Dynamic constraint satisfaction algorithm for online feature model reconfiguration

Date

2019-07-01

Author

Oğuztüzün, Mehmet Halit S.
Entekhabi, Sina

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

133
views

0
downloads

Dynamically reconfigurable systems are able to respond to changes in their operational environments by reconfiguring themselves automatically. Dynamic software product lines are dynamically reconfigurable systems with an explicit variability model that guides the reconfiguration. In this work, feature models are used as the variability model. An emerging situation in the environment can lead to some relevant changes to the current configuration: some features must be activated, and some must be deactivated. Due to constraint propagation, the status of other features might need to be changed as well. However, considering the feature state migration cost, one would like to mitigate the cost to the greatest extent possible. Furthermore, the configuration with a proper cost has to be reached in an acceptable time. In this paper, we devised a set of feature model heuristics for a constraint satisfaction problem algorithm that considers the efficiency and the cost of feature state changes to be applied to the current configuration while confronting the changes in the environment so that the requirements of the new situation will be efficiently satisfied with the minimum cost.

Subject Keywords

Heuristics, Dynamic software product line, Dynamic algorithm, Online reconfiguration, Feature Model

URI

https://hdl.handle.net/11511/36900

DOI

https://doi.org/10.1109/ceit.2018.8751750

Conference Name

6th International Conference on Control Engineering and Information Technology (CEIT)

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Dynamic constraint satisfaction algorithm for reconfiguration of feature models Entekhabi, Sina; Oğuztüzün, Mehmet Halit S.; Department of Computer Engineering (2018) Dynamically reconfigurable systems are able to respond to changes in their operational environments by reconfiguring themselves automatically. Dynamic software product lines are dynamically reconfigurable systems with an explicit variability model that guides the reconfiguration. In this work, feature models are used as the variability model. Features are assumed to be mapped to system's components that realize them. A feature model corresponds to a constraint satisfaction problem (CSP), and determines the ...
An incremental constraint satisfaction algorithm for dynamic reconfiguration Entekhabi, Sina; Karataş, Ahmet Serkan; Oğuztüzün, Mehmet Halit S. (null; 2017-05-08) Dynamically reconfigurable systems are able to respond to changes in their operational environment by reconfiguring themselves automatically. Dynamic software product lines are dynamically reconfigurable systems with an explicit model of variability, which plays a key role in the reconfiguration process. In our work we use feature models for modeling variability. Features are mapped to the system’s components that realize them. The feature model corresponds to a constraint logic program, and determines the ...
Dynamic Scoring-Based Sequence Alignment for Process Diagnostics Esgin, Eren; Karagöz, Pınar (2015-06-12) Even though process-aware information systems are intensively utilized in the organizations, traditional process management paradigms majorly concentrate on the design and configuration phases. Instead of starting with a process design, process mining attempts to discover interesting patterns from process enactment namely event logs and extract business processes by distilling these event logs as knowledge base. One of the challenging issues in process mining domain is process diagnostics, which is complex ...
Hypothesis-driven simulation experiments with an extension to SED-ML Cam, S.; Oğuztüzün, Mehmet Halit S.; Yilmaz, L. (2022-03-01) Most of the frameworks or assistance systems for experiment specification do not provide a process explicitly based on formally specified hypotheses. This deficiency leads to inaccurate or insufficient record of an experiment, decreasing the trustworthiness and reproducibility of the experiment. Moreover, the wide variety of models, metamodels, tools, and data for experimentation requires Global Model Management (GMM) that is utilizing Model-Driven Engineering techniques, facilitates documentation, sharing,...
Stochastic dynamic programming based resource allocation for multi target tracking for electronically steered antenna radar / Uzun, Çağlar; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2015) In this work, the concept of sensor management is introduced and stochastic dynamic programming based resource allocation approach is proposed to track multiple targets. The core of this approach is to use Lagrange relaxation for decreasing the state space dimension. By this approximation, the overall problem is separated into components instead of using joint Markov model to optimize large scale stochastic control problem. The aim of this study is to adaptively allocate radar resources in an optimal way in...

Citation Formats

M. H. S. Oğuztüzün and S. Entekhabi, “Dynamic constraint satisfaction algorithm for online feature model reconfiguration,” presented at the 6th International Conference on Control Engineering and Information Technology (CEIT), Istanbul, TURKEY, 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36900.