TY - GEN
T1 - Performance Robustness Evaluation of Mobile Networked Applications
AU - Al-Tekreeti, Mustafa
AU - Naik, Kshirasagar
AU - Abdrabou, Atef
AU - Zaman, Marzia
AU - Srivastava, Pradeep
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/12/4
Y1 - 2018/12/4
N2 - 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.
AB - 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.
KW - adaptive
KW - configurable
KW - metrics
KW - wireless
UR - http://www.scopus.com/inward/record.url?scp=85060591212&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060591212&partnerID=8YFLogxK
U2 - 10.1109/CSCI.2017.350
DO - 10.1109/CSCI.2017.350
M3 - Conference contribution
AN - SCOPUS:85060591212
T3 - Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
SP - 963
EP - 968
BT - Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
A2 - Tinetti, Fernando G.
A2 - Tran, Quoc-Nam
A2 - Deligiannidis, Leonidas
A2 - Yang, Mary Qu
A2 - Yang, Mary Qu
A2 - Arabnia, Hamid R.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
Y2 - 14 December 2017 through 16 December 2017
ER -