publication . Conference object . Article . Other literature type . 2016

Time Critical Requirements And Technical Considerations For Advanced Support Environments For Data-Intensive Research

Zhao, Zhiming; Martin, Paul; De Laat, Cees; Jeffery, Keith; Jones, Andrew; Taylor, Ian; Hardisty, Alex; Atkinson, Malcolm; Zuiderwijk, Anneke; Yin, Yi; ...
Open Access
  • Published: 29 Nov 2016
  • Publisher: Zenodo
Abstract
Data-centric approaches play an increasing role in many scientific domains, but in turn rely increasingly heavily on advanced research support environments for coordinating research activities, providing access to research data, and choreographing complex experiments. Critical time constraints can be seen in several application scenarios e.g., event detection for disaster early warning, runtime execution steering, and failure recovery. Providing support for executing such time critical research applications is still a challenging issue in many current research support environments however. In this paper, we analyse time critical requirements in three key kinds o...
Subjects
free text keywords: QA75, Virtual research environment, Research infrastructure, Time critical cloud applications, e-Infrastructure, real-time system
Related Organizations
Funded by
EC| VRE4EIC
Project
VRE4EIC
A Europe-wide Interoperable Virtual Research Environment to Empower Multidisciplinary Research Communities and Accelerate Innovation and Collaboration
  • Funder: European Commission (EC)
  • Project Code: 676247
  • Funding stream: H2020 | RIA
Validated by funder
,
EC| ENVRI PLUS
Project
ENVRI PLUS
Environmental Research Infrastructures Providing Shared Solutions for Science and Society
  • Funder: European Commission (EC)
  • Project Code: 654182
  • Funding stream: H2020 | RIA
Validated by funder
,
EC| SWITCH
Project
SWITCH
Software Workbench for Interactive, Time Critical and Highly self-adaptive cloud applications
  • Funder: European Commission (EC)
  • Project Code: 643963
  • Funding stream: H2020 | RIA
Validated by funder
Communities
CLARIN
Digital Humanities and Cultural HeritageDH-CH communities: CLARIN
EGI FederationEGI Projects: ENVRIPlus
Agricultural and Food SciencesAGINFRA+ Projects: None
39 references, page 1 of 3

[9] Belloum, A.S.Z., Inda, M. A., Vasunin, D., Korkhov, V., Zhao, Z., Rauwerda, H., Breit, T., Bubak, M.T. & Hertzberger, B. (2011). Collaborative e-Science Experiments and Scientific Workflows. IEEE Internet Computing, 15(4), 39-47.

[10] Mark A. Miller, Wayne Pfeiffer, and Terri Schwartz. 2012. The CIPRES science gateway: enabling high-impact science for phylogenetics researchers with limited resources. In Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond (XSEDE '12). ACM, New York, NY, USA

[11] Environmental Research Infrastructure Cluster, EU project, www.envriplus.eu

[19] R. White and S. Drucker. Investigating behavioural variability in web search. In WWW, pages 21-30, 2007

[20] D. Downey, S. Dumais, and E. Horvitz. Models of searching and browsing: Languages, studies, and application. In Proc. IJCAI, pages 2740-2747, 2007.

[21] E. Agichtein, E. Brill, and S. Dumais. Improving web search ranking by incorporating user behaviour information. In Proc. SIGIR, pages 19-26, 2006. [OpenAIRE]

[22] P. Ingwersen and K. J¨arvelin. The turn: Integration of information seeking and retrieval in context, volume 18. Springer, 2005.

[23] J. Yu, R. Buyya, C. K. Tham, Cost-based scheduling of scientific workflow applications on utility grids, in: e-Science and Grid Computing, 2005. First International Conference on, IEEE, 2005, pp. 8-pp.

[24] S. Abrishami, M. Naghibzadeh, D. H. Epema, Deadlineconstrained workflow scheduling algorithms for infrastructure as a service clouds, Future Generation Computer Systems 29 (1) (2013) 158-169. [OpenAIRE]

[25] M. A. Rodriguez, R. Buyya, Deadline based resource provisioningand scheduling algorithm for scientific workflows on clouds, Cloud Computing, IEEE Transactions on 2 (2) (2014) 222-235.

[26] Z. Cai, X. Li, J. N. Gupta, Critical path-based iterative heuristic for workflow scheduling in utility and cloud computing, in: Service-Oriented Computing, Springer, 2013, pp. 207-221.

[27] Z. Cai, X. Li, J. N. Gupta, Heuristics for provisioning services to workflows in xaas clouds.

