{"title":"基于人工神经网络的移动多媒体网络QoS提供的动态呼叫接纳控制","authors":"Anand Pandey, Sanjeev Kumar, Krishan Kumar","doi":"10.1109/NGCT.2016.7877441","DOIUrl":null,"url":null,"abstract":"In mobile multimedia communication systems, the limited bandwidth is an issue of serious concern. However for the better utilization of available resources in a network, channel allocation scheme plays a very important role to manage the available resources in each cell, hence this issue should be managed to reduce the call blocking or dropping probabilities. In this paper we have proposed the new dynamic channel allocation scheme based on handoff calls and traffic mobility using Hopfield neural network. It will improve the capacity of existing system. Hopfield method develops the new energy function that allocates channel not only for new call but also for handoff calls on the basis of traffic mobility information. Moreover, we have also examined the performance of traffic mobility with the help of error back propagation neural network model to enhance the overall quality of services (QoS) in terms of continuous service availability and intercell handoff calls. Our scheme decreases the call handoff dropping and blocking probability up to a better extent as compared to the other existing systems of fixed channel allocation and dynamic channel allocation.","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Dynamic call admission control for QoS provision in mobile multimedia networks using artificial neural networks\",\"authors\":\"Anand Pandey, Sanjeev Kumar, Krishan Kumar\",\"doi\":\"10.1109/NGCT.2016.7877441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In mobile multimedia communication systems, the limited bandwidth is an issue of serious concern. However for the better utilization of available resources in a network, channel allocation scheme plays a very important role to manage the available resources in each cell, hence this issue should be managed to reduce the call blocking or dropping probabilities. In this paper we have proposed the new dynamic channel allocation scheme based on handoff calls and traffic mobility using Hopfield neural network. It will improve the capacity of existing system. Hopfield method develops the new energy function that allocates channel not only for new call but also for handoff calls on the basis of traffic mobility information. Moreover, we have also examined the performance of traffic mobility with the help of error back propagation neural network model to enhance the overall quality of services (QoS) in terms of continuous service availability and intercell handoff calls. Our scheme decreases the call handoff dropping and blocking probability up to a better extent as compared to the other existing systems of fixed channel allocation and dynamic channel allocation.\",\"PeriodicalId\":326018,\"journal\":{\"name\":\"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)\",\"volume\":\"124 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NGCT.2016.7877441\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NGCT.2016.7877441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic call admission control for QoS provision in mobile multimedia networks using artificial neural networks
In mobile multimedia communication systems, the limited bandwidth is an issue of serious concern. However for the better utilization of available resources in a network, channel allocation scheme plays a very important role to manage the available resources in each cell, hence this issue should be managed to reduce the call blocking or dropping probabilities. In this paper we have proposed the new dynamic channel allocation scheme based on handoff calls and traffic mobility using Hopfield neural network. It will improve the capacity of existing system. Hopfield method develops the new energy function that allocates channel not only for new call but also for handoff calls on the basis of traffic mobility information. Moreover, we have also examined the performance of traffic mobility with the help of error back propagation neural network model to enhance the overall quality of services (QoS) in terms of continuous service availability and intercell handoff calls. Our scheme decreases the call handoff dropping and blocking probability up to a better extent as compared to the other existing systems of fixed channel allocation and dynamic channel allocation.