,
Building a blockchain-based decentralized ecosystem for cloud and edge computing:
an ALLSTAR approach and empirical study. Peer-to-Peer Network Application.
(2021). https://doi.org/10.1007/s12083-021-01198-z
[OA] 17. Calyam, P., Wilkins-Diehr, N., Miller, M., Brookes,
E.H., Arora, R., Chourasia, A., Jennewein, D.M., Nandigam, V., Drew LaMar,
M., Cleveland, S.B., Newman, G., Wang, S., Zaslavsky, I., Cianfrocco, M.A.,
Ellett, K., Tarboton, D., Jeffery, K.G., Zhao, Z., González - Aranda,
J., Perri, M.J., Tucker, G., Candela, L., Kiss, T., Gesing, S.: Measuring
success for a future vision: Defining impact in science gateways/virtual
research environments. Concurrency Computat Pract Exper. cpe.6099 (2020). https://doi.org/10.1002/cpe.6099. 18. Zhu, Z., Chen, B., Liu, W., Zhao, Y., Liu, Z., and Zhao Z., A Cost-Quality Beneficial
Cell Selection Approach for Sparse Mobile Crowdsensing With Diverse Sensing
Costs, in IEEE Internet of Things Journal, vol. 8, no. 5, pp.
3831-3850, 1 March1, 2021, https://doi.org/10.1109/JIOT.2020.3024833.[OA]. 19. Zhang, L., Jiang, W., Zhao, Z.: Short -text
feature expansion and classification based on nonnegative matrix
factorization. Int Journal of Intelligent Systems. int.22290 (2020)https://doi.org/10.1002/int.22290[OA]. 20. Uriarte, R.B., Zhou, H., Kritikos, K., Shi, Z., Zhao, Z., De Nicola, R.: Distributed
service- level agreement management with smart contracts and blockchain.
Concurrency Computat Pract Exper. (2020). https://doi.org/10.1002/cpe.5800. 21. Hu, Y., de Laat, C., Zhao, Z.: Optimizing Service Placement for Microservice
Architecture in Clouds. Applied Sciences. 9, 4663 (2019). https://doi.org/10.3390/app9214663. 22. Hu, Y., Zhou, H., de Laat, C., Zhao, Z.: Concurrent container scheduling on heterogeneous clusters
with multi-resource constraints. Future Generation Computer Systems. 102,
562–573 (2020). https://doi.org/10.1016/j.future.2019.08.025. 23. Remy, L., Ivanovic, D., Theodoridou, M., Kritsotaki,
A., Martin, P., Bailo, D., Sbarra, M., Zhao,
Z., Jeffery, K.: Building an Integrated Enhanced Virtual Research
Environment Metadata Catalogue. The Electronic Library. (2019) https://doi.org/10.1108/EL-09-2018-0183
[OA]. 24. Zhou, H., Hu, Y., Ouyang, X., Su, J., Koulouzis, S.,
Laat, C., Zhao, Z.: CloudsStorm: A
framework for seamlessly programming and controlling virtual infrastructure
functions during the DevOps lifecycle of cloud applications. Softw: Pract
Exper. 49, 1421–1447 (2019). https://doi.org/10.1002/spe.2741. 25. Tanhua, T., Pouliquen, S., Hausman, J., O’Brien, K.,
Bricher, P., de Bruin, T., Buck, J.J.H., Burger, E.F., Carval, T., Casey,
K.S., Diggs, S., Giorgetti, A., Glaves, H., Harscoat, V., Kinkade, D.,
Muelbert, J.H., Novellino, A., Pfeil, B., Pulsifer, P.L., Van de Putte, A.,
Robinson, E., Schaap, D., Smirnov, A., Smith, N., Snowden, D., Spears, T.,
Stall, S., Tacoma, M., Thijsse, P., Tronstad, S., Vandenberghe, T., Wengren,
M., Wyborn, L., Zhao, Z.: Ocean
FAIR Data Services. Front. Mar. Sci. 6, 440 (2019). https://doi.org/10.3389/fmars.2019.00440. 26. Martin, P., Remy, L., Theodoridou, M., Jeffery, K., Zhao, Z.: Mapping heterogeneous
research infrastructure metadata into a unified catalogue for use in a
generic virtual research environment. Future Generation Computer Systems.