[28] Shadi Alawneh, Roelof Dragt, Dennis Peters, Claude Daley, Stephen Bruneau, "Hyper-Real-Time Ice Simulation and Modeling Using GPGPU", IEEE Transactions on Computers, vol.64, no. 12, pp. 3475-3487, Dec. 2015

[29] Zhao, Z., Albada, G.D. van & Sloot, P.M.A. (2005). Agentbased flow control for HLA components. International Journal of Simulation Transaction. 81(7), 487-501

[30] Ahmet Bulut, Nick Koudas, Anand Meka, Ambuj K. Singh, Divesh Srivastava, "Optimization Techniques for Reactive Network Monitoring", IEEE Transactions on Knowledge & Data Engineering, vol.21, no. 9, pp. 1343-1357, September 2009

39 references, page 1 of 3
Abstract
Data-centric approaches play an increasing role in many scientific domains, but in turn rely increasingly heavily on advanced research support environments for coordinating research activities, providing access to research data, and choreographing complex experiments. Critical time constraints can be seen in several application scenarios e.g., event detection for disaster early warning, runtime execution steering, and failure recovery. Providing support for executing such time critical research applications is still a challenging issue in many current research support environments however. In this paper, we analyse time critical requirements in three key kinds o...
Subjects
free text keywords: QA75, Virtual research environment, Research infrastructure, Time critical cloud applications, e-Infrastructure, real-time system
Related Organizations
Funded by
EC| VRE4EIC
Project
VRE4EIC
A Europe-wide Interoperable Virtual Research Environment to Empower Multidisciplinary Research Communities and Accelerate Innovation and Collaboration
  • Funder: European Commission (EC)
  • Project Code: 676247
  • Funding stream: H2020 | RIA
Validated by funder
,
EC| ENVRI PLUS
Project
ENVRI PLUS
Environmental Research Infrastructures Providing Shared Solutions for Science and Society
  • Funder: European Commission (EC)
  • Project Code: 654182
  • Funding stream: H2020 | RIA
Validated by funder
,
EC| SWITCH
Project
SWITCH
Software Workbench for Interactive, Time Critical and Highly self-adaptive cloud applications
  • Funder: European Commission (EC)
  • Project Code: 643963
  • Funding stream: H2020 | RIA
Validated by funder
Communities
CLARIN
Digital Humanities and Cultural HeritageDH-CH communities: CLARIN
EGI FederationEGI Projects: ENVRIPlus
Agricultural and Food SciencesAGINFRA+ Projects: None
39 references, page 1 of 3

[9] Belloum, A.S.Z., Inda, M. A., Vasunin, D., Korkhov, V., Zhao, Z., Rauwerda, H., Breit, T., Bubak, M.T. & Hertzberger, B. (2011). Collaborative e-Science Experiments and Scientific Workflows. IEEE Internet Computing, 15(4), 39-47.

[10] Mark A. Miller, Wayne Pfeiffer, and Terri Schwartz. 2012. The CIPRES science gateway: enabling high-impact science for phylogenetics researchers with limited resources. In Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond (XSEDE '12). ACM, New York, NY, USA

[11] Environmental Research Infrastructure Cluster, EU project, www.envriplus.eu

[19] R. White and S. Drucker. Investigating behavioural variability in web search. In WWW, pages 21-30, 2007

[20] D. Downey, S. Dumais, and E. Horvitz. Models of searching and browsing: Languages, studies, and application. In Proc. IJCAI, pages 2740-2747, 2007.

[21] E. Agichtein, E. Brill, and S. Dumais. Improving web search ranking by incorporating user behaviour information. In Proc. SIGIR, pages 19-26, 2006. [OpenAIRE]

[22] P. Ingwersen and K. J¨arvelin. The turn: Integration of information seeking and retrieval in context, volume 18. Springer, 2005.

[23] J. Yu, R. Buyya, C. K. Tham, Cost-based scheduling of scientific workflow applications on utility grids, in: e-Science and Grid Computing, 2005. First International Conference on, IEEE, 2005, pp. 8-pp.

[24] S. Abrishami, M. Naghibzadeh, D. H. Epema, Deadlineconstrained workflow scheduling algorithms for infrastructure as a service clouds, Future Generation Computer Systems 29 (1) (2013) 158-169. [OpenAIRE]

[25] M. A. Rodriguez, R. Buyya, Deadline based resource provisioningand scheduling algorithm for scientific workflows on clouds, Cloud Computing, IEEE Transactions on 2 (2) (2014) 222-235.

[26] Z. Cai, X. Li, J. N. Gupta, Critical path-based iterative heuristic for workflow scheduling in utility and cloud computing, in: Service-Oriented Computing, Springer, 2013, pp. 207-221.

[27] Z. Cai, X. Li, J. N. Gupta, Heuristics for provisioning services to workflows in xaas clouds.

[28] Shadi Alawneh, Roelof Dragt, Dennis Peters, Claude Daley, Stephen Bruneau, "Hyper-Real-Time Ice Simulation and Modeling Using GPGPU", IEEE Transactions on Computers, vol.64, no. 12, pp. 3475-3487, Dec. 2015

[29] Zhao, Z., Albada, G.D. van & Sloot, P.M.A. (2005). Agentbased flow control for HLA components. International Journal of Simulation Transaction. 81(7), 487-501

[30] Ahmet Bulut, Nick Koudas, Anand Meka, Ambuj K. Singh, Divesh Srivastava, "Optimization Techniques for Reactive Network Monitoring", IEEE Transactions on Knowledge & Data Engineering, vol.21, no. 9, pp. 1343-1357, September 2009

39 references, page 1 of 3
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