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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 20
5257599 Office: C.3.145 Science park 904, 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. ENVRI-FAIR
FAIRness workshops |
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I am an assistant professor
and senior researcher at University of Amsterdam (UvA).
I lead a team on “Quality Critical Distributed Computing” in the context of
Multiscale Networked Systems (MNS) research group, the
System and Networking Lab (SNE). 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 agreement. Since 2014, I obtained more
than 3M euro funding from the EU H2020 research program to support my
research activities in UvA. I am the
scientific coordinator of the project SWITCH (Software
Workbench for interactive time critical and highly self-adaptive cloud
applications). I am the leader of the Data for Science theme
in the environmental science cluster project ENVRIPLUS and
lead 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 was involved in a number of other projects, such
as the EU FP7 ENVRI project.
I also lead the Virtual Research Environment (VRE) development in the LifeWatch Virtual Lab & Innovation Center. |
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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 modelling, 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: ·
Mr. Uraz Odyurt, AI and cloud computing (2021-) ·
Dr.
Peng Chen, Cloud infrastructure optimization (2020-) ·
Mr. Riccardo
Bianchi (M.Sc), DevOps
(2020-) ·
Dr. Siamak Farshidi, Knowledge base
and data set search (2020-) ·
Dr. Xiaofeng Liao,
Alignment, annotation (2017-2020) ·
Dr. Spiros Koulouzis,
DRIP, CONF, VRE and use cases (2017-) ·
Dr. Paul Martin, Semantic information
linking (2015-2018) ·
Dr. Arie Taal, Time critical
applications (2016-2019) 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-) ·
Zeshun Shi, Trustworthy Virtual
infrastructure (2018-) ·
Junchao Wang, Virtual Infrastructure
planning (2015-) ·
Hu Yang, Time critical application deployment
(2015-2019) [thesis] ·
Huan Zhou, Virtual infrastructure provisioning
and DevOps (2015-2019)[thesis] Student projects: ·
Robin van der Linde (2019) Infrastructure
planner[] ·
Wilco Kruijer (2019)
FAIR-Cells: an interactive tool for enabling the FAIRness
of code fragments in Jupyter notebooks [] ·
Cas Fahrenfort (2019)
Enabling the data FAIRness of version control
systems, Master thesis [10.5281/zenodo.3583010] ·
Rasha Daoud (2019) Towards sustainable service
portfolios: a self-learning solution for service portfolio Management, Master
thesis [10.5281/zenodo.3521558] ·
Pieter Donkers (2019)
MYST: Automated DevOps for distributed applications across heterogeneous
Cloud, Fog and Edge infrastructures. Master thesis [10.5281/zenodo.3521562] ·
Kees de Jong & Anas Younis (2019)
Planning and Scaling a Named Data Network with Persistent Identi ·
Elias el Khaldi Ahanach (2019) CWEA: Automated log retrieval for
performance analysis of service-oriented scienti ·
Jordy Bottelier,
Master thesis, Semi-Automatic schema matching: challenges and
a composable match-based solution, 2018, [doi:10.5281/zenodo.1419496]. ·
Jordan Maduro, Master thesis, Towards a taxonomy
for quality control in environmental sciences, 2018, [doi:10.5281/zenodo.1419494]. ·
Ewoud Bouman Bachelor
thesis, Characterizing access patterns from ftp logs: a case study on
Euro-Argo research infrastructure, 2018, [doi:10.5281/zenodo.1419490]. ·
Rahaf Mousa, RP, Application aware digital
object distribution using ICN, 2017, [doi:10.5281/zenodo.889740] ·
Carlos Acosta, Master thesis, Reference
model based smart architecture design, 2017 [doi:10.5281/zenodo.889748] ·
Olaf Elzinga, RP, Dynamic
cloud performance information, 2017 [doi:10.1109/NAS.2017.8026845] ·
Ryan Mork, PIRE,
Big data-oriented workflow, 2015 [doi:10.1145/2822332.2822336] ·
Fatemeh Abyarjoo, PIRE*,
Architecture for Cloud IoT, 2014 ·
Andreas Karakannas, RP,
Information Centric Networking and PID, 2014 [doi:10.5281/zenodo.889603] ·
Stavros Konstantaras, RP,
SDN for big data science, 2014 [doi:10.5281/zenodo.889699] ·
Ioannis Grafis, RP,
SDN for big data science, 2014[doi:10.5281/zenodo.889699] ·
Wenchao Jiang, Postdoctor/Guest,
SDN and NSI, 2013 [doi:10.1109/NAS.2013.53] ·
Dimitar Pavlov, RP, Energy
efficient cluster computing, 2012 [doi:10.5281/zenodo.889752] ·
Joris Soeurt, RP**,
Energy efficient cluster computing, 2012[doi:10.5281/zenodo.889752] ·
Dimitry Prapas, Master
thesis, JADE in Grid workflow, 2009 ·
Suresh Booms, Master thesis***, Agent
architecture for workflow interoperability, 2006 *PIRE: The
Open Science Data Cloud (OSDC) NSF-sponsored Partnerships for International
Research and Education (PIRE) program: http://pire.opensciencedatacloud.org/ **RP:
SNE OS3 master program, research project: http://www.delaat.net/rp ***
Master program, typically 3 month duration |
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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. [Newsletter
in IvI] 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 ARTICONF (smART socIal media eCOsytstem in a blockchaiN Federated
environment). Grant No 825134. H2020-ICT-2018-2 call. Duration: January
2019-December 2021 [Newsletter in IvI]. 4.
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 [Newsletter in IvI]. Finished projects 1.
EU H2020 ENVRIPLUS (ENVironmental Research Infrastructures Providing
shared soLUtions for Science
and society). Leader of the Data for Science Theme. Grant No. 654182 (News
letter in IvI, ENVRIPLUS, EGI). Duration: May 2015- April 2019, Project
website: www.envriplus.eu. 2.
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. (Newsletter in IvI) 3. 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. (Newsletter in IvI)
(SWITCH
project). Participated
projects 1.
EU FP7 ENVRI.
Task leader, task 3.4: linking data and infrastructure - Common operations of
Environmental Research Infrastructure (ENVRI). Grant number 283465. 2.
EU FP7 Geysers, Researcher Generalised Architecture for Dynamic
Infrastructure Services 3.
Gigaport/CineGrid,
Researcher. Including network QoS in planning Workflows. 4.
Dutch Virtual
Laboratory for e-Science (VL-e), 2005-2009 5.
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.
International journal of: Blockchains:
research and applications 2.
Journal of Circuits,
Systems and Computers Workshop
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
| 2019
| 2020) Workshop/Panel
chair
Program
committee
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Recent
activities and
agenda |
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Journals 1.
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.
2.
