Dr. Zhiming Zhao home page

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...

About me

Research

Projects

Vacancy

Events

Activities

Publications

Lists

Software

Notes

About me                     

Recent activities

1.     ENVRI-FAIR FAIRness workshops

...

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 ENVRI^PLUS 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.

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.

Leader: Dr. Zhiming Zhao 

Researchers:

·       Dr. Peng Chen, Cloud infrastructure optimization (2020-)

·       Dr. Xiaofeng Liao, Alignment, annotation (2017-)

·       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-)

·       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]

Master students:

·       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
er Interoperability, Master thesis [10.5281/zenodo.3521549]

·       Elias el Khaldi Ahanach (2019) CWEA: Automated log retrieval for performance analysis of service-oriented scienti
c workfows. Master thesis [10.5281/zenodo.3521576]

·       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 

Funding and projects (PI)                                        

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Current projects

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 ENVRI^FAIR (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 ENVRI^PLUS (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

Open positions            

Home

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

Community

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Editorial board

1.     International journal of: Blockchains: research and applications

Workshop organizer/co-organizer

1. Zhao, Z., et al., International workshop on interoperable infrastructures for interdisciplinary big data sciences (IT4RIs)
1. 1^st IT4RIs, in conjunction with IEEE e-Science 2015, Munich, Germany
2. 2^nd IT4RIs, in conjunction with IEEE RTSS (Real-time System Symposium) 2016, Porto, Portugal
3. 3^rd IT4RIs, in conjunction with Amsterdam HPC 2018, Amsterdam, the Netherlands
2. Zhao, Z., Keith, J., Magagana, B., Stocker, M., Martin, P.,

1.     Special session: Using heterogeneous environmental data for system-level science, 2018, Vienna, EGU

3. Chen, Y., et al., Zhao, Z., Session on Towards Environmental Research Infrastructure as a Service for the Open Science Cloud

1.     in Digital Infrastructure for research 2016, Krakow, Poland

2.     in Digital Infrastructure for research 2017, Brussels, Belgium

4. Zhao, Z., et al., International workshop on Workflow Systems in E-Sciences (WSES),
1. 1^st WSES, in conjunction with ICCS 2006, Reading, UK
2. 2^nd WSES, in conjunction with ICCS 2007, Beijing, China
3. 3^rd WSES, in conjunction with IEEE CCGrid 2008, Lyon, France
4. 4^th WSES, in conjunction with IEEE CCGrid 2009, Shanghai, China
5. Belloum, A., Bubak, M., Zhao, Z., International Workshop on Applications of workflows in Computational Science (AWCS) 

1. AWCS, in conjunction with ICCS, 2008
5. Belloum, A., Zhao, Z., et al, International Workshop on Scientific Workflows and Business Workflow Standards in e-Science (SWBES),

1. 1^st SWBES, in conjunction with IEEE e-Science 2006, Amsterdam, the Netherlands
2. 2^nd SWBES, in conjunction with IEEE e-Science 2007, Bangalore India
3. 3^rd SWBES, in conjunction with IEEE e-Science 2008, Indianapolis, USA

Summer school

1.    International summer school on data management in environmental and earth sciences (2018 | 2019 | 2020)

Workshop/Panel chair

1. Panel Co-Chair, International conference on High Performance Computing and Simulation (HPCS 2015, Amsterdam)
2. Workshop Chair, International conference on Network and Distributed Computing (ICNDC 2010-2013, 2015, 2016)

Program committee

1. Int’l workshop on Science Gateway (IWSG 2018 | 2019 | 2020)
2. IEEE International conference on Advanced Information Networking and Applications (AINA 2017)
3. IEEE International conference on e-Science (2014, 2015, 2016, 2017, 2019)
4. IEEE International conference on Ubiquitous Computing and Communication (IUCC, 2011, 2013, 2015, 2016, 2017)
5. IEEE International conference on Internet of Things and Cloud (FiCloud, 2016)
6. International conference on Smart Data (2016, 2017)
7. Workshop on Management of resources and services in Cloud and Sky computing (MICAS, 2016)
8. W3C – VRE4EIC Workshop on Smart Descriptions & Smarter Vocabularies (SDSVoc, 2016)
9. IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom, 2014)
10. International Workshop on Workflow Models, Systems, Services and Applications in the Cloud (2012-2014)
11. The 11th IEEE International Conference on Computer and Information Technology (2011)
12. The IET International Conference on Frontier Computing– Theory, Technologies and Applications (2010)
13. International Workshop on Scientific Workflows (2009-2011)

