Open Access

ARTICLE

Hybridizing Artificial Bee Colony with Bat Algorithm for Web Service Composition

Tariq Ahamed Ahanger^1,*, Fadl Dahan^2,3, Usman Tariq¹

1 Department of Management Information Systems, College of Business Administration, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia
2 Department of Management Information Systems, College of Business Administration-Hawtat Bani Tamim, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia
3 Department of Computer Sciences, Faculty of Computing and Information Technology Al-Turbah, Taiz University, Taiz, 9674, Yemen

* Corresponding Author: Tariq Ahamed Ahanger. Email:

Computer Systems Science and Engineering 2023, 46(2), 2429-2445. https://doi.org/10.32604/csse.2023.037692

Received 14 November 2022; Accepted 29 December 2022; Issue published 09 February 2023

Abstract

In the Internet of Things (IoT), the users have complex needs, and the Web Service Composition (WSC) was introduced to address these needs. The WSC’s main objective is to search for the optimal combination of web services in response to the user needs and the level of Quality of Services (QoS) constraints. The challenge of this problem is the huge number of web services that achieve similar functionality with different levels of QoS constraints. In this paper, we introduce an extension of our previous works on the Artificial Bee Colony (ABC) and Bat Algorithm (BA). A new hybrid algorithm was proposed between the ABC and BA to achieve a better tradeoff between local exploitation and global search. The bat agent is used to improve the solution of exhausted bees after a threshold (limits), and also an Elitist Strategy (ES) is added to BA to increase the convergence rate. The performance and convergence behavior of the proposed hybrid algorithm was tested using extensive comparative experiments with current state-of-the-art nature-inspired algorithms on 12 benchmark datasets using three evaluation criteria (average fitness values, best fitness values, and execution time) that were measured for 30 different runs. These datasets are created from real-world datasets and artificially to form different scale sizes of WSC datasets. The results show that the proposed algorithm enhances the search performance and convergence rate on finding the near-optimal web services combination compared to competitors. The Wilcoxon signed-rank significant test is used where the proposed algorithm results significantly differ from other algorithms on 100% of datasets.

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Keywords

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