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A Self-adaptive System reconfiguring a Composite Web Service for Emergency Medical Aid

Navinderjit Kaur Kahlon1

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-1 , Page no. 338-343, Jan-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i1.338343

Online published on Jan 31, 2019

Copyright © Navinderjit Kaur Kahlon . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Navinderjit Kaur Kahlon, “A Self-adaptive System reconfiguring a Composite Web Service for Emergency Medical Aid,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.338-343, 2019.

MLA Style Citation: Navinderjit Kaur Kahlon "A Self-adaptive System reconfiguring a Composite Web Service for Emergency Medical Aid." International Journal of Computer Sciences and Engineering 7.1 (2019): 338-343.

APA Style Citation: Navinderjit Kaur Kahlon, (2019). A Self-adaptive System reconfiguring a Composite Web Service for Emergency Medical Aid. International Journal of Computer Sciences and Engineering, 7(1), 338-343.

BibTex Style Citation:
@article{Kahlon_2019,
author = {Navinderjit Kaur Kahlon},
title = {A Self-adaptive System reconfiguring a Composite Web Service for Emergency Medical Aid},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2019},
volume = {7},
Issue = {1},
month = {1},
year = {2019},
issn = {2347-2693},
pages = {338-343},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3508},
doi = {https://doi.org/10.26438/ijcse/v7i1.338343}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i1.338343}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3508
TI - A Self-adaptive System reconfiguring a Composite Web Service for Emergency Medical Aid
T2 - International Journal of Computer Sciences and Engineering
AU - Navinderjit Kaur Kahlon
PY - 2019
DA - 2019/01/31
PB - IJCSE, Indore, INDIA
SP - 338-343
IS - 1
VL - 7
SN - 2347-2693
ER -

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Abstract

The web services run in a highly dynamic environment so, the most fundamental challenges in web services based software solutions is to manage QoS changes of their component web services at runtime. In order to make the composite web service adapt to these changes, a self adaptive system is proposed for web service composition. The distributed approach is followed at the client and the server side along with the runtime monitoring and adaptation of the component web services at the provider side. For the self adaptive systems to recover as quickly as possible, a way of performance prediction is proposed in this paper along with the case study and the performance of the system. The prototype is developed using Java, and the JADE platform is used for implementing software agents using hospital lookup case study. The experimental results show that the proposed solution has better performance for supporting self adaptive web service composition.

Key-Words / Index Term

Self-adaptive systems; Web services; Quality of Service (QoS) and Web Service Composition