101, 1–13 (2019). https://doi.org/10.1016/j.future.2019.05.076.
[OA] 27. Zhou, H., Ouyang, X., Su, J., Laat, C., Zhao, Z.: Enforcing trustworthy cloud
SLA with witnesses: A game theory–based model using smart contracts.
Concurrency Computation: Practice Experience (2019). https://doi.org/10.1002/cpe.5511. 28. Taal, A., Wang, J., de Laat, C., Zhao, Z.: Profiling the scheduling
decisions for handling critical paths in deadline-constrained cloud
workflows. Future Generation Computer Systems. 100, 237–249 (2019). https://doi.org/10.1016/j.future.2019.05.002. 29. Štefanič, P., Cigale, M., Jones, A.C., Knight, L.,
Taylor, I., Istrate, C., Suciu, G., Ulisses, A., Stankovski, V., Taherizadeh,
S., Salado, G.F., Koulouzis, S., Martin, P., Zhao, Z.: SWITCH workbench: A novel approach for the development
and deployment of time-critical microservice-based cloud-native applications.
Future Generation Computer Systems. 99, 197–212 (2019). https://doi.org/10.1016/j.future.2019.04.008. 30. Liao, X., Zhao,
Z.: Unsupervised Approaches for Textual Semantic Annotation, A Survey.
ACM Comput. Surv. 52, 1–45 (2019). https://doi.org/10.1145/3324473. 31. Liao, X., Bottelier, J., Zhao, Z.: A Column Styled Composable Schema Matcher for Semantic
Data-Types. Data Science Journal. 18-25 (2019). https://doi.org/10.5334/dsj-2019-025. 32. Koulouzis, S., Martin, P., Zhou, H., Hu, Y., Wang,
J., Carval, T., Grenier, B., Heikkinen, J., Laat, C., Zhao, Z.: Time-critical data management in clouds: Challenges and
a Dynamic Real-Time Infrastructure Planner (DRIP) solution. Concurrency
Computat Pract Exper. e5269 (2019). https://doi.org/10.1002/cpe.5269. 33. Taherizadeh, S., Jones, A.C., Taylor, I., Zhao, Z., Stankovski, V.: Monitoring
self-adaptive applications within edge computing frameworks: A
state-of-the-art review. Journal of Systems and Software. 136, 19–38 (2018). https://doi.org/10.1016/j.jss.2017.10.033. 34. Li, J., Yang, Y., Wang, X., Zhao, Z., Li, T.: A novel parallel distance metric-based approach
for diversified ranking on large graphs. Future Generation Computer Systems.
88, 79–91 (2018). https://doi.org/10.1016/j.future.2018.05.031. 35. Jiang, W., Zhai, Y., Zhuang, Z., Martin, P., Zhao, Z., Liu, J.-B.: Vertex
Labelling and Routing for Farey-Type Symmetrically-Structured Graphs.
Symmetry. 10, 407 (2018). https://doi.org/10.3390/sym10090407. 36. Jiang, W., Zhai, Y., Zhuang, Z., Martin, P., Zhao, Z., Liu, J.-B.: An Efficient
Method of Generating Deterministic Small-World and Scale-Free Graphs for
Simulating Real-World Networks. IEEE Access. 6, 59833–59842 (2018). https://doi.org/10.1109/ACCESS.2018.2875928. 37. Jiang, W., Zhai, Y., Martin, P., Zhao, Z.: Structure Properties of
Generalized Farey graphs based on Dynamical Systems for Networks. Sci Rep. 8,
12194 (2018). https://doi.org/10.1038/s41598-018-30712-2. 38. Wang, J., Taal, A., Martin, P., Hu, Y., Zhou, H.,
Pang, J., de Laat, C., Zhao, Z.:
Planning virtual infrastructures for time critical applications with multiple
deadline constraints. Future Generation Computer Systems. 75, 365–375 (2017).
https://doi.org/10.1016/j.future.2017.02.001,
[Zenodo]. 39. Koulouzis, S., Belloum, A.S.Z., Bubak, M.T., Zhao, Z., Živković, M., de Laat, C.T.A.M.:
SDN-aware federation of distributed data. Future Generation Computer Systems.
