Adaptive load balancing strategies in service composition for improved system performance

Wai Kent Low, R. Kanesaraj Ramasamy, Venushini Rajendran

Article ID: 8967
Vol 8, Issue 13, 2024

VIEWS - 30 (Abstract) 19 (PDF)

Abstract


Service composition enables the integration of multiple services to create new functionalities, optimizing resource utilization and supporting diverse applications in critical domains such as safety-critical systems, telecommunications, and business operations. This paper addresses the challenges in comparing load-balancing algorithms within service composition environments and proposes a novel dynamic load-balancing algorithm designed specifically for these systems. The proposed algorithm aims to improve response times, enhance system efficiency, and optimize overall performance. Through a simulated service composition environment, the algorithm was validated, demonstrating its effectiveness in managing the computational load of a BMI calculator web service. This dynamic algorithm provides real-time monitoring of critical system parameters and supports system optimization. In future work, the algorithm will be refined and tested across a broader range of scenarios to further evaluate its scalability and adaptability. By bridging theoretical insights with practical applications, this research contributes to the advancement of dynamic load balancing in service composition, offering practical implications for high-tech system performance.


Keywords


dynamic load balancing; service composition; least connection; service oriented architecture; round-robin; weight least connection

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References


A. Kanso and Y. Lemieux, “Achieving High Availability at the Application Level in the Cloud,” Jun. 2013. Available: https://www.researchgate.net/publication/259216367_Achieving_High_Availability_at_the_Application_Level_in_the_Cloud.

A. M. Alakeel, “A guide to dynamic load balancing in distributed computer systems,” International Journal of Computer Science and Information Security, vol. 10, no. 6, pp. 153-160, 2010.

C. Begau and G. Sutmann, “Adaptive dynamic load-balancing with irregular domain decomposition for particle simulations,” Computer Physics Communications, vol. 190, pp. 51-61, 2015, doi: 10.1016/j.cpc.2015.01.009.

Chawla, K. (2024). Reinforcement Learning-Based Adaptive Load Balancing for Dynamic Cloud Environments. arXiv preprint arXiv:2409.04896.

Chen, W., Zhu, Y., Liu, J., & Chen, Y. (2021). Enhancing mobile edge computing with efficient load balancing using load estimation in ultra-dense network. Sensors, 21(9), 3135.

D. Kanellopoulos and V. K. Sharma, “Dynamic Load Balancing Techniques in the IoT: A Review,” Symmetry, vol. 14, no. 12, p. 2554, 2022, doi: 10.3390/sym14122554.

D. Saxena and A. K. Singh, “A high availability management model based Tawfeeg, T. M., Yousif, A., Hassan, A., Alqhtani, S. M., Hamza, R., Bashir, M. B., & Ali, A. (2022). Cloud dynamic load balancing and reactive fault tolerance techniques: a systematic literature review (SLR). IEEE Access, 10, 71853-71873.

D. Thomson, “Application of Service Oriented Architecture to Distributed Simulation,” in AIAA Modeling and Simulation Technologies Conference and Exhibit, 2008, doi: 10.2514/6.2008-7091.

F. Aladwan, A. Alzghoul, E. Ali, H. Fakhouri, and I. Alzghoul, “Service Composition in Service Oriented Architecture: A Survey,” Modern Applied Science, vol. 12, no. 11, pp. 18-28, 2018, doi: 10.5539/mas.v12n12p18

G. Lokesh and K. K. Baseer, “An architecture for dynamic load balancing in cloud environment,” in 2023 2nd International Conference on Edge Computing and Applications (ICECAA), Namakkal, India, 2023, pp. 84-91, doi: 10.1109/ICECAA58104.2023.10212311.

Gupta, M. R., & Sharma, O. P. (2024). A Review exploration of Load Balancing Techniques in Cloud Computing. Educational Administration: Theory And Practice, 30(2), 580-590.

H. Wang, Y. Wang, G. Liang, Y. Gao, W. Gao, and W. Zhang, “Research on load balancing technology for microservice architecture,” MATEC Web of Conferences, vol. 336, p. 08002, 2021, doi: 10.1051/matecconf/202133608002.

H. Zeilinger and T. Anees, “SOA model for high availability of services,” Jun. 2013. Available: https://www.researchgate.net/publication/263926763_SOA_Model_for_High_Availability_of_Services.

He, H., Wang, L., Liu, J., & Qin, L. (2024). Optimizing Cloud Service Load Balancing Through Heat Conduction Equation Applications. International Journal of Heat & Technology, 42(1).

J. Giao, A. A. Nazarenko, D. Gonçalves, and J. Sarraipa, “A Framework for Service-Oriented Architecture (SOA)-Based IoT Application Development,” Processes, vol. 10, no. 9, p. 1782, 2022, doi: 10.3390/pr10091782.

