ارائه الگوریتم چندهدفه بهبودیافته به منظور انتخاب بهینه در ترکیب وب‌سرویس‌های آگاه به کیفیت در اینترنت اشیا

چکیده مقاله :

با ظهور اینترنت اشیا، مسئله ترکیب وب‌سرویس‌ها و برآورده‌کردن نیازهای متعدد و پیچیده از سوی کاربران بیش از پیش مورد توجه قرار گرفته است. به منظور ارائه خدمت به برنامه‌های کاربردی سیستم‌های مبتنی بر اینترنت اشیا، کاندیداهای متفاوتی با ویژگی‌های کیفی گوناگون وجود دارند. بنابراین یک چالش اساسی، انتخاب یک ترکیب بهینه از میان این کاندیداها به عنوان یک مسئله NP-hard است. در این مقاله، راه‌حل نزدیک به بهینه برای حل مسئله ترکیب وب‌سرویس در اینترنت اشیا و یافتن جبهه بهینه پارتو با استفاده از الگوریتم جستجوی فراابتکاری چندهدفه NSGA-III ارائه شده و سپس به منظور افزایش کیفیت و تنوع راه‌حل‌ها، الگوریتم بهبودیافته‌ای با ترکیب الگوریتم NSGA-III و تابع برازندگی جدید پیشنهاد گردیده است. به منظور بهینه‌سازی ترکیب سرویس‌ها در الگوریتم پیشنهادی از 9 پارامتر کیفی استفاده شده و در ادامه برای عملکرد بهتر به سه هدف اصلی تبدیل شده‌اند. نتایج آزمایش‌ها نشان می‌دهند که رویکرد پیشنهادی از نظر میانگین دو هدف از سه هدف در مقایسه با الگوریتم NSGA-III نتیجه بهتری دارد. همچنین از نظر شاخص‌های عملکردی توانسته به طور میانگین به 11 درصد پوشش بیشتر دست یابد و هم از لحاظ توزیع راه‌حل‌ها و هم از لحاظ پراکندگی نسبت به سایر الگوریتم‌ها عملکرد بهتری داشته باشد.

چکیده انگلیسی :

The emergence of the Internet of Things (IoT) has intensified the focus on web service composition and the fulfillment of increasingly complex and diverse user requirements. IoT-based systems often encounter numerous service candidates with varying qualitative attributes, presenting a significant challenge in selecting an optimal combination. This problem, categorized as NP-hard, requires efficient approaches for resolution. This study proposes a near-optimal solution for web service composition in IoT environments by leveraging the NSGA-III multi-objective metaheuristic algorithm to identify the optimal Pareto front. To further enhance the quality and diversity of the solutions, an improved algorithm integrating NSGA-III with a novel fitness function is introduced. The proposed approach optimizes service composition using nine quality parameters, which are subsequently streamlined into three principal objectives for better computational efficiency. Experimental evaluations demonstrate that the proposed method outperforms the baseline NSGA-III algorithm in terms of the average performance of two out of three objectives. Additionally, the approach achieves an average of 11% higher coverage based on performance indices and exhibits superior solution distribution and dispersion compared to alternative algorithms.

منابع و مأخذ:

[1] D. Prajapati and K. Bhargavi, "Old-age health risk prediction and maintenance via IoT devices and artificial neural network," in Proc. of the 6th Int. Conference on FICTA, pp. 373-381 Bhubaneswar, India, 14-16 Oct. 2017.
[2] Y. Wu, W. Jin, J. Ren, and Z. Sun, "A multi-perspective architecture for high-speed train fault diagnosis based on variational mode decomposition and enhanced multi-scale structure," Applied Intelligence, vol. 49, no. 11, pp. 3923-3937, 2019.
[3] P. Asghari, A. M. Rahmani, and H. H. S. Javadi, "Service composition approaches in IoT: a systematic review," J. of Network and Computer Applications, vol. 120, pp. 61-77, Oct. 2018.
[4] N. Kashyap, A. C. Kumari, and R. Chhikara, "Multi-objective optimization using NSGA II for service composition in IoT," Procedia Computer Science, vol. 167, pp. 1928-1933, 2020.
[5] A. C. Kumari, K. Srinivas, and M. P. Gupta, "Multi-objective test suite minimisation using quantum-inspired multi-objective differential evolution algorithm," in Proc. IEEE Int. Conf. on Computational Intelligence and Computing Research, 7 pp., Coimbatore, India, 18-20 Dec. 2012.
[6] M. E. Khanouche, Y. Amirat, A. Chibani, M. Kerkar, and A. Yachir, "Energy-centered and QoS-aware services selection for Internet of Things," IEEE Trans. on Automation Science and Engineering, vol. 13, no. 3, pp. 1256-1269, Jul. 2016.
[7] Q. Li, R. Dou, F. Chen, and G. Nan, "A QoS-oriented web service composition approach based on multi-population genetic algorithm for Internet of Things," International J. of Computational Intelligence Systems, vol. 7, no. sup. 2, pp. 26-34, Jul. 2014.
[8] A. Souri, A. M. Rahmani, N. J. Navimipour, and R. Rezaei, "Formal modeling and verification of a service composition approach in the social customer relationship management system," Information Technology & People, vol. 32, no. 6, pp. 1591-1607, Nov. 2019.
[9] L. J. Zhang, J. Zhang, and H. Cai, "Service-oriented architecture," In: Services Computing, pp. 89-113, Springer, Berlin, Heidelberg, 2007.
[10] A. Strunk, "QoS-aware service composition: a survey," in Proc. 8th IEEE European Conf. on Web Services, pp. 67-74, Ayia Napa, Cyprus, 1-3 Dec. 2010.
[11] Z. Brahmi and M. M. Gammoudi, "QoS-aware automatic web service composition based on cooperative agents," in Proc. Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, pp. 27-32, Hammamet, Tunisia, 17-20 Jun. 2013.
[12] P. Asghari, A. M. Rahmani, and H. H. S. Javadi, "Privacy-aware cloud service composition based on QoS optimization in Internet of Things," J. of Ambient Intelligence and Humanized Computing, vol. 13, no. 11, pp. 5295-5320, 2022.
[13] D. B. Claro, P. Albers, and J. K. Hao, "Selecting web services for optimal composition," in Proc. Second Int. Workshop on Semantic and Dynamic Web Processes, 14 pp., Orlando, FL, USA, 11-11 Jul. 2005.
[14] L. Li, P. Yang, L. Ou, Z. Zhang, and P. Cheng, "Genetic algorithm-based multi-objective optimisation for QoS-aware web services composition," in Proc. 4th Int. Conf. on Knowledge Science, Engineering and Management, pp. 549-554, Belfast, Northern Ireland, UK, 1-3 Sept. 2010.
[15] Y. Yao and H. Chen, "A rule-based web service composition approach," in Proc. 6th Int. Conf. on Autonomic and Autonomous Systems, pp. 150-155, Cancun, Mexico, 7-13 Mar. 2010.
[16] K. Hashmi, A. Alhosban, E. Najmi, and Z. Malik, "Automated web service quality component negotiation using NSGA-2," in Proc. ACS Int. Conf. on Computer Systems and Applications, 6 pp., Ifrane, Morocco, 27-30 May 2013.
[17] Y. Yao and H. Chen, "QoS-aware service composition using NSGA-II1," in Proc. of the 2nd Int. Conf. on Interaction Sciences: Information Technology, Culture and Human, pp. 358-363, Seoul, Korea, 24-26, Nov. 2009.
[18] P. Sharifara, A. Yari, and M. M. R. Kashani, "An evolutionary algorithmic based web service composition with quality of service," in Proc. 7th Int. Symp. on Telecommunications, pp. 61-65, Tehran, Iran, 9-11 Sept. 2014.
[19] L. Liu and M. Zhang, "Multi-objective optimization model with AHP decision-making for cloud service composition," KSII Trans. on Internet and Information Systems, vol. 9, no. 9, pp. 3293-3311, Sept. 2015.
[20] L. B. Said, S. Bechikh, and K. Ghédira, "The r-dominance: a new dominance relation for interactive evolutionary multicriteria decision making," IEEE Trans. on Evolutionary Computation, vol. 14, no. 5, pp. 801-818, Oct. 2010.
[21] J. Molina, L. V. Santana, A. G. Hernández-Díaz, C. A. C. Coello, and R. Caballero, "g-dominance: reference point based dominance for multiobjective metaheuristics," European J. of Operational Research, vol. 197, no. 2, pp. 685-692, Sept. 2009.
[22] J. H. Zheng and Z. Z. Xie, "A study on how to use angle information to include decision maker's preferences," Acta Electonica Sinica, vol. 42, no. 11, pp. 2239-2246, 2014.
[23] T. Ecarot, D. Zeghlache, and C. Brandily, "Consumer-and-provider-oriented efficient IaaS resource allocation," in Proc. IEEE Int. Parallel and Distributed Processing Symp. Workshops, pp. 77-85, Lake Buena Vista, FL, USA. 29 May- 2 Jun. 2017.
[24] Y. Li, Y. Kou, and Z. Li, "An improved nondominated sorting genetic algorithm III method for solving multiobjective weapon-target assignment part i: the value of fighter combat," International J. of Aerospace Engineering, Article ID: 8302324, 23 pp., 2018.
[25] P. Thangaraj and P. Balasubramanie, "Meta heuristic QoS based service composition for service computing," J. of Ambient Intelligence and Humanized Computing, vol. 12, no. 5, pp. 5619-5625, May 2021.
[26] F. Dahan, W. Binsaeedan, M. Altaf, M. S. Al-Asaly, and M. M. Hassan, "An efficient hybrid metaheuristic algorithm for QoS-aware cloud service composition problem," IEEE Access, vol. 9, pp. 95208-95217, 2021.
[27] B. Santoshkumar, K. Deb, and L. Chen, "Eliminating non-dominated sorting from NSGA-III," in Proc. 12th Int. Conf. on Evolutionary Multi-Criterion Optimization, pp. 71-85, Leiden, the Netherlands, Mar. 2023, 20-24 Mar. 2023.
[28] H. Nazif, M. Nassr, H. M. R. Al-Khafaji, N. Jafari Navimipour, and M. Unal, "A cloud service composition method using a fuzzy-based particle swarm optimization algorithm," Multimedia Tools and Applications, vol. 83, no. 19, pp. 1-28, Dec. 2023.
[29] Z. Brahmi and A. Selmi, "Coordinate system-based trust-aware web services composition in edge and cloud environment," The Computer J., vol. 66, no. 9, pp. 2102-2117, Sept. 2023.