56, 64–76 (2016). https://doi.org/10.1016/j.future.2015.09.032. 40. Zhu, H., van der Veldt, K., Zhao, Z., Grosso, P., Pavlov, D., Soeurt, J., Liao, X., de Laat,
C.: A semantic enhanced Power Budget Calculator for distributed computing
using IEEE 802.3az. Cluster Comput. 18, 61–77 (2015). https://doi.org/10.1007/s10586-014-0395-7. 41. Ghijsen, M., van der Ham, J., Grosso, P., Dumitru,
C., Zhu, H., Zhao, Z., de Laat,
C.: A semantic-web approach for modelling computing infrastructures.
Computers & Electrical Engineering. 39, 2553–2565 (2013). https://doi.org/10.1016/j.compeleceng.2013.08.011. 42. Zhao,
Z., Grosso, P., van der Ham,
J., Koning, R., de Laat, C.: An agent-based network resource planner for
workflow applications. MGS. 7, 187–202 (2011). https://doi.org/10.3233/MGS-2011-0180. 43. Belloum, A., Inda, M.A., Vasunin, D., Korkhov, V., Zhao, Z., Rauwerda, H., Breit,
T.M., Bubak, M., Hertzberger, L.O.: Collaborative e-Science Experiments and
Scientific Workflows. IEEE Internet Comput. 15, 39–47 (2011). https://doi.org/10.1109/MIC.2011.87. 44. Zhao,
Z., van Albada, D., Sloot, P.:
Agent-Based Flow Control for HLA Components. SIMULATION. 81, 487–501 (2005). https://doi.org/10.1177/0037549705058060. 45. Kommers, P. and Zhao, Z.: Conceptual
Support with Virtual Reality in Web-based Learning, International Journal
of Continuing Engineering Education and Life-Long Learning, vol. 8, nr 1
1998. ISSN 0957-4344 (1998). https://www.inderscienceonline.com/doi/abs/10.1504/IJCEELL.1998.030134. Editorial
(special issues and proceedings) 46. Wittenburg, P., Hardisty, A., Mozzafari,
A., Peer, L., Skvortsov, N., Spinuso, A., Zhao, Z.: Editors’ Note:
Special Issue on Canonical Workflow Frameworks for Research. Data
Intelligence. 4, 149–154 (2022). https://doi.org/10.1162/dint_e_00122. 47. Rong, C., Zhao, Z.: Welcome to the
new Journal of Cloud Computing by Springer. J Cloud Comp. 10, 49, s13677-021-00263–5
(2021). https://doi.org/10.1186/s13677-021-00263-5.
48. Zhao, Z., Taylor, I., Prodan, R.: Editorial for
FGCS Special issue on “Time-critical Applications on Software-defined
Infrastructures.” Future Generation Computer Systems. 112, 1170–1171 (2020). https://doi.org/10.1016/j.future.2020.07.056.[OA] [Content]
49. Zhao, Z., Altmeyer, S., Keith J., Atkinson,
M. and Ulisses A.: Nearly
real time data processing and time critical cloud applications. Proceedings
of the 2nd International workshop
on Interoperable infrastructures for interdisciplinary big data sciences
(IT4RIs 16), in the context of IEEE Real-time System Symposium (RTSS), Porto,
Portugal, November 29-December 2, (2016). [doi:10.5281/zenodo.204685] 50. Lu, S., Deelman, E. & Zhao,
Z.: Scientific workflows
special issue. International journal of business process integration
and management (pp. 1-2). Inder science Enterprises Ltd. (2010). [Full text] 51. Zhao, Z., Belloum, A.,
Bubak, M.: Special section on workflow systems and applications in e-Science.
Future Generation Computer Systems. 25, 525–527 (2009). https://doi.org/10.1016/j.future.2008.10.011. 52. Belloum, A., Deelman, E. & Zhao,
Z.: Scientific workflows.
