A hybrid service selection optimization algorithm in internet of things

Author:

Zhang XiaofeiORCID,Geng Juncheng,Ma Jianwei,Liu Hao,Niu Shuangxia,Mao Wandeng

Abstract

AbstractWith the scale of Internet of Things (IoT) continues to increase, it brings big challenges for service selection in a large-scale IoT. For solving this problem, a service selection method based on the enhanced genetic algorithm is proposed in this paper. To decrease the scale of service selection, this paper uses the lexicographic optimization approach and quality of service (QoS) constraint relaxation technique to find the candidate service with height QoS. Then, the IoT service selection problem is transformed into a single-objective optimization problem adopting a simple weighting method, and the final composite service meeting the user's QoS needs are obtained from the candidate service. The simulation results show that the proposed algorithm can efficiently and quickly achieve a composite service satisfying user's QoS needs, and is more suitable for solving the service composite problem in large-scale IoT services.

Funder

Science and Technology Foundation of State Grid Corporation of China

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Signal Processing

Cited by 14 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. Amalgamation of Optimization Algorithms With IoT Applications;Practice, Progress, and Proficiency in Sustainability;2024-06-30

2. A Ring Topology-Based Communication-Efficient Scheme for D2D Wireless Federated Learning;GLOBECOM 2023 - 2023 IEEE Global Communications Conference;2023-12-04

3. A web service selection model based on DeepFM and hash space segment matching;2023 35th Chinese Control and Decision Conference (CCDC);2023-05-20

4. DeepLens: Interactive Out-of-distribution Data Detection in NLP Models;Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19

5. Designing a model for selecting, ranking and optimising service quality indicators using meta-heuristic algorithms;International Journal of Data Mining, Modelling and Management;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