An Enhanced Energy-Efficient Web Service Composition Algorithm Based on the Firefly Algorithm

An Enhanced Energy-Efficient Web Service Composition Algorithm Based on the Firefly Algorithm

Yifei Xue, Jian Wang, Weipeng Jing
Copyright: © 2023 |Pages: 19
DOI: 10.4018/JDM.321740
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Abstract

Numerous web services with the same function but different service qualities are constantly emerging on the network. Optimizing web service composition based on multiple candidate services sets an urgent problem in the service composition neighborhood. This paper modifies the traditional Firefly algorithm and adds exchange and mutation mechanisms to optimize the Web service composition efficiently in multiple candidate service sets. Meanwhile, it discretizes the continuous space of its solution set and better adapts to the service composition optimization problem. Experimental results show that compared with the GA, IA, SA, ACO, FACO, and EFACO algorithms, this algorithm has better optimization performance, faster speed, and higher energy efficiency for solving service composition optimization problems in the case of large-scale data. The higher the combined complexity of the solution, the stronger the performance compared to other algorithms. It can better deal with the increasingly complex situation of Web service composition problems.
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Introduction

With the development of the information age, data is generated faster and faster, forming big data, which has brought a revolutionary product to many industries. Compared with the previous relational database management system, big data processing and storage are complicated, and the system's energy consumption increases a lot, which burdens the system (Meyer & Weske, 2006; Yaghoubi et al., 2020). As the infrastructure layer of the extensive data system, the cloud computing platform can meet this challenge to a certain extent. Cloud services are quantifiable IT services provided externally under the cloud computing architecture (Meyer & Weske, 2006; Yaghoubi et al., 2020). Cloud services are more convenient, low deployment cost, and highly open compared to traditional services (Ramalingam & Mohan, 2021). Web services are one of the cloud services. Web service is a kind of Web application, which is self-contained, self-describing, and modular, and can be published, searched, and invoked through the Web (Tsalgatidou & Pilioura, 2002). Using Web services can realize cross-platform interaction or integration of heterogeneous applications on the Internet, which provides excellent convenience for existing service providers and users (Al-Masri & Mahmoud, 2008). More and more enterprises and users are now beginning to deploy their software, systems, computing resources as Web services.

Web services adopt a service-oriented architecture(SOA), which implements service invocation through the interaction between service providers, requesters, and registry entities (Atkinson et al., 2002; Li et al., 2007; Marcelo Fantinato et al., 2021). The service provider (server) provides services that satisfy the requirements based on the initial query of the service requester (client or user) in the “service discovery” phase. These services are published in the registry; then, the service requester is registered. The center finds and binds the “best” Web service that fits its conditions (Haddad et al., 2010). The service providers consider the user’s needs and select the “best” Web service. More importantly, consider the quality of service (QoS) of Web services.

In the natural environment, many Web services can provide the same function. The difference is that their quality of service is uneven, good and bad. For example, when booking a flight or downloading music, many service providers can support similar services. However, their quality is different, and users will choose a service with fast response speed, high reliability, and low energy consumption. High-quality Web service will contribute to solid competitiveness for service providers.

Nowadays, the demands of users are becoming more and more complex. Web services with a single function can no longer fit the requirements of users. Service providers can combine multiple Web services to achieve business purposes by the reuse of services, and it does reduce not only business costs but also meets customer needs. However, Web service composition is a challenging problem. Among the massive amounts of data, the task of retrieving Web services is enormous, and each service has QoS indicators as restrictions. There may be conflicts between QoS indicators. Choosing the best combination of web services requires considering the QoS attributes of each type of web service (Dahan et al., 2021; Rajaram & Selvi, 2022; Vidyasankar & Vossen, 2011).

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