Scientific Programming, 14(3-4), 171-171 (2006). [Full text] Book
(Eds) 53. Zhao, Z., Hellström, M. eds: Towards
Interoperable Research Infrastructures for Environmental and Earth Sciences:
A Reference Model Guided Approach for Common Challenges. Springer
International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4.
[ENVRI archive][Book interview] Book
chapters 54. Jeffery, K., Pursula, A., Zhao, Z.: ICT Infrastructures for Environmental and Earth
Sciences. In: Zhao, Z. and
Hellström, M. (eds.) Towards Interoperable Research Infrastructures for
Environmental and Earth Sciences. pp. 17–29. Springer International
Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_2. 55. Magagna, B., Martin, P., de la Hidalga, A.N.,
Atkinson, M., Zhao, Z.: Common
Challenges and Requirements. In: Zhao,
Z. and Hellström, M. (eds.) Towards Interoperable Research
Infrastructures for Environmental and Earth Sciences. pp. 30–57. Springer
International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_3. 56. de la Hidalga, A.N., Hardisty, A., Martin, P.,
Magagna, B., Zhao, Z.: The ENVRI
Reference Model. In: Zhao, Z. and
Hellström, M. (eds.) Towards Interoperable Research Infrastructures for
Environmental and Earth Sciences. pp. 61–81. Springer International
Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_4. 57. Zhao, Z., Jeffery, K.: Reference
Model Guided Engineering. In: Zhao, Z. and Hellström, M. (eds.) Towards
Interoperable Research Infrastructures for Environmental and Earth Sciences.
pp. 82–99. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_5. 58. Martin, P., Liao, X., Magagna, B., Stocker, M., Zhao, Z.: Semantic and Knowledge
Engineering Using ENVRI RM. In: Zhao,
Z. and Hellström, M. (eds.) Towards Interoperable Research
Infrastructures for Environmental and Earth Sciences. pp. 100–119. Springer
International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_6. 59. Quimbert, E., Jeffery, K., Martens, C., Martin, P., Zhao, Z.: Data Cataloguing. In: Zhao, Z. and Hellström, M. (eds.)
Towards Interoperable Research Infrastructures for Environmental and Earth
Sciences. pp. 140–161. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_8. 60. Koulouzis, S., Martin, P., Zhao, Z.: Virtual Infrastructure Optimisation. In: Zhao, Z. and Hellström, M. (eds.)
Towards Interoperable Research Infrastructures for Environmental and Earth
Sciences. pp. 192–207. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_11. 61. Magagna, B., Goldfarb, D., Martin, P., Atkinson, M.,
Koulouzis, S., Zhao, Z.: Data
Provenance. In: Zhao, Z. and Hellström,
M. (eds.) Towards Interoperable Research Infrastructures for Environmental
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Atkinson, M., Petzold, A.: Towards Operational Research Infrastructures with
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Z.: Computational
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developments and Perspectives (2017). [ISBN 9781498751315] [OA]. 66. Zhao, Z., Grosso, P., Ham, J. van der, Koning, R.
& de Laat, C.: Quality guaranteed media delivery over
advanced network. Chapter in book Next Generation Content Delivery
Infrastructure: Emerging Paradigms and Technologies, IGI, (2012). ISBN
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X., Zhou, H.: The Extreme Counts: Modeling the Performance Uncertainty of
Cloud Resources with Extreme Value Theory. In: Troya, J., Medjahed, B.,
Piattini, M., Yao, L., Fernández, P., and Ruiz-Cortés, A. (eds.)
Service-Oriented Computing. pp. 498–512. Springer Nature Switzerland, Cham
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Mosquera-Zamudio, A., Moscardó, A., Monteagudo, C., Zhao, Z., Naranjo,
V.: Federating Unlabeled Samples: A Semi-supervised Collaborative Framework
for Whole Slide Image Analysis. In: Yin, H., Camacho, D., and Tino, P. (eds.)
