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Model-based Assistance for Making Time/Fidelity Trade-offs in Component Compositions

Vishal Dwivedi, David Garlan, Jürgen Pfeffer and Bradley Schmerl.


In 11th International Conference on Information Technology : New Generations (ITNG 2014), Special track on: MDCBSE: Model-Driven, Component-Based Software Engineering, Las Vegas, NV, 7-9 April 2014.

Online links: PDF

Abstract
In many scientific fields, simulations and analyses require compositions of computational entities such as web services, programs, and applications. In such fields, users may want various trade-offs between different qualities. Examples include: (i) performing a quick approximation vs. an accurate, but slower, experiment, (ii) using local slower execution environments vs. remote, but advanced, computing facilities, (iii) using quicker approximation algorithms vs. computationally expensive algorithms with smaller data. However, such trade-offs are difficult to make as many such decisions today are either (a) wired into a fixed configuration and cannot be changed, or (b) require detailed systems knowledge and experimentation to determine what configuration to use. In this paper we propose an approach that uses architectural models coupled with automated design space generation for making fidelity and timeliness trade-offs. We illustrate this approach through an example in the intelligence analysis domain.

Keywords: Acme, End-user Architecture, Model Checking, Mult-fidelity Applications, Resource Aware Computing.  
@InProceedings{2014/Dwivedi/Mutlifidelity,
      AUTHOR = {Dwivedi, Vishal and Garlan, David and Pfeffer, J\"{u}rgen and Schmerl, Bradley},
      TITLE = {Model-based Assistance for Making Time/Fidelity Trade-offs in Component Compositions},
      YEAR = {2014},
      MONTH = {7-9 April},
      BOOKTITLE = {11th International Conference on Information Technology : New Generations (ITNG 2014), Special track on: MDCBSE: Model-Driven, Component-Based Software Engineering},
      ADDRESS = {Las Vegas, NV},
      PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/ITNGpaper.pdf},
      ABSTRACT = {In many scientific fields, simulations and analyses require compositions of computational entities such as web services, programs, and applications. In such fields, users may want various trade-offs between different qualities. Examples include: (i) performing a quick approximation vs. an accurate, but slower, experiment, (ii) using local slower execution environments vs. remote, but advanced, computing facilities, (iii) using quicker approximation algorithms vs. computationally expensive algorithms with smaller data. However, such trade-offs are difficult to make as many such decisions today are either (a) wired into a fixed configuration and cannot be changed, or (b) require detailed systems knowledge and experimentation to determine what configuration to use. In this paper we propose an approach that uses architectural models coupled with automated design space generation for making fidelity and timeliness trade-offs. We illustrate this approach through an example in the intelligence analysis domain.},
      KEYWORDS = {Acme, End-user Architecture, Model Checking, Mult-fidelity Applications, Resource Aware Computing}
}
    Created: 2013-11-04 08:39:50     Modified: 2014-05-02 09:35:01
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