Nikita Karandikar, Rockey
Abhishek, Nishant Saurabh, Zhiming Zhao, Alexander Lercher,
Ninoslav Marina, Radu Prodan, Chunming
Rong, Antorweep Chakravorty,
Blockchain-based prosumer incentivization for peak mitigation through
temporal aggregation and contextual clustering, Journal of Blockchain:
Research and Applications (2021). https://doi.org/10.1016/j.bcra.2021.100016
3.
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.
4.
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
5.
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. 6.
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, doi:
10.1109/JIOT.2020.3024833.[Zenodo]. 7.
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[Zenodo]. 8.
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. 9.
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. 10. 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. 11. 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://zenodo.org/record/3497056.
12. 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. 13. 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. 14. 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.
[Zenodo] 15. 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 Computat Pract Exper. (2019). https://doi.org/10.1002/cpe.5511. 16. 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. 17. 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. 18. 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. 19. 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. 20. 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. 21. 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. 22. 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. 23. Jiang, W., Zhai, Y., Zhuang, Z., Martin, P., Zhao, Z., Liu, J.-B.: Vertex Labeling
and Routing for Farey-Type Symmetrically-Structured
Graphs. Symmetry. 10, 407 (2018). https://doi.org/10.3390/sym10090407. 24. 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. 25. 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. 26. 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]. 27. 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. 28. 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. 29. Ghijsen, M., van der Ham, J.,
Grosso, P., Dumitru, C., Zhu, H., Zhao,
Z., de Laat, C.: A semantic-web approach for modeling
computing infrastructures. Computers & Electrical Engineering. 39,
2553–2565 (2013). https://doi.org/10.1016/j.compeleceng.2013.08.011. 30. 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. 31. 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. 32. 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. 33. 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) 34. 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.
35. 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.[Zenodo] [Content] 36. 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] 37. 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] 38. 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. 39. Belloum, A., Deelman,
E. & Zhao, Z.: Scientific
workflows. Scientific Programming, 14(3-4), 171-171 (2006). [Full text] Book
(Eds) 40. 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 41.
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. 42.
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. 43.
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. 44.
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. 45.
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. 46.
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. 47.
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. 48.
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
and Earth Sciences. pp. 208–225. Springer International Publishing, Cham
(2020). https://doi.org/10.1007/978-3-030-52829-4_12. 49.
Martin, P., Magagna,
B., Liao, X., Zhao, Z.: Semantic
Linking of Research Infrastructure Metadata. In: Zhao, Z. and Hellström, M. (eds.)
Towards Interoperable Research Infrastructures for Environmental and Earth
Sciences. pp. 226–246. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_13. 50.
Koulouzis,
S., Carval, T., Heikkinen, J., Pursula, A., Zhao, Z.: Case Study: Data
Subscriptions Using Elastic Cloud Services. In: Zhao, Z. and Hellström, M. (eds.)
Towards Interoperable Research Infrastructures for Environmental and Earth
Sciences. pp. 293–306. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_16. 51.
Zhao,
Z., Jeffery, K., Stocker, M., Atkinson, M., Petzold, A.: Towards Operational Research Infrastructures
with FAIR Data and Services. In: Zhao,
Z. and Hellström, M. (eds.) Towards
Interoperable Research Infrastructures for Environmental and Earth Sciences.
pp. 360–372. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_20. 52. Martin, P., Chen, Y. Hardisty, A.,
Jeffery, K., and Zhao, Z.: Computational Challenges in Global
Environmental Research Infrastructures. in the book of
Terrestrial Ecosystem Research Infrastructures: Challenges, New developments and Perspectives (2017). [ISBN 9781498751315] [Zenodo]. 53. 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 978-1-4666-1794-0 [doi: 10.4018/978-1-4666-1794-0.ch006]. Conferences 54. Liu H., Chen P., Zhao, Z.,:
Towards A Robust Meta-Reinforcement Learning-Based Scheduling Framework for Time
Critical Tasks in Cloud Environments, IEEE Cloud (2021), Online, [10.1109/CLOUD53861.2021.00082]
[Zenodo](Best
student paper) 55. 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 (GoodIT 2021), Rome Italy [https://doi.org/10.1145/3462203.3475876]
[Zenodo] 56. Xin R., Mohazzab J., Shi Z., and Zhao Z.: CBProf: Customisable
Blockchain-as-a-service Performance Profiler in Cloud Environments,
International Conf. on Blockchain (2021), Online [Zenodo] 57. Spiros Koulouzis,
Riccardo Bianchi, Robin van der Linde, Yuandou Wang
and Zhiming Zhao, SPIRIT: A microservice-based framework for
interactive Cloud infrastructure planning, Euro-Par 2021 Workshops (2021),
Online [Zenodo]. 58. 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) (2020), Spain. [Zenodo] 59.
Zhao, Z., Rong, C., Jaatun, M.G.: A Trustworthy Blockchain-based
Decentralised Resource Management System in the Cloud. In: 2020 IEEE 26th
International Conference on Parallel and Distributed Systems (ICPADS). pp.
617–624. IEEE, Hong Kong (2020). https://doi.org/10.1109/ICPADS51040.2020.00086
[Zendo]. 60. Wang, Y., Zhao, Z.: Decentralized workflow management on software defined
infrastructure, Workshop on The 1st Workshop On Data-Centric Workflows On
Heterogeneous Infrastructures: Challenges And Directions (DAWHI), in the
context of IEEE Service Congress, (2020), [https://doi.org/10.1109/SERVICES48979.2020.00059][Zenodo]. 61. de Jong, K., Fahrenfort,
C., Younis, A., Zhao, Z.: Sharing
digital object across data infrastructures using Named Data Networking (NDN).
2nd workshop on Network Aware Big Data Computing (NEAC), In: 2020
20th IEEE/ACM International Symposium on Cluster, Cloud and Internet
Computing (CCGRID). pp. 873–880. IEEE, Melbourne, Australia (2020). https://doi.org/10.1109/CCGrid49817.2020.00013.
[Zenodo]. 62. Zhou, H., Ouyang, X., Zhao, Z.: ALLSTAR: A Blockchain Based
Decentralized Ecosystem for Cloud and Edge Computing. In: 2020 IEEE
International Conference on Joint Cloud Computing. pp. 55–62. IEEE, Oxford,
United Kingdom (2020). https://doi.org/10.1109/JCC49151.2020.00018
[Zendo]. 63. Shi, Z., Zhou, H., Surbiryala,
J., Hu, Y., de Laat, C., Zhao, Z.:
An Automated Customization and Performance Profiling Framework for
Permissioned Blockchains in a Virtualized Environment. In: 2019 IEEE
International Conference on Cloud Computing Technology and Science (CloudCom). pp. 404–410. IEEE, Sydney, Australia (2019). https://doi.org/10.1109/CloudCom.2019.00069,
[Zenodo]. 64. 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 Conference on
eScience (eScience). pp. 277–280. IEEE, San Diego, CA, USA (2019). https://doi.org/10.1109/eScience.2019.00038,
[Zenodo]. 65. Fahrenfort, C., Zhao, Z.: Effective Digital Object Access and Sharing Over a
Networked Environment using DOIP and NDN. In: 2019 15th International
Conference on eScience (eScience). pp. 632–633. IEEE, San Diego, CA, USA
(2019). https://doi.org/10.1109/eScience.2019.00092,
[Zenodo]. 66. Demchenko, Y., Zhao, Z., Surbiryala, J., Koulouzis, S., Shi, Z., Liao, X., Gordiyenko,
J.: Teaching DevOps and Cloud Based Software Engineering in University
Curricula. In: 2019 15th International Conference on eScience (eScience). pp.
