{"title":"异构无线和移动综合网络中多种流量的资源管理方案","authors":"Wei Shen, Qing-An Zeng","doi":"10.1109/ICCCN.2008.ECP.38","DOIUrl":null,"url":null,"abstract":"In order to provide more comprehensive services, a concept of integrated heterogeneous wireless and mobile network (IHWMN) is introduced by combing different types of wireless and mobile networks (WMNs). However, it imposes great challenges such as resource management schemes to support multiple traffic in IHWMNs. In this paper, we propose two resource management schemes for IHWMNs. The first scheme is called traffic-based resource management scheme (TRMS) which allocates the resource based on traffic type, call type, bandwidth availability, and bandwidth provision. In the second scheme which is called Q-learning-based resource management scheme (QRMS), the resource management scheme is formulated as a Markov decision process (MDP) and Q-learning approach is applied to conduct the resource allocation. The system performance of both proposed schemes are evaluated and compared by using extensive simulations.","PeriodicalId":314071,"journal":{"name":"2008 Proceedings of 17th International Conference on Computer Communications and Networks","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Resource Management Schemes for Multiple Traffic in Integrated Heterogeneous Wireless and Mobile Networks\",\"authors\":\"Wei Shen, Qing-An Zeng\",\"doi\":\"10.1109/ICCCN.2008.ECP.38\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to provide more comprehensive services, a concept of integrated heterogeneous wireless and mobile network (IHWMN) is introduced by combing different types of wireless and mobile networks (WMNs). However, it imposes great challenges such as resource management schemes to support multiple traffic in IHWMNs. In this paper, we propose two resource management schemes for IHWMNs. The first scheme is called traffic-based resource management scheme (TRMS) which allocates the resource based on traffic type, call type, bandwidth availability, and bandwidth provision. In the second scheme which is called Q-learning-based resource management scheme (QRMS), the resource management scheme is formulated as a Markov decision process (MDP) and Q-learning approach is applied to conduct the resource allocation. The system performance of both proposed schemes are evaluated and compared by using extensive simulations.\",\"PeriodicalId\":314071,\"journal\":{\"name\":\"2008 Proceedings of 17th International Conference on Computer Communications and Networks\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Proceedings of 17th International Conference on Computer Communications and Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCN.2008.ECP.38\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Proceedings of 17th International Conference on Computer Communications and Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCN.2008.ECP.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Resource Management Schemes for Multiple Traffic in Integrated Heterogeneous Wireless and Mobile Networks
In order to provide more comprehensive services, a concept of integrated heterogeneous wireless and mobile network (IHWMN) is introduced by combing different types of wireless and mobile networks (WMNs). However, it imposes great challenges such as resource management schemes to support multiple traffic in IHWMNs. In this paper, we propose two resource management schemes for IHWMNs. The first scheme is called traffic-based resource management scheme (TRMS) which allocates the resource based on traffic type, call type, bandwidth availability, and bandwidth provision. In the second scheme which is called Q-learning-based resource management scheme (QRMS), the resource management scheme is formulated as a Markov decision process (MDP) and Q-learning approach is applied to conduct the resource allocation. The system performance of both proposed schemes are evaluated and compared by using extensive simulations.