References

[1] V. Agarwal, & P. Jalote, “Enabling end-to-end support for non-functional properties in web services”, 2009 IEEE International Conference on Service-Oriented Computing and Applications (SOCA) , pp 1 – 8, 2009.
[2] A. Amin, A. Colman, & L. Grunske,”Statistical detection of qos violations based on cusum control charts”. In Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering, ACM., pp. 97-108, 2012.
[3] R. Angarita, Y. Cardinale, & M. Rukoz, “Reliable Composite Web Services Execution: Towards a Dynamic Recovery Decision”, Electronic Notes in Theoretical Computer Science Volume 302, Proceedings of the XXXIX Latin American Computing Conference (CLEI 2013) , pp 5-28, 2014.
[4] R. Angarita, “Responsible objects: Towards self-healing internet of things applications”,2015 IEEE International Conference on Autonomic Computing (ICAC). IEEE., pp. 307-312, 2015, July.
[5] R. Angarita, M. Rukoz, & Y. Cardinale, “Modeling dynamic recovery strategy for composite web services execution”, World Wide Web, 19(1), pp 89-109, 2016.
[6] D. Ardagna, M. Comuzzi, E. Mussi, B. Pernici, & P. Plebani, “PAWS: A Framework for Executing Adaptive Web-Service Processes”, IEEE software, 24(6) , 39, 2007.
[7] S. Asadollah, & T. Chiew, “Web Service Response Time Monitoring: Architecture and Validation”, Theoretical and Mathematical Foundations of Computer Science Volume 164 of the series Communications in Computer and Information Science , pp 276-282, 2011.
[8] R. Aschoff, & A. Zisman, “QoS-Driven proactive adaptation of service composition”, Service-Oriented Computing, Lecture Notes in Computer Science, Volume 7084 2011 , pp 421-435, 2011.
[9] L. Baresi, & S. Guinea, “Towards Dynamic Monitoring of WS-BPEL Processes”. Service-Oriented Computing - ICSOC 2005 Volume 3826 of the series Lecture Notes in Computer Science , pp 269-282, 2005.
[10] Y. Dai, L. Yang, & B. Zhang, “QoS-driven self-healing web service composition based on performance prediction”, Journal of Computer Science and Technology, 24(2), pp 250-261, 2009.
[11] D. H. Elsayed, E. S. Nasr, M. Alaa El Din, & M. H. Gheith, “Appraisal and Analysis of Various Self-Adaptive Web Service Composition Approaches”, In Requirements Engineering for Service and Cloud Computing, Springer International Pub , pp. 229-246, 2017.
[12] Q. He, J. Han, Y. Yang, H. Jin, J.G. Schneider, & S. Versteeg, “Formulating cost-effective monitoring strategies for service-based systems”, IEEE Transactions on Software Engineering, 40(5). IEEE Transactions on Software Engineering, 40(5), pp 461-482, 2014.
[13] J. S. Hunter, “The Exponentially Weighted Moving Average”, Journal of Quality Technology, Vol. 18, No. 4 , pp 203-210, 1986.
[14] C. L. Hwang, & K. Yoon, “Multiple attribute decision making Methods and applications”, CRC press, 1981.
[15] N.K. Kahlon, K.K. Chahal, & S.B. Narang, “Managing QoS degradation of partner web services: A proactive and preventive approach”, Journal of Service Science Research, 8(2) , pp 131-159, 2016.
[16] Q. Liang, B. Lee, & P.Hung, “A rule-based approach for availability of service by automated service substitution”. Softw., Pract. Exper. 44(1) , pp 47-76, 2014.
[17] H. Mansour, & T. Dillon, “Dependability and Rollback Recovery for Composite Web Services”, IEEE Transactions on Services Computing, Volume: 4, Issue: 4 , pp 328-339, Oct.-Dec. 2011.
[18] A. Metzger, C. H. Chi, Y. Engel, & A. Marconi, “Research challenges on online service quality prediction for proactive adaptation”, 2012 Workshop on EuropeanSoftware Services and Systems Research - Results and Challenges (S-Cube), pp 51 – 57, 2012.
[19] A. Michlmayr, F. Rosenberg, P. Leitner, & S. Dustdar, “Comprehensive QoS monitoring of Web services and event-based SLA violation detection”, Proceeding MWSOC `09 Proceedings of the 4th International Workshop on Middleware for Service Oriented Computing, ACM New York, NY, USA , pp 1-6, 2009.
[20] M. Natrella, NIST/SEMATECH e-Handbook of Statistical Methods, 2010.
[21] M. Oriol, X. Franch, & J. Marco, “Monitoring the service-based system lifecycle with SALMon”, Expert Systems with Applications, 42(19) , pp 6507-6521, 2015.
[22] P. Plebani, & B. Pernici, “URBE: Web service retrieval based on similarity evaluation”, IEEE Transactions on Knowledge and Data Engineering, 21(11), pp 1629-1642, 2009.
[23] K. Ren, J. Song, M. Zhu, & N. Xiao, “A bargaining-driven global QoS adjustment approach for optimizing service composition execution path”, The Journal of Supercomputing, Volume 63 (1), pp 126–149, 2013.
[24] F. Rosenberg, C. Platzer, & S. Dustdar, “Bootstrapping Performance and Dependability Attributes of Web Services”, In Proceedings of the IEEE International Conference on Web Services (ICWS’06),pp. 205–212, 2006.
[25] F. Rosenberg, C. Platzer, & S. Dustdar, “QUATSCH–A QoS Evaluation and Monitoring Tool for Web Services” Journal on Web services Research, 2007.
[26] J. Ruiz, & C. Rubira, “Quality of Service Conflict During Web Service Monitoring: A Case Study”, Electronic Notes in Theoretical Computer Science, 321 , pp 113-127, 2016.
[27] Z. Zheng, & M. Lyu, “A runtime dependability evaluation framework for fault tolerant web services”, In The International Workshop on Proactive Failure Avoidance, Recovery and Maintenance (PFARM`09), co-located with DSN2009, 2009.
[28] J. Zhu, P. He, Z. Zheng, & M. Lyu, “Online QoS Prediction for Runtime Service Adaptation via Adaptive Matrix Factorization”, IEEE Transactions on Parallel and Distributed Systems, IEEE, 2017.