548–552. IEEE, San Diego, CA, USA (2019). https://doi.org/10.1109/eScience.2019.00075,
[Zenodo]. 67. Ahanach, E. el K., Koulouzis,
S., Zhao, Z.: Contextual Linking
between Workflow Provenance and System Performance Logs. In: 2019 15th
International Conference on eScience (eScience). pp. 634–635. IEEE, San
Diego, CA, USA (2019). https://doi.org/10.1109/eScience.2019.00093,
[Zenodo]. 68. 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://zenodo.org/record/3580716.
69. Shi, Z., Zhou, H., Hu, Y., Koulouzis, S., Rubia, C., and Zhao, Z.: Co-located and Orchestrated Network Fabric (CONF): An
Automated Cloud Virtual Infrastructure for Social Network Applications. 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_36,
https://zenodo.org/record/3679385.
70. Zhou, H., Shi, Z., Hu, Y., Donkers, P., Afanasyev, A., Koulouzis, S., Taal, A., Ulisses,
A., Zhao, Z.: Large Distributed
Virtual Infrastructure Partitioning and Provisioning Across Providers. In:
2019 IEEE International Conference on Smart Internet of Things (SmartIoT). pp. 56–63. IEEE, Tianjin, China (2019). https://doi.org/10.1109/SmartIoT.2019.00018,
[Zenodo]
(Best student paper candidate). 71. 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
Infrastructures in Environmental and Earth Sciences. In: 2019 IEEE World
Congress on Services (SERVICES). pp. 127–132. IEEE, Milan, Italy (2019). https://doi.org/10.1109/SERVICES.2019.00041,
[Zenodo]. 72. Hu, Y., de Laat, C., Zhao, Z.: Learning Workflow Scheduling on Multi-Resource
Clusters. In: 2019 IEEE International Conference on Networking, Architecture and
Storage (NAS). pp. 1–8. IEEE, EnShi, China (2019). https://doi.org/10.1109/NAS.2019.8834720,
[Zenodo]. 73. Ahanach, E. el K., Koulouzis,
S., Zhao, Z.: Linking provenance
with system logs: a context aware information integration and exploration
framework for analyzing workflow execution. 10th
International Workshop on Science Gateways (IWSG 2019), pp. 13-15 June 2019
(2019). [10.5281/zenodo.3466766] 74. Zhou, H., Ouyang, X., Ren, Z., Su, J., de Laat, C., Zhao,
Z.: A Blockchain based Witness Model for Trustworthy Cloud Service Level
Agreement Enforcement. In: IEEE INFOCOM 2019 - IEEE Conference on Computer
Communications. pp. 1567–1575. IEEE, Paris, France (2019). https://doi.org/10.1109/INFOCOM.2019.8737580,
[Zenodo]
Best presentation in the session. 75. Shi, Z., Zhou, H., Hu, Y., Jayachander, S., de Laat, C., Zhao, Z.: Operating Permissioned Blockchain in Clouds: A
Performance Study of Hyperledger Sawtooth. In: 2019 18th International
Symposium on Parallel and Distributed Computing (ISPDC). pp. 50–57. IEEE,
Amsterdam, Netherlands (2019). https://doi.org/10.1109/ISPDC.2019.00010,
[Zenodo]. 76. Hu, Y., De Laat, C., Zhao, Z.: Multi-objective Container Deployment on Heterogeneous
Clusters. In: 2019 19th IEEE/ACM International Symposium on Cluster, Cloud
and Grid Computing (CCGRID). pp. 592–599. IEEE, Larnaca,
Cyprus (2019). https://doi.org/10.1109/CCGRID.2019.00076,
[Zenodo]
Best paper award. 77. 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 and Cloud
Computing Companion (UCC Companion). pp. 321–326. IEEE, Zurich (2018). https://doi.org/10.1109/UCC-Companion.2018.00075,
[Zenodo]. 78. Zhou, H., de Laat, C., Zhao, Z.: Trustworthy Cloud Service
Level Agreement Enforcement with Blockchain Based Smart Contract. In: 2018
IEEE International Conference on Cloud Computing Technology and Science (CloudCom). pp. 255–260. IEEE, Nicosia (2018). https://doi.org/10.1109/CloudCom2018.2018.00057,
[Zenodo]. 79. Hu, Y., Zhou, H., de Laat, C., Zhao, Z.: ECSched:
Efficient Container Scheduling on Heterogeneous Clusters. In: Aldinucci, M., Padovani, L.,
and Torquati, M. (eds.) Euro-Par 2018: Parallel
Processing. pp. 365–377. Springer International Publishing, Cham (2018). https://doi.org/10.1007/978-3-319-96983-1_26. 80. 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. 7243–7246. IEEE, Valencia
(2018). https://doi.org/10.1109/IGARSS.2018.8518538. 81. Zhou, H., Hu, Y., Su,
J., Chi, M., de Laat, C., Zhao, Z.: Empowering
Dynamic Task-Based Applications with Agile Virtual Infrastructure
Programmability. In: 2018 IEEE 11th International Conference on Cloud
Computing (CLOUD). pp. 484–491. IEEE, San Francisco, CA, USA (2018). https://doi.org/10.1109/CLOUD.2018.00068. 82. 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:
Luo, M. and Zhang, L.-J. (eds.) Cloud Computing – CLOUD 2018. pp. 265–280.
Springer International Publishing, Cham (2018). https://doi.org/10.1007/978-3-319-94295-7_18. 83. 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 (IWSG 2018),
13-15 June 2018, (2018). [PDF] 84. 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. In: Shi, Y., Fu, H., Tian, Y., Krzhizhanovskaya,
V.V., Lees, M.H., Dongarra, J., and Sloot, P.M.A. (eds.) Computational Science – ICCS 2018.
pp. 644–654. Springer International Publishing, Cham (2018). https://doi.org/10.1007/978-3-319-93701-4_51. 85. Koulouzis, S., Mousa, R., Karakannas,
A., de Laat, C., Zhao, Z.:
Information Centric Networking for Sharing and Accessing Digital Objects with
Persistent Identifiers on Data Infrastructures. In: 2018 18th IEEE/ACM
International Symposium on Cluster, Cloud and Grid Computing (CCGRID). pp.
