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A connection-level call admission control using genetic algorithm for MultiClass multimedia services in wireless networks

机译:基于遗传算法的无线网络中MultiClass多媒体服务的连接级呼叫允许控制

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摘要

Call admission control in a wireless cell in a personal communication system (PCS) can be modeled as an M/M/C/C queuing system with m classes of users. Semi-Markov Decision Process (SMDP) can be used to optimize channel utilization with upper bounds on handoff blocking probabilities as Quality of Service constraints. However, this method is too time-consuming and therefore it fails when state space and action space are large. In this paper, we apply a genetic algorithm approach to address the situation when the SMDP approach fails. We code call admission control decisions as binary strings, where a value of “1” in the position i (i=1,…m) of a decision string stands for the decision of accepting a call in class-i; a value of “0” in the position i of the decision string stands for the decision of rejecting a call in class-i. The coded binary strings are feed into the genetic algorithm, and the resulting binary strings are founded to be near optimal call admission control decisions. Simulation results from the genetic algorithm are compared with the optimal solutions obtained from linear programming for the SMDP approach. The results reveal that the genetic algorithm approximates the optimal approach very well with less complexity.
机译:可以将个人通信系统(PCS)中无线小区中的呼叫允许控制建模为具有m个用户类别的M / M / C / C排队系统。半马尔可夫决策过程(SMDP)可用于优化信道利用率,并以服务质量约束作为切换阻塞概率的上限。但是,该方法太耗时,因此在状态空间和动作空间较大时会失败。在本文中,我们采用遗传算法来解决SMDP方法失败时的情况。我们将呼叫接纳控制决策编码为二进制字符串,其中决策字符串的位置i(i = 1,…m)中的值“ 1”代表在类i中接受呼叫的决策。决策字符串的位置i处的值“ 0”表示拒绝类别i中的呼叫的决策。将编码后的二进制字符串输入遗传算法,然后将生成的二进制字符串建立为接近最佳呼叫接纳控制决策。将遗传算法的仿真结果与SMDP方法的线性规划获得的最佳解决方案进行了比较。结果表明,遗传算法很好地逼近了最优方法,并且复杂度更低。

著录项

  • 作者

    Hong, X; Xiao, Y; Ni, Q;

  • 作者单位
  • 年度 2006
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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