Recent activities and agenda

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• 2019, August 25-29, Euro-Par, Gottingen, Germany
• 2019, August 15-17, IEEE NAS, Enshi, China
• 2019, August 10-11, IEEE Smart IoT, Tianjin, China
• 2019, July 8-13, IEEE Service congress, Milan, Italy
• 2019, July 1-5, ENVRI summer school, Lecce, Italy
• 2019, June 26, ENVRI-FAIR ecosystem workshop, Lecce, Italy
• 2019, June 18, DISCCO site visit, Leiden
• 2019, June 13, goFAIR workshop, Leiden
• 2019, June 11-12, ENVRI-FAIR atmosphere workshop, Amsterdam
• 2019, June 6-8, EU H2020 ARTICONF project meeting, Stavanger, Norway
• 2019, June 4, ENVRI-PLUS, final dissemination event, Brussels
• 2019, May 27-29, Lifewatch community meeting, Rome
• 2019, May 14-17, IEEE CCGrid conference, Cyprus
• 2019, May 13-14, ENVRI-FAIR marine community workshop, Amsterdam
• 2019, April 29- May 2, IEEE INFOCOM, Paris, France
• 2019, April 15-16, LifeWatch VRE workshop
• 2019, April, 10-12, EOSC Hub conference, Prague, Czech
• 2019, April 8-12, EGU, Austria
• 2019, January 14-16, ENVR-FAIR kickoff, Prague, Czech
• 2019, January 11-12, ACTRIS site visit, Olso, Norway
• 2019, January 8-10, ARTICONF kick off, Klagenfurt, Austria
• 2018, December 17-29, IEEE/ACM UCC
• 2018, December 10-15, IEEE/ACM CloudCom
• 2018, September 11, ICOS science conference, Prague
• 2018, August 31, EuroPar, Turin, Italy
• 2018, August 20, Fudan Data Science lab visit, China
• 2018, May 14-18, ENVRI week, Zandvoort, NL
• 2018, May 1-3, IEEE CCGrid, Washington, USA
• 2018, April, EGU, Vienna, Austria
• 2018, March 20/21, SWITCH, final project review, Brussels, Belgium
• 2018, February, VRE4EIC project meeting, Barcelona, Spain
• 2018, February, ENVRIPLUS/D4Science workshop, Pisa, Italy
• 2018, January, 18 IT4RIs Amsterdam, the Netherlands
• …

Publications

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Journals

1.     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.

2.     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. IEEE Internet of Things (IoT) Journal, (2020). https://doi.org/10.1109/JIOT.2020.3024833[Zenodo].

3.     Zhang, L., Jiang, W., and Zhao, Z., Short‐text feature expansion and classification based on nonnegative matrix factorization, International Journal of Intelligent Systems. (2020). https://doi.org/10.1002/int.22290[Zenodo].

4.     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.

5.     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.

6.     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.

7.     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.

8.     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.

9.     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.

10.  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]

11.  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.

12.  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.

13.  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.

14.  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.

15.  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.

16.  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.

17.  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.

18.  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.

19.  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.

20.  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.

21.  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.

22.  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].

23.  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.

24.  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.

25.  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.

26.  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.

27.  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.

28.  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.

29.  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)

30.  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]

31.  Zhao, Z., Altmeyer, S., Keith J., Atkinson, M. and Ulisses A.: Nearly real time data processing and time critical cloud applications. Proceedings of the 2^nd 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]

32.  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]

33.  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.

34.  Belloum, A., Deelman, E. & Zhao, Z.: Scientific workflows. Scientific Programming, 14(3-4), 171-171 (2006). [Full text]

Book (Eds)

35.  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

36.  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.

37.  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.

38.  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.

39.   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.

40.  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.

41.  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.

42.  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.

43.  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.

44.  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.

45.  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.

46.  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.

47. 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].

48. 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

49.  Zhao, Z., Rong, C., Gilje Jaatun, M., A Trustworthy Blockchain-based DecentralisedResource Management System in the Cloud, in the Proceedings of the international conference on Parallel and Distributed Systems (ICPADS) 2020, Hongkong, accepted. [Zenodo]

50.  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].

51.  de Jong, K., Fahrenfort, C., Younis, A., Zhao, Z.: Sharing digital object across data infrastructures using Named Data Networking (NDN). 2^nd 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].

52.  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].

53.  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].

54.  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].

55.  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].

56.  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].

57.  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].

58.  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.

59.  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.

60.  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).

61.  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].

62.  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].

63.  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]

64.  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.

65.  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].