661–668. IEEE, Washington, DC, USA (2018). https://doi.org/10.1109/CCGRID.2018.00098. 86. Zhou, H., de Laat, C., Zhao, Z.: Cloudsstorm:
An Application-Driven Devops Framework For Managing Networked Infrastructures On Federated
Clouds. (2018). https://doi.org/10.5281/ZENODO.1162914. 87. Zhao, Z., Martin, P., Jones, A., Taylor, I., Stankovski, V., Salado, G.F., Suciu, G., Ulisses, A., de Laat, C.: Developing, Provisioning and
Controlling Time Critical Applications in Cloud. In: Mann, Z.Á. and Stolz, V.
(eds.) Advances in Service-Oriented and Cloud Computing. pp. 169–174.
Springer International Publishing, Cham (2018). https://doi.org/10.1007/978-3-319-79090-9_14. 88. Wang, J., Zhou, H., Hu, Y., De Laat, C., Zhao,
Z.: Deadline-Aware Coflow Scheduling in a DAG.
In: 2017 IEEE International Conference on Cloud Computing Technology and
Science (CloudCom). pp. 341–346. IEEE, Hong Kong
(2017). https://doi.org/10.1109/CloudCom.2017.55. 89. Wang, J., de Laat, C., Zhao, Z.: QoS-aware
virtual SDN network planning. In: 2017 IFIP/IEEE Symposium on Integrated
Network and Service Management (IM). pp. 644–647. IEEE, Lisbon, Portugal
(2017). https://doi.org/10.23919/INM.2017.7987350. 90. Taherizadeh, S., Taylor, I., Jones, A., Zhao, Z.,
Stankovski, V.: A Network Edge Monitoring
Approach for Real-Time Data Streaming Applications. In: Bañares,
J.Á., Tserpes, K., and Altmann, J. (eds.) Economics
of Grids, Clouds, Systems, and Services. pp. 293–303. Springer International
Publishing, Cham (2017). https://doi.org/10.1007/978-3-319-61920-0_21. 91. Koulouzis, S., Martin, P., Carval, T., Grenier, B., Judeau, G.,
Heikkinen, J., Wang, J., Zhou, H., Hu, Y., De Laat, C., Zhao, Z.: Seamless
Infrastructure Customisation and Performance Optimisation for Time-critical
Services in Data Infrastructures. (2017). https://doi.org/10.5281/ZENODO.1570919. 92. Hu, Y., Wang, J., Zhou, H., Martin, P.,
Taal, A., de Laat, C., Zhao, Z.: Deadline-Aware Deployment for Time
Critical Applications in Clouds. In: Rivera, F.F., Pena, T.F., and Cabaleiro, J.C. (eds.) Euro-Par 2017: Parallel
Processing. pp. 345–357. Springer International Publishing, Cham (2017). https://doi.org/10.1007/978-3-319-64203-1_25. 93. Elzinga, O., Koulouzis,
S., Taal, A., Wang, J., Hu, Y., Zhou, H., Martin, P., de Laat, C., Zhao,
Z.: Automatic Collector for Dynamic Cloud Performance Information. In:
2017 International Conference on Networking, Architecture, and Storage (NAS).
pp. 1–6. IEEE, Shenzhen, China (2017). https://doi.org/10.1109/NAS.2017.8026845. 94. Zhou, H., Wang, J., Hu, Y., Su, J., Martin, P., De Laat, C., Zhao, Z.: Fast
Resource Co-provisioning for Time Critical Applications Based on Networked
Infrastructures. In: 2016 IEEE 9th International Conference on Cloud
Computing (CLOUD). pp. 802–805. IEEE, San Francisco, CA, USA (2016). https://doi.org/10.1109/CLOUD.2016.0111. 95. Zhou, H., Martin, P., Su,
J., De Laat, C., Zhao, Z.: A Flexible Inter-Locale Virtual Cloud For Nearly Real-Time Big Data Applications. (2016). https://doi.org/10.5281/ZENODO.204774. 96. Zhou, H., Hu, Y., Wang, J., Martin, P.,
De Laat, C., Zhao, Z.: Fast and Dynamic Resource Provisioning for
Quality Critical Cloud Applications. In: 2016 IEEE 19th International
Symposium on Real-Time Distributed Computing (ISORC). pp. 92–99. IEEE, York,
United Kingdom (2016). https://doi.org/10.1109/ISORC.2016.22. 97. Zhao, Z., Martin, P., De Laat, C., Jeffery, K.,
Jones, A., Taylor, I., Hardisty, A., Atkinson, M., Zuiderwijk,
A., Yin, Y., Chen, Y.: Time Critical Requirements And
Technical Considerations For Advanced Support Environments For Data-Intensive
Research. (2016). https://doi.org/10.5281/ZENODO.204756. 98. Taherizadeh, S., Jones, A.C., Taylor, I., Zhao, Z.,
Martin, P., Stankovski, V.: Runtime Network-Level
Monitoring Framework. In The Adaptation Of
Distributed Time-Critical Cloud Applications. Zenodo
(2016). https://doi.org/10.5281/ZENODO.53869. 99. Petcu, D., Fazio, M., Prodan, R., Zhao, Z., Rak,
M.: On the Next Generations of Infrastructure-as-a-Services: In: Proceedings
of the 6th International Conference on Cloud Computing and Services Science.
pp. 320–326. SCITEPRESS - Science and and
Technology Publications, Rome, Italy (2016). https://doi.org/10.5220/0005912503200326. 100.
Martin, P., Taal, A., Quevedo, F., Rogers, D.,
Evans, K., Jones, A., Stankovski, V., Taherizadeh, S., Trnkoczy, J.,
Suciu, G., Zhao, Z.: Information
Modelling and Semantic Linking for a Software Workbench for Interactive, Time
Critical and Self-Adaptive Cloud Applications. In: 2016 30th International
Conference on Advanced Information Networking and Applications Workshops
(WAINA). pp. 127–132. IEEE, Crans-Montana,
Switzerland (2016). https://doi.org/10.1109/WAINA.2016.38. 101.
Casale, G., Chesta,
C., Deussen, P., Di Nitto, E., Gouvas,
P., Koussouris, S., Stankovski,
V., Symeonidis, A., Vlassiou,
V., Zafeiropoulos, A., Zhao, Z.: Current and Future Challenges of Software Engineering
for Services and Applications. Procedia Computer Science. 97, 34–42 (2016). https://doi.org/10.1016/j.procs.2016.08.278. 102.
Zhao, Z., Taal, A., Jones, A., Taylor, I., Stankovski, V., Vega, I.G., Hidalgo, F.J., Suciu, G., Ulisses, A., Ferreira, P., Laat, C. de: A Software
Workbench for Interactive, Time Critical and Highly Self-Adaptive Cloud
Applications (SWITCH). In: 2015 15th IEEE/ACM International Symposium on
Cluster, Cloud and Grid Computing. pp. 1181–1184. IEEE, Shenzhen, China
(2015). https://doi.org/10.1109/CCGrid.2015.73. 103.