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69. Ivankovic, V., Shi, Z., Zhao, Z.: A
Customizable dApp Framework for User Interactions in Decentralized Service
Marketplaces. In: 2022 IEEE International Conference on Smart Internet of
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Multi-Objective Robust Workflow Offloading in Edge-to-Cloud Continuum. In:
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Adaptable Framework for Entity Matching Model Selection in Business
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90–99. IEEE, Amsterdam, Netherlands (2022). https://doi.org/10.1109/CBI54897.2022.00017 [OA] 72. Farshidi, S., Zhao, Z.: An Adaptable Indexing
Pipeline for Enriching Meta Information of Datasets from Heterogeneous
Repositories. In: Gama, J., Li, T., Yu, Y., Chen, E., Zheng, Y., and Teng, F.
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[OA]. 73. Hoogenkamp, B., Farshidi, S., Xin, R., Shi, Z.,
Chen, P., Zhao, Z.: A Decentralized Service Control Framework for
Decentralized Applications in Cloud Environments. In: Montesi, F.,
Papadopoulos, G.A., and Zimmermann, W. (eds.) Service-Oriented and Cloud
Computing. pp. 65–73. Springer International Publishing, Cham (2022). [https://doi.org/10.1007/978-3-031-04718-3_4][OA] 74. Bergers, J., Shi, Z., Korsmit, K., Zhao, Z.:
DWH-DIM: A Blockchain Based Decentralized Integrity Verification Model for
Data Warehouses. In: 2021 IEEE International Conference on Blockchain (Blockchain).
pp. 221–228. IEEE, Melbourne, Australia (2021). https://doi.org/10.1109/Blockchain53845.2021.00037
[OA] 75. Poon, L., Farshidi, S., Li, N., Zhao, Z.:
Unsupervised Anomaly Detection in Data Quality Control. In: 2021 IEEE
International Conference on Big Data (Big Data). pp. 2327–2336. IEEE,
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Meta-Reinforcement Learning-Based Scheduling Framework for Time Critical
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[OA](Best student paper) 77. Shi Ze., Farshidi S., Zhou H., Zhao Z., An
Auction and Witness Enhanced Trustworthy SLA Model for Decentralized Cloud Marketplaces, The
2021 ACM International Conference on Information Technology for Social Good
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[OA] 78. Xin R., Mohazzab J., Shi Z., and Zhao Z.:
CBProf: Customisable Blockchain-as-a-service Performance Profiler in Cloud
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Y., Zhao, Z.: SPIRIT: A Microservice-Based Framework for Interactive
Cloud Infrastructure Planning. In: Chaves, R., B. Heras, D., Ilic, A., Unat,
D., Badia, R.M., Bracciali, A., Diehl, P., Dubey, A., Sangyoon, O., L. Scott,
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[OA]. 80. Kruijer W., Wang Y., Koulouzis S., Li N., Bianchi
R., Zhao, Z.: FAIR-Cells: an interactive tool for enabling the
FAIRness of code fragments in Jupyter notebooks, in the proceedings of
international conference of High-Performance Computing and Simulation (HPCS)
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Zhao, Z., Rong, C., Jaatun, M.G.: A
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Cloud. In: 2020 IEEE 26th International Conference on Parallel and
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Z.: Decentralized workflow management on software defined infrastructure,
Workshop on The 1st Workshop On Data-Centric Workflows On Heterogeneous
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across data infrastructures using Named Data Networking (NDN). 2nd
workshop on Network Aware Big Data Computing (NEAC), In: 2020 20th IEEE/ACM
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[OA]. 84. Zhou, H., Ouyang, X., Zhao, Z.: ALLSTAR: A Blockchain Based Decentralized Ecosystem for
Cloud and Edge Computing. In: 2020 IEEE International Conference on Joint
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C., Zhao, Z.: An Automated
Customization and Performance Profiling Framework for Permissioned
Blockchains in a Virtualized Environment. In: 2019 IEEE International
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[OA]. 86. Petzold, A., Asmi, A., Vermeulen, A., Pappalardo,
G., Bailo, D., Schaap, D., Glaves, H.M., Bundke, U., Zhao, Z.: ENVRI-FAIR - Interoperable Environmental FAIR Data and
Services for Society, Innovation and Research. In: 2019 15th International
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[OA]. 88. Demchenko, Y., Zhao,
Z., Surbiryala, J., Koulouzis, S., Shi, Z., Liao, X., Gordiyenko, J.:
Teaching DevOps and Cloud Based Software Engineering in University Curricula.
