{"title":"基于改进遗传算法的移动边缘计算服务安置策略","authors":"Ruijuan Zheng, Junwei Xu, Xueqi Wang, Muhua Liu, Junlong Zhu","doi":"10.1016/j.pmcj.2024.101986","DOIUrl":null,"url":null,"abstract":"<div><div>In mobile edge computing (MEC), quality of service (QoS) is closely related to optimizing service placement strategies, which is crucial to providing efficient services that meet user needs. However, due to the mobility of users and the energy consumption limit of edge servers, the existing policies make it difficult to ensure the QoS level of users. In this paper, a novel genetic algorithm based on a simulated annealing algorithm is proposed to balance the QoS of users and the energy consumption of edge servers. Finally, the effectiveness of the algorithm is verified by experiments. The results show that the QoS value obtained by the proposed algorithm is closer to the maximum value, which has significant advantages in improving QoS value and resource utilization. In addition, in software development related to mobile edge computing, our algorithm helps improve the program’s running speed.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Service placement strategies in mobile edge computing based on an improved genetic algorithm\",\"authors\":\"Ruijuan Zheng, Junwei Xu, Xueqi Wang, Muhua Liu, Junlong Zhu\",\"doi\":\"10.1016/j.pmcj.2024.101986\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In mobile edge computing (MEC), quality of service (QoS) is closely related to optimizing service placement strategies, which is crucial to providing efficient services that meet user needs. However, due to the mobility of users and the energy consumption limit of edge servers, the existing policies make it difficult to ensure the QoS level of users. In this paper, a novel genetic algorithm based on a simulated annealing algorithm is proposed to balance the QoS of users and the energy consumption of edge servers. Finally, the effectiveness of the algorithm is verified by experiments. The results show that the QoS value obtained by the proposed algorithm is closer to the maximum value, which has significant advantages in improving QoS value and resource utilization. In addition, in software development related to mobile edge computing, our algorithm helps improve the program’s running speed.</div></div>\",\"PeriodicalId\":49005,\"journal\":{\"name\":\"Pervasive and Mobile Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pervasive and Mobile Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1574119224001111\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pervasive and Mobile Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574119224001111","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Service placement strategies in mobile edge computing based on an improved genetic algorithm
In mobile edge computing (MEC), quality of service (QoS) is closely related to optimizing service placement strategies, which is crucial to providing efficient services that meet user needs. However, due to the mobility of users and the energy consumption limit of edge servers, the existing policies make it difficult to ensure the QoS level of users. In this paper, a novel genetic algorithm based on a simulated annealing algorithm is proposed to balance the QoS of users and the energy consumption of edge servers. Finally, the effectiveness of the algorithm is verified by experiments. The results show that the QoS value obtained by the proposed algorithm is closer to the maximum value, which has significant advantages in improving QoS value and resource utilization. In addition, in software development related to mobile edge computing, our algorithm helps improve the program’s running speed.
期刊介绍：
As envisioned by Mark Weiser as early as 1991, pervasive computing systems and services have truly become integral parts of our daily lives. Tremendous developments in a multitude of technologies ranging from personalized and embedded smart devices (e.g., smartphones, sensors, wearables, IoTs, etc.) to ubiquitous connectivity, via a variety of wireless mobile communications and cognitive networking infrastructures, to advanced computing techniques (including edge, fog and cloud) and user-friendly middleware services and platforms have significantly contributed to the unprecedented advances in pervasive and mobile computing. Cutting-edge applications and paradigms have evolved, such as cyber-physical systems and smart environments (e.g., smart city, smart energy, smart transportation, smart healthcare, etc.) that also involve human in the loop through social interactions and participatory and/or mobile crowd sensing, for example. The goal of pervasive computing systems is to improve human experience and quality of life, without explicit awareness of the underlying communications and computing technologies.
The Pervasive and Mobile Computing Journal (PMC) is a high-impact, peer-reviewed technical journal that publishes high-quality scientific articles spanning theory and practice, and covering all aspects of pervasive and mobile computing and systems.
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