Zhao, Z., Martin, P., Wang, J., Taal, A., Jones,
A., Taylor, I., Stankovski, V., Vega, I.G., Suciu,
G., Ulisses, A., de Laat, C.: Developing and
Operating Time Critical Applications in Clouds: The State of the Art and the
SWITCH Approach. Procedia Computer Science. 68, 17–28 (2015). https://doi.org/10.1016/j.procs.2015.09.220. 104.
Zhao, Z., Martin, P., Grosso, P., Los, W., Laat,
C. de, Jeffrey, K., Hardisty, A., Vermeulen, A., Castelli, D., Legre, Y., Kutsch, W.: Reference
Model Guided System Design and Implementation for Interoperable Environmental
Research Infrastructures. In: 2015 IEEE 11th International Conference on
e-Science. pp. 551–556. IEEE, Munich, Germany (2015). https://doi.org/10.1109/eScience.2015.41. 105.
Mork, R., Martin, P., Zhao, Z.: Contemporary challenges for data-intensive scientific
workflow management systems. In: Proceedings of the 10th Workshop on
Workflows in Support of Large-Scale Science - WORKS ’15. pp. 1–11. ACM Press,
Austin, Texas (2015). https://doi.org/10.1145/2822332.2822336. 106.
Martin, P., Grosso, P., Magagna,
B., Schentz, H., Chen, Y., Hardisty, A., Los, W.,
Jeffery, K., Laat, C. de, Zhao, Z.:
Open Information Linking for Environmental Research Infrastructures. In: 2015
IEEE 11th International Conference on e-Science. pp. 513–520. IEEE, Munich,
Germany (2015). https://doi.org/10.1109/eScience.2015.66. 107.
Jeferry, K., Kousiouris,
G., Kyriazis, D., Altmann, J., Ciuffoletti,
A., Maglogiannis, I., Nesi,
P., Suzic, B., Zhao,
Z.: Challenges Emerging from Future Cloud Application Scenarios. Procedia
Computer Science. 68, 227–237 (2015). https://doi.org/10.1016/j.procs.2015.09.238. 108.
Evans, K., Trnkoczy, J.,
Suciu, G., Suciu, V., Martin, P., Wang, J., Zhao, Z., Jones, A., Preece, A.,
Quevedo, F., Rogers, D., Spasić, I., Taylor, I., Stankovski, V., Taherizadeh,
S.: Dynamically reconfigurable workflows for time-critical applications. In:
Proceedings of the 10th Workshop on Workflows in Support of Large-Scale
Science - WORKS ’15. pp. 1–10. ACM Press, Austin, Texas (2015). https://doi.org/10.1145/2822332.2822339. 109.
Zhao, Z., Wibisono, A., Grosso, P., Los, W., De Laat,
C., Chen, Y., Hardisty, A., Martin, P., Atkinson, M., Schentz,
H., Magagna, B.: Oeilm: A
Semantic Linking Framework For Environmental
Research Infrastructures. (2013). https://doi.org/10.5281/ZENODO.205781. 110.
Jiang, W., Zhao,
Z., Wibisono, A., Grosso, P., Laat, C. de: Dynamic Workflow Planning on
Programmable Infrastructure. In: 2013 IEEE Eighth International Conference on
Networking, Architecture and Storage. pp. 326–330. IEEE, Xi’an, Shaanxi,
China (2013). https://doi.org/10.1109/NAS.2013.53. 111.
Jiang, W., Zhao,
Z., Laat, C. de: An Autonomous Security Storage Solution for
Data-Intensive Cooperative Cloud Computing. In: 2013 IEEE 9th International
Conference on e-Science. pp. 369–372. IEEE, Beijing, China (2013). https://doi.org/10.1109/eScience.2013.31. 112.
Chen, Y., Martin, P., Schentz,
H., Magagna, B., Zhao, Z., Hardisty,
A., Preece, A., Atkinson, M., Huber, R.,
and Legre. R.: A common reference model for environmental science research
infrastructures. In Proceedings of EnviroInfo2013, (2013). [Full text] 113.
Chen, Y., Hardisty, A., Preece, A., Atkinson, M., Martin, P., Zhao, Z., Schentz, H., Magagna,
B. and Legre. R., (2013) Analysis
of Common Requirements for Environmental Science Research
Infrastructures. In Proceedings of The International Symposium on
Grids and Clouds (ISGC). [Full text] 114.
Dumitru, C., Zhao,
Z., Grosso, P., de Laat, C.: HybridFlow:
Towards intelligent video delivery and processing over hybrid
infrastructures. In: 2013 International Conference on Collaboration
Technologies and Systems (CTS). pp. 473–478. IEEE, San Diego, CA, USA (2013).
https://doi.org/10.1109/CTS.2013.6567271. 115.
Zhu, H., van der Veldt, K., Grosso, P., Zhao,
Z., Liao, X., and de Laat, C.: Energy aware Semantic modelling in large scale infrastructure,
International conference on Green Com, France, (2012) [Fulltext]. 116.
Belloum, A.S.Z., Cushing, R., Koulouzis, S., Korkhov, V., Vasunin, D., Guevara-Masis, V.,
Zhao, Z., Bubak,
M.: Support for Cooperative Experiments in e-Science: From Scientific
Workflows to Knowledge Sharing. In: Roterman-Konieczna,
I. (ed.) Identification of Ligand Binding Site and Protein-Protein
Interaction Area. pp. 135–159. Springer Netherlands, Dordrecht (2013). https://doi.org/10.1007/978-94-007-5285-6_7. 117.
Zhao, Z., Ham, J. van der, Taal, A., Koning, R.,
Dumitru, C., Wibisono, A., Grosso, P., Laat, C. de: Planning Data Intensive
Workflows on Inter-domain Resources Using the Network Service Interface
(NSI). In: 2012 SC Companion: High Performance Computing, Networking Storage
and Analysis. pp. 150–156. IEEE, Salt Lake City, UT (2012). https://doi.org/10.1109/SC.Companion.2012.30. 118.
Zhao, Z., Grosso, P., de Laat, C.: OEIRM: An Open
Distributed Processing Based Interoperability Reference Model for e-Science.
In: Park, J.J., Zomaya, A., Yeo, S.-S., and Sahni, S. (eds.) Network and Parallel Computing. pp.
437–444. Springer Berlin Heidelberg, Berlin, Heidelberg (2012). https://doi.org/10.1007/978-3-642-35606-3_52. 119.
Zhao, Z., Dumitru, C., Grosso, P., de Laat, C.:
Network Resource Control for Data Intensive Applications in Heterogeneous
Infrastructures. In: 2012 IEEE 26th International Parallel and Distributed
Processing Symposium Workshops & PhD Forum. pp. 2069–2076. IEEE,
Shanghai, China (2012). https://doi.org/10.1109/IPDPSW.2012.243. 120.
