具有时变马尔可夫调制服务速率的M2M小数据业务排队分析模型

Analytical queuing model with time- varying Markov modulated service rate for M2M small data service

将机器类通信(M2M)监控视频类业务(SVS)优先占用网络带宽时,网络对M2M小数据类业务(SDS)的服务过程抽象为时变马尔可夫调制服务率的包级排队系统,研究了网络对SDS的服务能力以及SVS对SDS的制约。求解了叠加在SDS随机到达过程上的多态马尔可夫调制泊松过程(MMPP)环境状态概率空间。运用第一步分析法和LS变换,分析了在随机环境过程下SDS的复杂随机服务过程,求解了SDS包服务时间的均值和方差。最后,通过数值仿真给出了SVS的突发度、到达率和服务率对SDS服务特性的影响。

A packet-level queuing system with time-varying Markov modulated service rate was established to model the process that network serves Machine to Machine （M2M） Small Data Services （SDS） when M2M Surveillance Video Services （SVS） use network bandwidth preferentially. The main goal was to investigate the service capability of the network for SDS and the restrictions of SVS on SDS. Stochastic process theory, queuing theory and probability theory were used to analyze the environmental state probability space of the multi-state Markov-modulated Poisson Process （MMPP） attached to the random arrival process of SDS. Then first step analysis and Laplace-Stieltjes（LS） were applied to analyze the complex random service process of SDS under the multi-state MMPP random environment process, and the average and variance of the service time for SDS packets were calculated. Numerical simulation results demonstrate the impacts of burstiness, arrival rate and service rate of SVS on the service features of SDS.