{"title":"改进的云计算动态负载均衡方法","authors":"Soumen Swarnakar, Ritik Kumar, Saurabh Krishn, Chandan Banerjee","doi":"10.1109/ICCE50343.2020.9290602","DOIUrl":null,"url":null,"abstract":"Cloud computing is one of the important technologies in the field of Information Technology. Many services are available and provided by different service providers using different cloud technology nowadays. The main problem of cloud computing-based technology is load balancing in different cloud servers. It is one of the important issues in the necessary growth of cloud computation. Demand for the new cloud services with a high-speed service is important issue in this current era. There are various algorithms of load balancing which have been already discussed for an efficient allocation of requests through a proper selection of virtual machines in a cloud environment. In this paper, a new distribution technique of the entire incoming requests among the virtual machines has been proposed with an improved dynamic load balancing approach (IDLBA) in the cloud environment. Thus, its simulation is performed using the CloudAnalyst simulator three times with different numbers of tasks of different length. The simulation result is compared with some previously designed load balancing algorithms [1][2] in the cloud environment. Comparative analysis of simulation results establishes the fact that the incoming tasks are distributed dynamically among different available virtual machines which are of different configurations in a different data center in such a way that comparatively better response time and makespan time are achieved.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Improved Dynamic Load Balancing Approach in Cloud Computing\",\"authors\":\"Soumen Swarnakar, Ritik Kumar, Saurabh Krishn, Chandan Banerjee\",\"doi\":\"10.1109/ICCE50343.2020.9290602\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cloud computing is one of the important technologies in the field of Information Technology. Many services are available and provided by different service providers using different cloud technology nowadays. The main problem of cloud computing-based technology is load balancing in different cloud servers. It is one of the important issues in the necessary growth of cloud computation. Demand for the new cloud services with a high-speed service is important issue in this current era. There are various algorithms of load balancing which have been already discussed for an efficient allocation of requests through a proper selection of virtual machines in a cloud environment. In this paper, a new distribution technique of the entire incoming requests among the virtual machines has been proposed with an improved dynamic load balancing approach (IDLBA) in the cloud environment. Thus, its simulation is performed using the CloudAnalyst simulator three times with different numbers of tasks of different length. The simulation result is compared with some previously designed load balancing algorithms [1][2] in the cloud environment. Comparative analysis of simulation results establishes the fact that the incoming tasks are distributed dynamically among different available virtual machines which are of different configurations in a different data center in such a way that comparatively better response time and makespan time are achieved.\",\"PeriodicalId\":421963,\"journal\":{\"name\":\"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCE50343.2020.9290602\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE50343.2020.9290602","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improved Dynamic Load Balancing Approach in Cloud Computing
Cloud computing is one of the important technologies in the field of Information Technology. Many services are available and provided by different service providers using different cloud technology nowadays. The main problem of cloud computing-based technology is load balancing in different cloud servers. It is one of the important issues in the necessary growth of cloud computation. Demand for the new cloud services with a high-speed service is important issue in this current era. There are various algorithms of load balancing which have been already discussed for an efficient allocation of requests through a proper selection of virtual machines in a cloud environment. In this paper, a new distribution technique of the entire incoming requests among the virtual machines has been proposed with an improved dynamic load balancing approach (IDLBA) in the cloud environment. Thus, its simulation is performed using the CloudAnalyst simulator three times with different numbers of tasks of different length. The simulation result is compared with some previously designed load balancing algorithms [1][2] in the cloud environment. Comparative analysis of simulation results establishes the fact that the incoming tasks are distributed dynamically among different available virtual machines which are of different configurations in a different data center in such a way that comparatively better response time and makespan time are achieved.