Pavlov, D., Soeurt, J.,
Grosso, P., Zhao, Z., Veldt, K.
van der, Zhu, H., Laat, C. de: Towards Energy Efficient Data Intensive
Computing Using IEEE 802.3az. In: 2012 SC Companion: High Performance
Computing, Networking Storage and Analysis. pp. 806–810. IEEE, Salt Lake
City, UT (2012). https://doi.org/10.1109/SC.Companion.2012.112. 121.
Demchenko, Y., Zhao, Z., Grosso, P., Wibisono, A., de Laat, C.: Addressing Big
Data challenges for Scientific Data Infrastructure. In: 4th IEEE
International Conference on Cloud Computing Technology and Science
Proceedings. pp. 614–617. IEEE, Taipei, Taiwan (2012). https://doi.org/10.1109/CloudCom.2012.6427494. 122.
Zhao, Z., Taal, A., Grosso, P., de Laat, C.:
Resource Discovery in Large Scale Network Infrastructure. In: 2011 IEEE Sixth
International Conference on Networking, Architecture, and Storage. pp.
186–190. IEEE, Dalian, China (2011). https://doi.org/10.1109/NAS.2011.43. 123.
Zhao, Z., Grosso, P., Koning, R., van der Ham, J.,
de Laat, C.: An agent based planner for including
network QoS in scientific workflows. In: Proceedings of the International
Multiconference on Computer Science and Information Technology. pp. 231–238.
IEEE, Wisla (2010). https://doi.org/10.1109/IMCSIT.2010.5680060,
Best paper award. 124.
Zhao, Z., Grosso, P., Koning, R., van der Ham, J.,
de Laat, C.: Network resource selection for data transfer processes in
scientific workflows. In: The 5th Workshop on Workflows in Support of
Large-Scale Science. pp. 1–6. IEEE, New Orleans, LA, USA (2010). https://doi.org/10.1109/WORKS.2010.5671840. 125.
Zhao, Z., Grosso, P., Koning, R., Ham, J., de
Laat, C.: An Architecture Including Network QoS in Scientific Workflows. In:
2010 Ninth International Conference on Grid and Cloud Computing. pp. 104–109.
IEEE, Nanjing, China (2010). https://doi.org/10.1109/GCC.2010.32. 126.
Zhao, Z., Belloum, A., Bubak, M., Hertzberger, B.:
Support for Cooperative Experiments in VL-e: From Scientific Workflows to
Knowledge Sharing. In: 2008 IEEE Fourth International Conference on eScience.
pp. 329–330. IEEE, Indianapolis, IN, USA (2008). https://doi.org/10.1109/eScience.2008.120. 127.
Wibisono, A., Zhao,
Z., Belloum, A., Bubak,
M.: A Framework for Interactive Parameter Sweep Applications. In: Bubak, M., van Albada, G.D., Dongarra, J., and Sloot, P.M.A.
(eds.) Computational Science – ICCS 2008. pp. 481–490. Springer Berlin
Heidelberg, Berlin, Heidelberg (2008). https://doi.org/10.1007/978-3-540-69389-5_55. 128.
Wibisono, A., Zhao,
Z., Belloum, A., Bubak,
M.: A Framework for Interactive Parameter Sweep Applications. In: 2008 Eighth
IEEE International Symposium on Cluster Computing and the Grid (CCGRID). pp.
703–703. IEEE, Lyon, France (2008). https://doi.org/10.1109/CCGRID.2008.111. 129.
Belloum, A., Zhao, Z., Bubak, M.: International
Workshop on Applications of Workflows in Computational Science (AWCS 08). In:
Bubak, M., van Albada,
G.D., Dongarra, J., and Sloot,
P.M.A. (eds.) Computational Science – ICCS 2008. pp. 459–462. Springer Berlin
Heidelberg, Berlin, Heidelberg (2008). https://doi.org/10.1007/978-3-540-69389-5_52. 130.
Zhao, Z., Belloum, A.,
De Laat, C., Adriaans, P., Hertzberger,
B.: Using Jade agent framework to prototype an e-Science workflow bus. In:
Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid ’07). pp. 655–660. IEEE, Rio de Janeiro, Brazil
(2007). https://doi.org/10.1109/CCGRID.2007.120. 131.
Zhao, Z., Belloum, A.,
de Laat, C., Adriaans, P., Hertzberger,
B.: Distributed execution of aggregated multi domain workflows using an agent
framework. In: 2007 IEEE Congress on Services (Services 2007). pp. 183–190.
IEEE, Salt Lake City, UT, USA (2007). https://doi.org/10.1109/SERVICES.2007.30. 132.
Wibisono, A., Vasyunin,
D., Korkhov, V., Zhao, Z., Belloum, A., de Laat, C., Adriaans, P., Hertzberger, B.:
WS-VLAM: A GT4 Based Workflow Management System. In: Shi, Y., van Albada, G.D., Dongarra, J., and
Sloot, P.M.A. (eds.) Computational Science – ICCS
2007. pp. 191–198. Springer Berlin Heidelberg, Berlin, Heidelberg (2007). https://doi.org/10.1007/978-3-540-72588-6_34. 133.
Terpstra, F., Zhao,
Z., Mulder, W., Adriaans, P.: Towards a Formal
Foundation for Aggregating Scientific Workflows. In: Shi, Y., van Albada, G.D., Dongarra, J., and
Sloot, P.M.A. (eds.) Computational Science – ICCS
2007. pp. 216–219. Springer Berlin Heidelberg, Berlin, Heidelberg (2007). https://doi.org/10.1007/978-3-540-72588-6_38. 134.
Zhao, Z., Booms, S., Belloum,
A., Laat, C., Hertzberger, B.: VLE-WFBus: A Scientific Workflow Bus for Multi e-Science
Domains. In: 2006 Second IEEE International Conference on e-Science and Grid
Computing (e-Science’06). pp. 11–11. IEEE, Amsterdam, The Netherlands (2006).
https://doi.org/10.1109/E-SCIENCE.2006.261095. 135.
Zhao, Z., van Albada,
D., Sloot, P.: Rapid Prototyping of Complex
Interactive Simulation Systems. In: 10th IEEE International Conference on
Engineering of Complex Computer Systems (ICECCS’05). pp. 366–375. IEEE,
Shanghai, China (2005). https://doi.org/10.1109/ICECCS.2005.69. 136.
Zhao, Z., Belloum, A., Yakali, H., Sloot, P., Hertzberger, B.: Dynamic Work.ow
in a Grid Enabled Problem Solving Environment. In: The Fifth International
Conference on Computer and Information Technology (CIT’05). pp. 339–345.
IEEE, Shanghai, China (2005). https://doi.org/10.1109/CIT.2005.101. 137.
Zhao, Z., Belloum, A.,
Wibisono, A., Terpstra, F., de Boer, P.T., Sloot,
P., Hertzberger, B.: Scientific workflow
management: between generality and applicability. In: Fifth International
Conference on Quality Software (QSIC’05). pp. 357–364. IEEE, Melbourne,
Australia (2005). https://doi.org/10.1109/QSIC.2005.56. 138.
