|
|
|
|||
|
|
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... |
||
|
|
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 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. |
||||
|
|
||||
|
|
Research:
Quality Critical Applications on Programmable Infrastructures |
|
|
|
|
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. 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-) ·
Zhengqiu
Zhu, Incentive models in crowd applications (2020-) ·
Yixian Shen, Cloud
application scheduling (2019-) ·
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 · 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 |
|
|
|
|
|
Funding and projects (PI) |
|
|
|
|
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]. 5. 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. Finished projects 6. EU
H2020 VRE4EIC (A Europe-wide interoperable Virtual Research
Environment to Empower multidisciplinary research communities and accelerate
Innovation and Collaboration). Grant number 676247. H2020-EINFRA-2015-1. Duration October 2015-
September 2018. (Newsletter in IvI) 7.
EU H2020 SWITCH (Software
Workbench for Interactive, Time Critical and Highly self-adaptive cloud
applications). Grant No 643963. H2020-ICT 9-2014-1 call: Tools and methods
for software development. Duration: February 2015- January 2018. (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 |
|
|
||
|
|
|
|
|
|
|
|
|
|
||
|
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 |
|
|
||
|
|
|
|
|
|
|
|
|
|
||
|
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
|
|
|
||
|
|
|
|
|
|
|
|
Recent activities and
agenda |
|
|
|
|
|
|
||
|
|
|
|
|
|
|
|
|
|
||
|
Journals 1. 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. 2. 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. 3. 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. 4. 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.
5. 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. 6. 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. 7. 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] 8. 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. 9. 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. 10. 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. 11. 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. 12. 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. 13. 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. 14. 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. 15. 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. 16. 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. 17. 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. 18. 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. 19. 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]. 20. 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. 21. 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. 22. 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. 23. 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. 24. 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. 25. 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. 26. 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) 27. 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] 28. 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] 29. 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. 30. Belloum,
A., Deelman, E. & Zhao, Z.: Scientific workflows. Scientific
Programming, 14(3-4), 171-171 (2006). [Full text] Book chapters 31. 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]. 32. 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 33. Kees de Jong, Cas Fahrenfort, Anas Younis and Zhiming Zhao (2020) Sharing
digital object across data infrastructures using Named Data Networking (NDN),
2nd workshop on Network Aware Big Data Computing (NEAC) in the
context of IEEE CCGrid, Australia (to appear). 34. Huan
Zhou, Xue Ouyangy, and Zhiming Zhao (2020) ALLSTAR: a blockchain based joint ecosystem for the decentralized
cloud and edge computing environment, IEEE Joint Cloud Computing
Conference, UK (to appear). 35. 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]. 36. 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]. 37. 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]. 38. 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]. 39. 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]. 40. 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.
41. 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.
42. 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). 43. 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]. 44. 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]. 45. 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] 46. 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. 47. 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]. 48. 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. 49. 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]. 50. 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]. 51. 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. 52. 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. 53. 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. 54. 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. 55. 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] 56. 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. 57. 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. 58. 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. 59. 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. 60. 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. 61. 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. 62. 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. 63. 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. 64. 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. 65. 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. 66. 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. 67. 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. 68. 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. 69. 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. 70. 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. 71. 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. 72. 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. 73. 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. 74. 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. 75. 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. 76. 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. 77. 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. 78. 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. 79. 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. 80. 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. 81. 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. 82. 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. 83. 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. 84. 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] 85. 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] 86. 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. 87. 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]. 88. 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. 89. 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. 90. 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. 91. 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. 92. 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. 93. 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. 94. 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. 95. 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. 96. 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. 97. 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. 98. 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. 99. 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. 100.
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. 101.
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. 102.
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. 103.
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. 104.
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. 105.
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. 106.
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. 107.
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. 108.
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. 109.
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. 110.
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. 111.
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. 112.
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] 113.
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. 114.
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. 115.
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. 116.
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. 117.
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. 118.
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] 119.
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] 120.
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] 121.
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 122.
Xiaofeng
Liao, Doron Goldfarb, Barbara Magagna, Markus
Stocker, Peter Thijsse, Dick Schaap,
Zhiming Zhao (2020) EGU, April 2020 [to
appear] 123.
Zhiming Zhao, Paul Martin, and
Spiros Koulouzis, (2019) Optimizing environmental data
services on federated Cloud and e-Infrastructures, EGU, April 2019 [2019EGUGA..21.3683Z] 124.
Yang Hu, Cees De Laat and Zhiming Zhao(2019)Learning
Workflow Scheduling in Multi-Resource Clusters, ICT.open,
March 20, 2019 [Poster] 125.
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] 126.
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] 127.
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] 128.
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 129.
Zhao, Z., Martin,
P. Jeffery K., (2017) VRE in the Data for Science Approach to Common
Challenges in ENVRIPLUS, ERCIM, Newsletter, April 2017 130.
Zhao, Z. (2016) Data
for science: software and solutions for the environmental sciences,
EGI Newsletter, January 2016. 131.
Zhao, Z.,
(2015) Data for Science theme: software and solutions to address
common challenges facing environmental research infrastructures, 1st
ENVRIPLUS Newsletter, November 2015. 132.
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] 133.
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 134.
Yang Hu (2019) Resource Scheduling for
Quality-Critical Applications on Cloud Infrastructure, University of
Amsterdam, [ISBN: 978-94-028-1713-3]. 135.
Huan Zhou (2019) Seamless Infrastructure
Programming and Control for Quality-critical Cloud Applications, [ISBN: 978-94-028-1727-0] Supervised student thesis 136.
Rasha
Daoud (2019) Towards sustainable service portfolios: a self-learning solution
for service portfolio Management, Master thesis [10.5281/zenodo.3521558],
Supervisor, Zhao, Z 137.
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. 138.
Kees de
Jong & Anas Younis (2019) Planning and Scaling a Named Data Network with
Persistent Identi 139.
Elias el Khaldi Ahanach (2019) CWEA:
Automated log retrieval for performance analysis of service-oriented scienti 140.
Jordy Bottelier (2018) Semi-Automatic schema matching:
challenges and a composable match based solution,
Master thesis [doi:10.5281/zenodo.1419496], Supervisor, Zhao,
Z. 141.
Jordan Maduro (2018)
Towards a taxonomy for quality control in environmental sciences, Master
thesis [doi:10.5281/zenodo.1419494],
Supervisor, Zhao, Z. 142.
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. 143.
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. 144.
Elzinga,
O., (2017). Collecting, cataloguing and searching performance information of
Cloud resources. Master, Zenodo. [doi:10.5281/zenodo.889738].
Supervisor Taal, A., & Zhao, Z. 145.
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. 146.
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. 147.
Karakannas,
A., (2014) Information Centric Networking for Delivering Big Data with
Persistent Identifiers. [doi:10.5281/zenodo.889603]. Master,
Supervisor Zhao, Z. 148.
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 149.
Zhiming
Zhao, Xiaofeng Liao, Xiaoling Wang, Chunsheng Ruan, Yifeng Zhu, Dongsheng Feng (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] 150.
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] 151.
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. 152.
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. 153.
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. 154.
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. 155.
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. 156.
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. |
|
|
||
|
|
|
|
|
|
|
|
||||
Update date:
March 30 2020