[1]孙君,谷苏文. 自适应簇和学习算法的调度策略[J].计算机技术与发展,2017,27(05):92-96.
　SUN Jun,GU Su-wen. Dispatching Strategy with Adaptive Clustering and Learning Algorithm[J].,2017,27(05):92-96.
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 自适应簇和学习算法的调度策略()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年05期
页码:
92-96
栏目:
智能、算法、系统工程
出版日期:
2017-05-10

文章信息/Info

Title:
 Dispatching Strategy with Adaptive Clustering and Learning Algorithm
文章编号:
1673-629X（2017)05-0092-05
作者:
 孙君; 谷苏文
 南京邮电大学
Author(s):
 SUN Jun; GU Su-wen
关键词:
 ; 以用户为中心; 自适应簇; 学习算法; 泊松点过程
Keywords:
 ; user-centric; adaptive clustering; learning algorithm; Poisson Point Processes (PPP)
分类号:
TP31
文献标志码:
A
摘要:
 提升用户的峰值速率和吞吐量性能一直以来是一个非常重要但同时又具有挑战性的问题.密集蜂窝网络中,采用了以用户为中心的自适应簇和基于学习算法高速缓存方法的调度方法,一定程度上可以改善用户的峰值速率和吞吐量性能;应用调度策略的网络中,以用户为中心的自适应簇方法能实现每个用户的效吞吐量最大化.若小基站有很高的存储容量,常用的数据被储存在本地小基站的缓存器中,用户可以通过学习算法选择附近小基站中的一个来获得想要的数据.当用户进行通信时,可计算出此时自适应簇的最大化归一化有效吞吐量,大于门限值时选择基于自适应簇的通信,否则采用基于学习算法的方法选择最优的小基站进行通信.这种新颖的网络架构能够为用户提供个性化的网络服务,提升用户的峰值速率和吞吐量性能.
Abstract:
 With the development of mobile communication networks,enhancing peak rate and throughput performance for users has always been a very important but challenging issue.In a dense cellular network,a dispatching strategy which is based on user-centric adaptive clustering and a learning algorithm has been studied.A large and dense cellular network has been considered which has been modeled by a random network where the BSs’ and UEs’ locations are placed randomly,following Poisson Point Process (PPP) distributions.An adaptive clustering algorithm for user-centric has been described,which means generating a cell for each user,and all base stations within the district can provide services for user,it is proposed also to maximize each user normalized effective throughput.SBS are assumed to possess high storage capacity and to form a distributed caching network.Popular files are stored in local cache of SBS in its vicinity.The popularity profile of cached content is unknown and estimated using instantaneous demands from users within a specified time interval.When a user goes to communication,the effective throughput of normalization with user-centric adaptive cluster can be found.If the value is greater than the threshold,the network system will select adaptive communication;otherwise select the most use of excellent small base station to communicate with learning method.This novel network architecture can provide users with personalized network service,and enhance the peak rate and throughput performance for users.

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更新日期/Last Update: 2017-07-07