Mobile Motion Prediction and QoS Improvement
碩士 === 國立中正大學 === 資訊管理學系 === 92 === There are many way to lower handoff drop rate, one of them is prediction. If we can predict the next cell which people will move in, we could preserve bandwidth for him or her, when people move in that cell, the phone call will not drop because of bandwidth reserv...
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ndltd-TW-092CCU003960052016-01-04T04:08:29Z http://ndltd.ncl.edu.tw/handle/02417103242283851294 Mobile Motion Prediction and QoS Improvement 行動通訊之方向預測及服務品質之提升 詹文志 碩士 國立中正大學 資訊管理學系 92 There are many way to lower handoff drop rate, one of them is prediction. If we can predict the next cell which people will move in, we could preserve bandwidth for him or her, when people move in that cell, the phone call will not drop because of bandwidth reservation. Many people had develop their method to predict the user moving direction, but most of them use sophisticate stochastic processes or they need record huge data to complete the job. We are trying to use simple calculation and a little extract data to predict the user moving direction. What we are trying to do is using less cost to achieve the same, even better performance. Our prediction method keeps track of user mobility patterns and traffic patterns between cells. With the easy path comparing, we can derivate condition probability and the next target cell, the target cell will informed to reserve bandwidth basis of this probability. Through adjusting the reserved bandwidth dynamically, we could maintain the handoff drop rate under target value, mean while, using bandwidths efficiently and improving the quality of services. 古政元 2004 學位論文 ; thesis 64 zh-TW |
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碩士 === 國立中正大學 === 資訊管理學系 === 92 === There are many way to lower handoff drop rate, one of them is prediction. If we can predict the next cell which people will move in, we could preserve bandwidth for him or her, when people move in that cell, the phone call will not drop because of bandwidth reservation. Many people had develop their method to predict the user moving direction, but most of them use sophisticate stochastic processes or they need record huge data to complete the job. We are trying to use simple calculation and a little extract data to predict the user moving direction. What we are trying to do is using less cost to achieve the same, even better performance. Our prediction method keeps track of user mobility patterns and traffic patterns between cells. With the easy path comparing, we can derivate condition probability and the next target cell, the target cell will informed to reserve bandwidth basis of this probability. Through adjusting the reserved bandwidth dynamically, we could maintain the handoff drop rate under target value, mean while, using bandwidths efficiently and improving the quality of services.
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古政元 |
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古政元 詹文志 |
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詹文志 |
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詹文志 Mobile Motion Prediction and QoS Improvement |
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詹文志 |
title |
Mobile Motion Prediction and QoS Improvement |
title_short |
Mobile Motion Prediction and QoS Improvement |
title_full |
Mobile Motion Prediction and QoS Improvement |
title_fullStr |
Mobile Motion Prediction and QoS Improvement |
title_full_unstemmed |
Mobile Motion Prediction and QoS Improvement |
title_sort |
mobile motion prediction and qos improvement |
publishDate |
2004 |
url |
http://ndltd.ncl.edu.tw/handle/02417103242283851294 |
work_keys_str_mv |
AT zhānwénzhì mobilemotionpredictionandqosimprovement AT zhānwénzhì xíngdòngtōngxùnzhīfāngxiàngyùcèjífúwùpǐnzhìzhītíshēng |
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1718158163913474048 |