{"title":"An Optimal Service Composition Algorithm in Multi-Cloud Environment","authors":"Zahra Nazari, A. Kamandi, M. Shabankhah","doi":"10.1109/ICWR.2019.8765266","DOIUrl":null,"url":null,"abstract":"Major part of internet users are devices which are connected to each other on the internet and are exchanging data with internet brokers to receive requested services. Managing and accounting well to IoT requests needs maximum processing power, speed in data transfer and proper combining services in minimum time. This many devices in IoT, made solving problems in this area to use abilities and facilities of cloud environment. Hence combining services in cloud environment is paid attention recently. In this research we want to give an algorithm with approach of improving factors propounded in the problem combining service composition problem like number of clouds involved in giving services, number of services studied before fulfilling users requests and load balance between clouds. In this paper we use the factor, similarity measure, to find the most suitable cloud and composition plan in each phase which in addition to improving QoS metrics propounded in previous papers, it caused improving QoS metric of load balancing between clouds, prevention of formation of bottleneck in clouds entrance, decreasing the probability of temporarily failing of any of clouds and consequently increasing the users’ satisfaction.","PeriodicalId":6680,"journal":{"name":"2019 5th International Conference on Web Research (ICWR)","volume":"2 1","pages":"141-151"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 5th International Conference on Web Research (ICWR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWR.2019.8765266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Major part of internet users are devices which are connected to each other on the internet and are exchanging data with internet brokers to receive requested services. Managing and accounting well to IoT requests needs maximum processing power, speed in data transfer and proper combining services in minimum time. This many devices in IoT, made solving problems in this area to use abilities and facilities of cloud environment. Hence combining services in cloud environment is paid attention recently. In this research we want to give an algorithm with approach of improving factors propounded in the problem combining service composition problem like number of clouds involved in giving services, number of services studied before fulfilling users requests and load balance between clouds. In this paper we use the factor, similarity measure, to find the most suitable cloud and composition plan in each phase which in addition to improving QoS metrics propounded in previous papers, it caused improving QoS metric of load balancing between clouds, prevention of formation of bottleneck in clouds entrance, decreasing the probability of temporarily failing of any of clouds and consequently increasing the users’ satisfaction.