Abstract
In this paper, we propose a model-based methodology to evaluate the impact of the wireless network conditions on the robustness of performance of adaptive and non-adaptive networked mobile applications (apps). The methodology consists of three steps and it requires three different artefacts as inputs: the network model, the app behaviour model, and the performance model. To quantify robustness, two metrics (static and dynamic robustness) are proposed. The main challenge in evaluating robustness is the combinatorial growth of network-app interactions that need to be evaluated. To mitigate this issue, we propose an algorithm to limit the number of interactions, utilizing the monotonicity property of the performance model. To evaluate the dynamic robustness metric, the ability of the adaptive app to tolerate degraded network conditions has to be evaluated. This problem is formulated as a minimization problem. The methodology is used to evaluate the performance robustness of a mobile multimedia streaming app. The effectiveness of the proposed methodology is evaluated. The obtained results show three to five times reduction in total cost compared to the naive approach in which all combinations are exhaustively evaluated.
Original language | English |
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Title of host publication | Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017 |
Editors | Fernando G. Tinetti, Quoc-Nam Tran, Leonidas Deligiannidis, Mary Qu Yang, Mary Qu Yang, Hamid R. Arabnia |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 963-968 |
Number of pages | 6 |
ISBN (Electronic) | 9781538626528 |
DOIs | |
Publication status | Published - Dec 4 2018 |
Event | 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017 - Las Vegas, United States Duration: Dec 14 2017 → Dec 16 2017 |
Other
Other | 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017 |
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Country/Territory | United States |
City | Las Vegas |
Period | 12/14/17 → 12/16/17 |
Keywords
- adaptive
- configurable
- metrics
- wireless
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Safety, Risk, Reliability and Quality