J. S. Hurwitz, R. Bloor, M. Kaufman, and F. Halper, Service Oriented Architecture (SOA) For Dummies. John Wiley & Sons, 2009. Available: https://books.google.com.my/books?hl=en&lr=&id=8uM5pTncAO4C&oi=fnd&pg=PA3.

Khan, A. R. (2024). Dynamic Load Balancing in Cloud Computing: Optimized RL-Based Clustering with Multi-Objective Optimized Task Scheduling. Processes, 12(3), 519.

Lohumi, Y., Gangodkar, D., Srivastava, P., Khan, M. Z., Alahmadi, A., & Alahmadi, A. H. (2023). Load Balancing in Cloud Environment: A State-of-the-Art Review. IEEE Access, 11, 134517-134530.

M. H. Valipour, B. Amirzafari, K. N. Maleki, and N. Daneshpour, “A brief survey of software architecture concepts and service oriented architecture,” in 2009 2nd IEEE International Conference on Computer Science and Information Technology, Beijing, China, 2009, pp. 34-38, doi: 10.1109/ICCSIT.2009.5235004.

M. R. Mesbahi, A. M. Rahmani, and M. Hosseinzadeh, “Reliability and high availability in cloud computing environments: A reference roadmap,” Human-Centric Computing and Information Sciences, vol. 8, no. 1, p. 1-31, 2018, doi: 10.1186/s13673-018-0143-8.

M. Tsai and C. Wang, “Computing coordination-based fuzzy group decision-making (CC-FGDM) for web service oriented architecture,” Expert Systems with Applications, vol. 34, no. 4, pp. 2921-2936, 2008, doi: 10.1016/j.eswa.2007.05.017.

P.-W. Zhang, J.-X. Chen, and X.-Y. Jia, “A prediction based adaptive load balancing algorithm in SOA,” Microelectronics & Computer, vol. 28, no. 11, pp. 174-177, 2011. Available: http://www.journalmc.com/en/article/id/17b5cf43-c512-4d5a-b361-c564e29c6501.

P.-Y. Zhang, S. Y. Technology, and Nanjing, “Dynamic Web service composition,” Journal of Software, Nov. 2018. Available: https://www.jsjkx.com/CN/abstract/abstract8055.shtml.

Rajendran, V., Ramasamy, R. K., & Mohd-Isa, W. N. (2022). Improved eagle strategy algorithm for dynamic web service composition in the IoT: a conceptual approach. Future Internet, 14(2), 56.

Ramasamy, R. K., Chua, F. F., Haw, S. C., & Ho, C. K. (2022). WSFeIn: A Novel, Dynamic Web Service Composition Adapter for Cloud-Based Mobile Application. Sustainability, 14(21), 13946.

S. Namuye, L. Mutanu, G. Chege, and J. Macharia, “Leveraging health through the enhancement of information access using Mobile and service oriented technology,” in 2014 IST-Africa Conference Proceedings, Pointe aux Piments, Mauritius, 2014, pp. 1-9, doi: 10.1109/ISTAFRICA.2014.6880661

S. T. Waghmode and B. M. Patil, “Optimised and adaptive dynamic load balancing in the distributed database server,” in 7th International Conference on Computing in Engineering & Technology (ICCET 2022), Feb. 2022, pp. 145-149, doi: 10.1109/ICCET2022.9800278.

S. Wang, Y. Gong, G. Chen, Q. Sun, and F. Yang, “Service vulnerability scanning based on service-oriented architecture in Web service environments,” Journal of Systems Architecture, vol. 59, no. 9, pp. 731-739, 2013, doi: 10.1016/j.sysarc.2013.01.002.

Syed, D., Muhammad, G., & Rizvi, S. (2024). Systematic Review: Load Balancing in Cloud Computing by Using Metaheuristic Based Dynamic Algorithms. Intelligent Automation & Soft Computing, 39(3).

T. Wira Harjanti, H. Setiyani, and J. Trianto, “Load Balancing Analysis Using Round-Robin and Least-Connection Algorithms for Server Service Response Time,” Applied Technology and Computing Science Journal, vol. 5, no. 2, pp. 119-128, 2022, doi: 10.33086/atcsj.v5i2.3743.

V. Indhumathi and G. M. Nasira, “Service oriented architecture for load balancing with fault tolerant in grid computing,” in 2016 IEEE International Conference on Advances in Computer Applications (ICACA), 2016, pp. 313-317, doi: 10.1109/ICACA.2016.7887972.




DOI: https://doi.org/10.24294/jipd8967

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