Zhao, Z., Belloum, A., Sloot, P., Hertzberger, B.:
Agent technology and scientific workflow management in an e-science
environment. In: 17th IEEE International Conference on Tools with Artificial
Intelligence (ICTAI’05). pp. 5 pp. – 23. IEEE, Hong Kong, China (2005). https://doi.org/10.1109/ICTAI.2005.29. 139.
Zhao, Z., Belloum, A., Sloot, P., Hertzberger, B.:
Agent Technology and Generic Workflow Management in an e-Science Environment.
In: Zhuge, H. and Fox, G.C. (eds.) Grid and
Cooperative Computing - GCC 2005. pp. 480–485. Springer Berlin Heidelberg,
Berlin, Heidelberg (2005). https://doi.org/10.1007/11590354_61. 140.
Zhao, Z. (2004, december 09). An
agent based architecture for constructing
Interactive Simulation Systems. UvA Universiteit van Amsterdam. Promoter/co-promoter: prof. dr.
P.M.A. Sloot & dr. G.D. van Albada.
[Link] 141.
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. 142.
Zajac, K., Tirado-Ramos, A., Zhao, Z., Sloot, P., Bubak, M.: Grid Services for HLA-Based Distributed
Simulation Frameworks. In: Fernández Rivera, F., Bubak,
M., Gómez Tato, A., and Doallo, R. (eds.) Grid Computing. pp. 147–154. Springer Berlin
Heidelberg, Berlin, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24689-3_19. 143.
Zhao, Z., van Albada,
G.D., Tirado-Ramos, A., Zajac, K., Sloot, P.M.A.:
ISS-Studio: A Prototype for a User-Friendly Tool for Designing Interactive
Experiments in Problem Solving Environments. In: Sloot,
P.M.A., Abramson, D., Bogdanov, A.V., Dongarra,
J.J., Zomaya, A.Y., and Gorbachev, Y.E. (eds.)
Computational Science — ICCS 2003. pp. 679–688. Springer Berlin Heidelberg,
Berlin, Heidelberg (2003). https://doi.org/10.1007/3-540-44860-8_70. 144.
Tirado-Ramos, A., Zajac, K., Zhao, Z., Sloot, P.M.A., van Albada, D., Bubak, M.:
Experimental Grid Access for Dynamic Discovery and Data Transfer in
Distributed Interactive Simulation Systems. In: Sloot,
P.M.A., Abramson, D., Bogdanov, A.V., Dongarra,
J.J., Zomaya, A.Y., and Gorbachev, Y.E. (eds.)
Computational Science — ICCS 2003. pp. 284–292. Springer Berlin Heidelberg,
Berlin, Heidelberg (2003). https://doi.org/10.1007/3-540-44860-8_29. 145.
Zhao, Z., Belleman,
R.G., van Albada, G.D., Sloot,
P.M.A.: AG-IVE: An Agent Based Solution to Constructing Interactive
Simulation Systems. In: Sloot, P.M.A., Hoekstra,
A.G., Tan, C.J.K., and Dongarra, J.J. (eds.)
Computational Science — ICCS 2002. pp. 693–703. Springer Berlin Heidelberg,
Berlin, Heidelberg (2002). https://doi.org/10.1007/3-540-46043-8_70. 146.
Zhao, Z., Belleman, R.G., Albada,
G.D. van & Sloot, P.M.A. (2002). Reusability
and Efficiency in Constructing Interactive Simulation Systems. In E.F. Deprettere,
A.S.Z. Belloum, J.W.J. Heijnsdijk & F. van der Stappen (Eds.),
ASCI 2002, Proceedings of the eighth annual conference of the Advanced School
for Computing and Imaging (pp. 268-275). Delft: ASCI. [Link] 147.
Zhao, Z., Belleman, R.G., Albada,
G.D. van & Sloot, P.M.A. (2002). Scenario
Switches and State Updates in an Agent-based Solution to Constructing
Interactive Simulation Systems. In Proceedings of the Communication Networks
and Distributed Systems Modeling and
Simulation Conference (CNDS 2002) (pp. 3-10). [Link] 148.
Zhao, Z., Belleman R.
G., Albada G.D.and Sloot P.M.A. (2001): System integration for interactive simulation systems using
intelligent agents, in R.L. Lagendijk;
J.W.J. Heijnsdijk; A.D. Pimentel and M.H.F.
Wilkinson, editors, Proceedings of the 7th annual conference of the Advanced
School for Computing and Imaging, pp. 399-406. ASCI, May 2001. ISBN
90-803086-6-8. [Link] 149.
Belleman,R.G., Zhao,Z., Albada G.D. van and Sloot P.M.A
(2000) Design considerations for
the construction of immersive dynamic exploration environments, in
L.J. van Vliet; J.W.J. Heijnsdijk;
T. Kielmann and P.M.W. Knijnenburg, editors, ASCI 2000, Proceedings of the sixth
annual conference of the Advanced School for Computing and Imaging, pp.
195-201. ASCI, Delft, June 2000. ISBN 90-803086-5-x. [Link] Peer
reviewed abstracts and posters 150.
Xiaofeng Liao, Doron Goldfarb, Barbara Magagna, Markus Stocker, Peter Thijsse,
Dick Schaap, Zhiming
Zhao (2020) EGU, April 2020 [to appear] 151.
Zhiming Zhao, Paul Martin, and Spiros Koulouzis, (2019) Optimizing environmental data services
on federated Cloud and e-Infrastructures, EGU, April 2019 [2019EGUGA..21.3683Z] 152.
Yang Hu, Cees De Laat and Zhiming Zhao(2019)Learning
Workflow Scheduling in Multi-Resource Clusters, ICT.open,
March 20, 2019 [Poster] 153.
Huan Zhou, Yang Hu, Jinshu Su, Cees de Laat and Zhiming
Zhao (2018) CloudsStorm: An
Application-driven Framework to Enhance the Programmability and
Controllability of Cloud Virtual Infrastructures, ICT.open, March 19, 2018 [online] 154.
Koulouzis, Spiros; Carval, Thierry;
Martin, Paul; Grenier, Baptiste; Chen,
Yin; Heikkinen, Jani; Zhao, Zhiming(2018) Dynamic
Optimization for Time-critical Data Services: A Case Study in Euro-Argo
Research Infrastructure, 20th EGU General Assembly, EGU2018, Proceedings
from the conference held 4-13 April, 2018 in Vienna, Austria, p.16012. [2018EGUGA..2016012K] 155.
Abraham Nieva de
la Hidalga, Alex R Hardisty,
Barbara Magagna, Paul W Martin, Zhiming
Zhao (2018) Use of the ENVRI Reference Model to Support the Design
of Environmental Research Infrastructures, 20th EGU General Assembly,
EGU2018, Proceedings from the conference held 4-13 April, 2018 in Vienna,
Austria, p.18552 [2018EGUGA..2018552N] 156.