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Workflow Provenance and System Performance Logs. In: 2019 15th International
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[OA]. 90. Prodan, R., Saurabh, N., Zhao, Z.,
Orton-Johnson, K., Chakravorty, A., Karadimce, A., and Ulisses, A.: ARTICONF:
Towards a Smart Social Media Ecosystem in a Blockchain Federated Environment,
in the 7th Workshop on Large Scale Distributed Virtual Environments, in the
context of Euro-Par conference 2019, Gottingen, Germany (2019) https://doi.org/10.1007/978-3-030-48340-1_32
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Orchestrated Network Fabric (CONF): An Automated Cloud Virtual Infrastructure
for Social Network Applications. in the 7th Workshop on Large Scale
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[OA] (Best student paper candidate). 93. Zhao,
Z., Liao, X., Martin, P.,
Maduro, J., Thijsse, P., Schaap, D., Stocker, M., Goldfarb, D., Magagna, B.:
Knowledge-as-a-Service: A Community Knowledge Base for Research
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system logs: a context aware information integration and exploration
framework for analyzing workflow execution. 10th International Workshop on
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[OA] Best presentation in the session. 97. Shi, Z., Zhou, H., Hu, Y., Jayachander, S., de Laat,
C., Zhao, Z.: Operating Permissioned
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18th International Symposium on Parallel and Distributed Computing (ISPDC).
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and Grid Computing (CCGRID). pp. 592–599. IEEE, Larnaca, Cyprus (2019). https://doi.org/10.1109/CCGRID.2019.00076,
[OA] Best paper award. 99. Zhou, H., Koulouzis, S., Hu, Y., Wang, J., de Laat,
C., Ulisses, A., Zhao, Z.:
Migrating Live Streaming Applications onto Clouds: Challenges and a
CloudStorm Solution. In: 2018 IEEE/ACM International Conference on Utility
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Zhou,
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Hu,
Y., Zhou, H., de Laat, C., Zhao, Z.: ECSched:
Efficient Container Scheduling on Heterogeneous Clusters. In: Aldinucci, M.,
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Qin,
Y., Chi, M., Liu, X., Zhang, Y., Zeng, Y., Zhao, Z.: Classification of High Resolution Urban Remote Sensing
Images Using Deep Networks by Integration of Social Media Photos. In: IGARSS
2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. pp.
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Zhou,
H., Hu, Y., Su, J., Chi, M., de Laat, C., Zhao, Z.: Empowering Dynamic Task-Based Applications with Agile
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Zhou,
H., Hu, Y., Su, J., de Laat, C., Zhao,
Z.: CloudsStorm: An Application-Driven Framework to Enhance the
Programmability and Controllability of Cloud Virtual Infrastructures. In:
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Martin,
P., Remy, L., Theodoridou, M., Jeffery, K., Zhao, Z.: Mapping metadata
from different research infrastructures into a unified framework for use in a
virtual research environment. 10th International Workshop on Science Gateways
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Zhou,
H., Taal, A., Koulouzis, S., Wang, J., Hu, Y., Suciu, G., Poenaru, V., de Laat,
C., Zhao, Z.: Dynamic Real-Time
Infrastructure Planning and Deployment for Disaster Early Warning Systems.
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Koulouzis,
S., Mousa, R., Karakannas, A., de Laat, C., Zhao, Z.: Information Centric Networking for Sharing and
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Zhou,
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Zhao, Z., Martin, P., Jones, A., Taylor, I., Stankovski, V.,
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Wang,
J., Zhou, H., Hu, Y., De Laat, C., Zhao, Z.: Deadline-Aware Coflow
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Wang,
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Taherizadeh,
S., Taylor, I., Jones, A., Zhao, Z., Stankovski, V.: A Network Edge
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S., Martin, P., Carval, T., Grenier, B., Judeau, G., Heikkinen, J., Wang, J.,
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Hu,
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Elzinga,
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Zhou,
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Petcu,
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Jeferry,
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Update date: November 21, 2022