Improved Eagle Strategy Algorithm for Dynamic Web Service Composition in the IoT: A Conceptual Approach

Author:

Rajendran VenushiniORCID,Ramasamy R KanesarajORCID,Mohd-Isa Wan-NoorshahidaORCID

Abstract

The Internet of Things (IoT) is now expanding and becoming more popular in most industries, which leads to vast growth in cloud computing. The architecture of IoT is integrated with cloud computing through web services. Recently, Dynamic Web Service Composition (DWSC) has been implemented to fulfill the IoT and business processes. In recent years, the number of cloud services has multiplied, resulting in cloud services providing similar services with similar functionality but varying in Quality of Services (QoS), for instance, on the response time of web services; however, existing methods are insufficient in solving large-scale repository issues. Bio-inspired algorithm methods have shown better performance in solving the large-scale service composition problems, unlike deterministic algorithms, which are restricted. Thus, an improved eagle strategy algorithm method is proposed to increase the performance that directly indicates an improvement in computation time in large-scale DWSC in a cloud-based platform and on both functional and non-functional attributes of services. By proposing the improved bio-inspired method, the computation time can be improved, especially in a large-scale repository of IoT.

Funder

Telekom Malaysia Berhad

Publisher

MDPI AG

Subject

Computer Networks and Communications

Reference31 articles.

1. Service-Oriented Architecture Application in Long-Term Care Institution: A Case Study on an Information System Project Based on the Whole Person Concept in Taiwan;Chung;Int. J. Comput. Sci. Res.,2018

2. An Efficient Multi-Cloud Service Composition Using a Distributed Multiagent-Based, Memory-Driven Approach

3. A dynamic ant-colony genetic algorithm for cloud service composition optimization

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Eagle Strategy in Nature-Inspired Optimization: Theory, Analysis, Applications, and Comparative Study;Archives of Computational Methods in Engineering;2023-10-24

2. Deep Reinforcement Learning for QoS-Aware IoT Service Composition: The PD3QND Approach;2023 IEEE 14th International Conference on Software Engineering and Service Science (ICSESS);2023-10-17

3. A novel membrane‐inspired multiverse optimizer algorithm for quality of service‐aware cloud web service composition with service level agreements;International Journal of Communication Systems;2023-03-28

4. Artificial Bee Colony with Cuckoo Search for Solving Service Composition;Intelligent Automation & Soft Computing;2023

5. Hybridizing Artificial Bee Colony with Bat Algorithm for Web Service Composition;Computer Systems Science and Engineering;2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3