Cloud-based e-Infrastructure for scheduling astronomical observations

James Patrick Wetter; Ozgur Akgun; Adam David Barker; Martin Dominik; Ian James Miguel; Blesson Varghese

doi:10.1109/eScience.2015.54

Cloud-based e-Infrastructure for scheduling astronomical observations

James Patrick Wetter, Ozgur Akgun, Adam David Barker, Martin Dominik, Ian James Miguel, Blesson Varghese

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Gravitational microlensing exploits a transient phenomenon where an observed star is brightened due to deflection of its light by the gravity of an intervening foreground star. It is conjectured that this technique can be used to measure
the abundance of planets throughout the Milky Way. In order to undertake efficient gravitational microlensing an observation schedule must be constructed such that various targets are observed while undergoing a microlensing event. In this paper, we propose a cloud-based e-Infrastructure that currently supports
four methods to compute candidate schedules via the application of local search and probabilistic meta-heuristics. We then validate the feasibility of the e-Infrastructure by evaluating the methods on historic data. The experiments demonstrate that the use of on-demand cloud resources for the e-Infrastructure can allow better schedules to be found more rapidly.

Original language	English
Title of host publication	2015 IEEE 11th International Conference on e-Science (e-Science) (2015)
Publisher	IEEE Computer Society
Pages	362-370
DOIs	https://doi.org/10.1109/eScience.2015.54
Publication status	Published - 31 Aug 2015
Event	11th IEEE International Conference on eScience - Ludwig-Maximilians-Universität , Munich, Germany Duration: 31 Aug 2015 → 4 Sept 2015 http://escience2015.mnm-team.org/

Conference

Conference	11th IEEE International Conference on eScience
Country/Territory	Germany
City	Munich
Period	31/08/15 → 4/09/15
Internet address	http://escience2015.mnm-team.org/

Access to Document

10.1109/eScience.2015.54

scheduling
© 2015. IEEE. This is the accepted manuscript of a conference paper originally submitted to the 11th IEEE International Conference on eScience available from http://www.computer.org/csdl/proceedings/escience/index.html
Accepted author manuscript, 1.49 MB

Cite this

@inproceedings{3881455b36054960a6bae0910108ab95,

title = "Cloud-based e-Infrastructure for scheduling astronomical observations",

abstract = "Gravitational microlensing exploits a transient phenomenon where an observed star is brightened due to deflection of its light by the gravity of an intervening foreground star. It is conjectured that this technique can be used to measurethe abundance of planets throughout the Milky Way. In order to undertake efficient gravitational microlensing an observation schedule must be constructed such that various targets are observed while undergoing a microlensing event. In this paper, we propose a cloud-based e-Infrastructure that currently supportsfour methods to compute candidate schedules via the application of local search and probabilistic meta-heuristics. We then validate the feasibility of the e-Infrastructure by evaluating the methods on historic data. The experiments demonstrate that the use of on-demand cloud resources for the e-Infrastructure can allow better schedules to be found more rapidly.",

author = "Wetter, {James Patrick} and Ozgur Akgun and Barker, {Adam David} and Martin Dominik and Miguel, {Ian James} and Blesson Varghese",

note = "This research was pursued under the EPSRC grant {\textquoteleft}Working Together: Constraint Programming and Cloud Computing{\textquoteright} (EP/K015745/1) and an Amazon Web Services (AWS) Education Research Grant. ; 11th IEEE International Conference on eScience ; Conference date: 31-08-2015 Through 04-09-2015",

year = "2015",

month = aug,

day = "31",

doi = "10.1109/eScience.2015.54",

language = "English",

pages = "362--370",

booktitle = "2015 IEEE 11th International Conference on e-Science (e-Science) (2015)",

publisher = "IEEE Computer Society",

address = "United States",

url = "http://escience2015.mnm-team.org/",

}

Wetter, JP, Akgun, O, Barker, AD, Dominik, M , Miguel, IJ & Varghese, B 2015, Cloud-based e-Infrastructure for scheduling astronomical observations. in 2015 IEEE 11th International Conference on e-Science (e-Science) (2015). IEEE Computer Society, pp. 362-370, 11th IEEE International Conference on eScience, Munich, Germany, 31/08/15. https://doi.org/10.1109/eScience.2015.54

TY - GEN

T1 - Cloud-based e-Infrastructure for scheduling astronomical observations

AU - Wetter, James Patrick

AU - Akgun, Ozgur

AU - Barker, Adam David

AU - Dominik, Martin

AU - Miguel, Ian James

AU - Varghese, Blesson

N1 - This research was pursued under the EPSRC grant ‘Working Together: Constraint Programming and Cloud Computing’ (EP/K015745/1) and an Amazon Web Services (AWS) Education Research Grant.

PY - 2015/8/31

Y1 - 2015/8/31

N2 - Gravitational microlensing exploits a transient phenomenon where an observed star is brightened due to deflection of its light by the gravity of an intervening foreground star. It is conjectured that this technique can be used to measurethe abundance of planets throughout the Milky Way. In order to undertake efficient gravitational microlensing an observation schedule must be constructed such that various targets are observed while undergoing a microlensing event. In this paper, we propose a cloud-based e-Infrastructure that currently supportsfour methods to compute candidate schedules via the application of local search and probabilistic meta-heuristics. We then validate the feasibility of the e-Infrastructure by evaluating the methods on historic data. The experiments demonstrate that the use of on-demand cloud resources for the e-Infrastructure can allow better schedules to be found more rapidly.

AB - Gravitational microlensing exploits a transient phenomenon where an observed star is brightened due to deflection of its light by the gravity of an intervening foreground star. It is conjectured that this technique can be used to measurethe abundance of planets throughout the Milky Way. In order to undertake efficient gravitational microlensing an observation schedule must be constructed such that various targets are observed while undergoing a microlensing event. In this paper, we propose a cloud-based e-Infrastructure that currently supportsfour methods to compute candidate schedules via the application of local search and probabilistic meta-heuristics. We then validate the feasibility of the e-Infrastructure by evaluating the methods on historic data. The experiments demonstrate that the use of on-demand cloud resources for the e-Infrastructure can allow better schedules to be found more rapidly.

UR - http://www.computer.org/csdl/proceedings/escience/index.html

U2 - 10.1109/eScience.2015.54

DO - 10.1109/eScience.2015.54

M3 - Conference contribution

SP - 362

EP - 370

BT - 2015 IEEE 11th International Conference on e-Science (e-Science) (2015)

PB - IEEE Computer Society

T2 - 11th IEEE International Conference on eScience

Y2 - 31 August 2015 through 4 September 2015

ER -

Cloud-based e-Infrastructure for scheduling astronomical observations

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Working Together in ICT: Working Together: Constraint Programming and Cloud Computing

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Cloud-based e-Infrastructure for scheduling astronomical observations

Abstract

Conference

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Working Together in ICT: Working Together: Constraint Programming and Cloud Computing

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