Kutsch, W. L.; Zhao, Z.; Hardisty,
A.; Hellström, M.; Chin, Y.; Magagna, B.; Asmi, A.; Papale,
D.; Pfeil, B.; Atkinson, M. (2017) Data interoperabilty between European Environmental
Research Infrastructures and their contribution to global data networks, AGU
2018, American Geophysical Union, Fall Meeting 2017, abstract
#IN44B-01. [2017AGUFMIN44B..01K] Technical
report and newsletters 157.
Zhao, Z., Martin, P. Jeffery K.,
(2017) VRE in the Data for Science Approach to Common Challenges in
ENVRIPLUS, ERCIM, Newsletter, April 2017 158.
Zhao, Z. (2016) Data for science: software
and solutions for the environmental sciences, EGI Newsletter, January 2016. 159.
Zhao, Z., (2015) Data for Science theme:
software and solutions to address common challenges facing environmental
research infrastructures, 1st ENVRIPLUS Newsletter, November 2015. 160.
Ghijsen, M., Ham, J. van der, Grosso, P., Dumitru, C.,
Zhu, H., Zhao, Z. & Laat, C. de (2013). A semantic-web approach for modeling computing infrastructures. (SNE technical report 2013-01).
Amsterdam: Universiteit van Amsterdam, System and Network
Engineering. [Full text] 161.
Hertzberger, L.O., Belleman,
R.G., Jansen, M.G., Zhao, Z., Hooft,
P. van, Belloum, A.S.Z., Mirzadeh, N., Yakali,
H.H., Liere, R. van, Nuallain,
B.S., Verstoep, K., Groep,
D.L. & Bouwhuis, M.C. (2005). Recommendation
to VLeIT: Scientific workflow management
systems for the PoC r1. (Internal
report). Amsterdam: Informatics Institute. Supervised
PhD thesis 162.
Yang
Hu (2019) Resource Scheduling for Quality-Critical Applications on Cloud
Infrastructure, University of Amsterdam, [ISBN: 978-94-028-1713-3]. 163.
Huan
Zhou (2019) Seamless Infrastructure Programming and Control for
Quality-critical Cloud Applications, [ISBN: 978-94-028-1727-0] Supervised
student thesis 164.
Rasha Daoud (2019) Towards sustainable service
portfolios: a self-learning solution for service portfolio Management, Master
thesis [10.5281/zenodo.3521558],
Supervisor, Zhao, Z 165.
Pieter Donkers (2019)
MYST: Automated DevOps for distributed applications across heterogeneous
Cloud, Fog and Edge infrastructures. Master thesis [10.5281/zenodo.3521562],
Supervisor, Zhao, Z. 166.
Kees de Jong & Anas Younis (2019)
Planning and Scaling a Named Data Network with Persistent Identi 167.
Elias el Khaldi Ahanach (2019) CWEA: Automated log retrieval for
performance analysis of service-oriented scienti 168.
Jordy Bottelier (2018)
Semi-Automatic schema matching: challenges and a composable match based solution, Master thesis [doi:10.5281/zenodo.1419496], Supervisor, Zhao, Z. 169.
Jordan Maduro (2018) Towards a taxonomy
for quality control in environmental sciences, Master thesis [doi:10.5281/zenodo.1419494], Supervisor, Zhao, Z. 170.
Ewoud Bouman (2018) Characterizing
access patterns from ftp logs: a case study on Euro-Argo research
infrastructure, Bachelor thesis [doi:10.5281/zenodo.1419490]. Supervisor Zhao,
Z., Taal, A., and Koulouz, S. 171.
Mousa, R., (2017), Application aware digital objects
access and distribution using Named Data Networking (NDN). Master, Zenodo. [doi:10.5281/zenodo.889740].
Supervisor Zhao, Z. 172.
Elzinga, O., (2017). Collecting, cataloguing and searching performance information of Cloud
resources. Master, Zenodo. [doi:10.5281/zenodo.889738].
Supervisor Taal, A., & Zhao, Z. 173.
Acosta, C., (2017) From reference model and system
requirements to architecture design recommendations: an expert system
approach. Zenodo. [doi:10.5281/zenodo.889748].
Master, Supervisor Zhao, Z., & Martin, P. 174.
Konstantaras, S., Grafis,
I., (2014) PIRE ExoGENI – ENVRI:
Preparation for Big Data Science, Zenodo. [doi:10.5281/zenodo.889699].
Master, Supervisor Oprescu, A., & Zhao,
Z. 175.
Karakannas, A., (2014) Information Centric
Networking for Delivering Big Data with Persistent Identifiers. [doi:10.5281/zenodo.889603].
Master, Supervisor Zhao, Z. 176.
Pavlov, D., & Soeurt,
J., (2012) Green Computing in IEEE 802.3az-enabled Clusters. Zenodo. [doi:10.5281/zenodo.889752].
Master, Supervisor Grosso, P., & Zhao, Z. In
Chinese 177.
Zhao, Z., Liao, X., Wang, X., Ruan, C., Zhu, Y., Feng, D. (2019), An Reference Model approach for developing agriculture
big data infrastructures, Journal of East China Normal University (Natural
Sc 2019 Vol.2019 (2): 77-96, [10.3969/j.issn.1000-5641.2019.02.009] 178.
Demchenko, Y., Zhao, Z., Grosso,
P., Wibisono, A., de Laat, C., (2013) 科研信息化基础 设施的大数据挑战 (Big Data Challenges for e-Science
Infrastructure) China Science and Technology Resources Review,
Vol.45 No.1 30-35,40 Jan. 2013. ISSN 1674-1544 [online] 179.
Zhao, Z. (1997) How to analyze the effect and cost in using educational
resources, Journal of Research of Audio and Video Education, (In Chinese) January 1997. 180.
Zhao, Z. and Zhang, J. (1997) The
courseware authoring system in Multimedia Language Learning system,
Journal of Research of Audio and Video Education, (In Chinese) March 1997. 181.
Zhao, Z. and Zhang J. (1997) The trend of
Multimedia Language Learning system, in Proceedings of the eighth annual
conference on CBE, (In Chinese) pp. 202. Shanghai, China,
November 1997. 182.
Zhao, Z. and Zhang J (1997): The software
environment of Multimedia language Learning system, in proceedings of 1st
annual of GCCCE (Global Chinese Computer Education), (In Chinese) Guangzhou, China, May 1997. 183.
Zhou Q. and Zhao, Z. (1997): A
new model of developing Web based courseware, in Proceedings of the
eighth annual conference on CBE, (In Chinese) pp. 165. Shanghai, China,
November 1997. Excellent paper award. 184.
Zhao, Z. and Wang J. (1995): The
implementation of the instructional strategy in educational software, in
Proceedings of the seventh annual conference on CBE, (In Chinese) Changsha, China, November 1995. |
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Update date: September 12 2020