66.  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.

67.  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].

68.  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].

69.  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.

70.  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.

71.  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.

72.  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.

73.  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]

74.  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.

75.  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.

76.  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.

77.  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.

78.  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.

79.  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.

80.  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.

81.  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.

82.  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.

83.  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.

84.  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.

85.  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.

86.  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.

87.  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.

88.  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.

89.  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.

90.  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.

91.  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.

92.  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.

93.  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.

94.  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.

95.  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.

96.  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.

97.  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.

98.  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.

99.  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.

100.                 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.

101.                 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.

102.                 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]

103.                 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]

104.                 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.

105.                 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].

106.                 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.

107.                 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.

108.                 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.

109.                 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.

110.                 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.

111.                 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.

112.                 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.

113.                 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. 

114.                 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.

115.                 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.

116.                 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.

117.                 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.

118.                 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.

119.                 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.

120.                 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.

121.                 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.

122.                 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.

123.                 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.

124.                 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.

125.                 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.

126.                 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.

127.                 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.

128.                 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.

129.                 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.

130.                 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]

131.                 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.

132.                 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.

133.                 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.

134.                 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.

135.                 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.

136.                 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]

137.                 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]

138.                 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]

139.                 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

140.                 Xiaofeng Liao, Doron Goldfarb, Barbara Magagna, Markus Stocker, Peter Thijsse, Dick Schaap, Zhiming Zhao (2020) EGU, April 2020 [to appear]

141.                 Zhiming Zhao, Paul Martin, and Spiros Koulouzis, (2019) Optimizing environmental data services on federated Cloud and e-Infrastructures, EGU, April 2019 [2019EGUGA..21.3683Z]

142.                 Yang Hu, Cees De Laat and Zhiming Zhao(2019)Learning Workflow Scheduling in Multi-Resource Clusters, ICT.open, March 20, 2019 [Poster]

143.                 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]

144.                 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]

145.                 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]

146.                 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

147.                Zhao, Z., Martin, P. Jeffery K., (2017) VRE in the Data for Science Approach to Common Challenges in ENVRIPLUS, ERCIM, Newsletter, April 2017

148.                Zhao, Z. (2016) Data for science: software and solutions for the environmental sciences, EGI Newsletter, January 2016.

149.                Zhao, Z., (2015) Data for Science theme: software and solutions to address common challenges facing environmental research infrastructures, 1st ENVRIPLUS Newsletter, November 2015.

150.                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]

151.                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

152.                 Yang Hu (2019) Resource Scheduling for Quality-Critical Applications on Cloud Infrastructure, University of Amsterdam, [ISBN: 978-94-028-1713-3].

153.                 Huan Zhou (2019) Seamless Infrastructure Programming and Control for Quality-critical Cloud Applications, [ISBN: 978-94-028-1727-0]

Supervised student thesis

154.                 Rasha Daoud (2019) Towards sustainable service portfolios: a self-learning solution for service portfolio Management, Master thesis [10.5281/zenodo.3521558], Supervisor, Zhao, Z

155.                 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.

156.                 Kees de Jong & Anas Younis (2019) Planning and Scaling a Named Data Network with Persistent Identi
er Interoperability, Master thesis [10.5281/zenodo.3521549], Supervisor, Zhao, Z,

157.                 Elias el Khaldi Ahanach (2019) CWEA: Automated log retrieval for performance analysis of service-oriented scienti
c workfows. Master thesis [10.5281/zenodo.3521576], Supervisor, Zhao, Z., Spiros Koulouzis.

158.                 Jordy Bottelier (2018) Semi-Automatic schema matching: challenges and a composable match based solution, Master thesis [doi:10.5281/zenodo.1419496], Supervisor, Zhao, Z.

159.                 Jordan Maduro (2018) Towards a taxonomy for quality control in environmental sciences, Master thesis [doi:10.5281/zenodo.1419494], Supervisor, Zhao, Z.

160.                 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.

161.                 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.

162.                 Elzinga, O., (2017). Collecting, cataloguing and searching performance information of Cloud resources. Master, Zenodo. [doi:10.5281/zenodo.889738]. Supervisor Taal, A., & Zhao, Z.

163.                 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.

164.                 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.

165.                 Karakannas, A., (2014) Information Centric Networking for Delivering Big Data with Persistent Identifiers. [doi:10.5281/zenodo.889603]. Master, Supervisor Zhao, Z.

166.                 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

167.                 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]

168.                 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]

169.                 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.

170.                 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.

171.                 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.

172.                 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.

173.                 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. 

174.                 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.