Naishuo Tian

Modeling and performance evaluation for the sleep mode in the IEEE 802.16e wireless networks

IEEE 802.16e is the latest broadband wireless access standard designed to support mobility. In mobile networks, how to control energy consumption is one of the most important issues for the battery-powered mobile stations. The standard proposes an energy saving mechanism named ¿sleep mode¿ for conserving the power of the mobile stations. According to the operating mechanism of the sleep mode for downlink traffic in the type I power saving class, a discrete-time Geom/G/1 queueing model with a close-down time and multiple vacations is built in this paper. By employing an embedded Markov chain method, the average queue length and the average sojourn time of the system model are derived. Correspondingly, we get the performance measures of the energy saving rate and the average packet delay time for the sleep mode in the IEEE 802.16e. Finally, numerical results are given to demonstrate the dependency relationships between the system performance measures and the system parameters. Furthermore, a cost model is developed to determine the optimum length of the close-down time.

Performance Analysis and Evaluation for Connection-Oriented Networks Based on Discrete Time Vacation Queueing Model

Abstract In this paper, we establish a discrete time Geom/G/1 queue with setup/close-delay/close-down based on operating mechanism of Switch Virtual Channel Connection (SVCC) in connection-oriented networks. The formulas of SVCC performance measures of setup ratio, idle ratio, transmission efficiency and average response time are derived. Combining the formulas with system simulation, we confirm the dependency relationships between these performance measures and the close delay timer’s setting, which have potential applications in system optimal design and network control.

Performance Evaluation of Wireless Communication Networks for Multi-Traffic with Multi-Channel

In this paper, we present a new effective mathematical analysis to numerically evaluate the performance for multitraffic in wireless communication networks with multi-channel and an admission control scheme. We apply a matrix geometric solution method to describe the stochastic behavior of the system and give the exact performance measures, such as, utilization of channel for both voice and data packets, blocking probability of voice packets, the average queue length of data packets, and the average waiting time of data packets. The numerical results show how priority can be provided and how the whole system performance can be improved based on the running mechanism of the multi-channel wireless communication networks and the various quality of service (QoS) requirements of multi-traffic.

Modeling and performance evaluation of the sleep mode in the IEEE 802.16e wireless networks with self-similar traffic

Abstract IEEE 802.16e is currently the latest broadband wireless access standard designed to support mobility. In mobile networks, how to control energy consumption is one of the most important issues for battery-powered mobile stations. The standard proposes an energy saving mechanism named ‘sleep mode’ for conserving the power of mobile stations. According to the operation principle of the sleep mode for downlink traffic in the type I power saving class, considering the self-similar nature of massive multimedia data in wireless networks, a discrete-time batch arrival Geom X /G/1 queuing model with a close-down time and multiple vacations is built. The batch size is supposed to be Pareto distributed. By employing an embedded Markov chain method, the average queue length and the average sojourn time of the system model are derived. Correspondingly, the performance measures are obtained of the energy saving rate and the average packet delay time for the sleep mode in the IEEE 802.16e. The numerical results demonstrate the dependency relationships between the system performance measures and the system parameters with different offered loads and different self-similar degrees. Furthermore, a cost model is developed to determine the optimum length of the close-down time for minimizing the total system cost.

Performance Analysis of ARQ Schemes in Self-Similar Traffic

In this chapter, we present a new method to analyze the performance of Automatic Repeat reQuest (ARQ) schemes in self-similar traffic. Taking into account the self-similar nature of a massive-scale wireless multimedia service, we build a batch arrival queueing model and suppose the batch size to be a random variable following a Pareto(c,α) distribution. Considering the delay in the setting up procedure of a data link, we introduce a setup strategy in this queueing model. Thus a batch arrival Geom X /G/1 queueing system with setup is built in this chapter. By using a discrete-time embedded Markov chain, we analyze the stationary distribution of the queueing system and derive the Probability Generation Functions (P.GFs.) of the queueing length and the waiting time of the system. We give the formula for performance measures in terms of the response time of data frames, setup ratios, and offered loads for different ARQ schemes. Numerical results are given to evaluate the performance of the system and to show the influence of the self-similar degree and the delay of the setup procedure on the system performance.

Performance analysis of self-similar traffic for future service-oriented internet

In this paper, we present a new method to analyze the performance of automatic repeat request (ARQ) schemes in self-similar traffic for the future service-oriented Internet. Taking into account the self-similar traffic of a massive-scale wireless multimedia service, we build a batch arrival queueing model and suppose the batch size is a random variable following Pareto (c, alpha) distribution. Considering the delay in the setting up procedure of a data link, we introduce a setup strategy in this queueing model. Thus a batch arrival Geomxi/G/1 queueing system with setup is built in this paper. We give the formula for performance measures in terms of setup ratio and offered load for different ARQ schemes. Numerical results are given to evaluate the performance of the system and to show influence of the self-similar degree and the delay of the setup procedure on these system performance.

Non-saturated throughput analysis of IEEE 802.11-based cognitive radio networks

Abstract Technology of cognitive radio networks has emerged as an effective method to enhance the utilization of the radio spectrum where the primary users have priority to use the spectrum, and the secondary users try to exploit the spectrum unoccupied by the primary users. In this paper, considering the non-saturated condition, the performance analysis for the IEEE 802.11-based cognitive radio networks is presented with single-channel and multi-channel, respectively. For the single-channel case, an absorbing Markov chain model describing the system transitions is constructed, and one-step transition probability matrix of the Markov chain is given. By using the method of probability generating function, the non-saturated throughput of the secondary users is obtained. For the multi-channel case, taking into account the negotiation-based sensing policy, the mean number of unused channels perceived by the second users is given, and then the non-saturated aggregate throughput of the secondary users is derived. Finally, numerical examples are provided to show the influences of the non-saturated degree, the number of the secondary users and the channel utilization of the primary users on the performance measures for the non-saturated throughput with single-channel and the non-saturated aggregate throughput with multi-channel.

A Pure Decrement Service Geom/G/1 Queue with Multiple Adaptive Vacations

In this chapter, a Geom/G/1 queue model with a pure decrement service policy and multiple adaptive vacations is analyzed. The Probability Generation Function (P.G.F.) of the queue length is obtained by using an embedded Markov chain method. The P.G.F. of the waiting time is then derived based on the independence between the arrival process and the waiting time. The probabilities for the system being in various states of busy, vacation, or idle, respectively, are also derived. Finally, some special cases for the Geom/G/1 queue model with a pure decrement service policy and multiple adaptive vacations are given to demonstrate the general properties of the queue models.

Performance evaluation of a connection-oriented Internet service based on a queueing model with finite capacity

The operating mechanism of a connection-oriented Internet service is analyzed. Considering the finite buffer in connection-oriented Internet service, we establish a Geom/G/1/K queueing model with setup-close delay-close down for user-initiated session. Using the approach of an embedded Markovian chain and supplementary variables, we derive the probability distribution for the steady queue length and the probability generating function for the waiting time. Correspondingly, we study the performance measures of quality of service (QoS) in terms of system throughput, system response time, and system blocking probability. Based on the simulation results, we discuss the influence of the upper limit of close delay period and the capacity of the queueing model on the performance measures, which have potential application in the design, resource assigning, and optimal setting for the next generation Internet.

Simulation Study of a Connection-Oriented Internet Service Based on a Queueing Model

In this paper, we analyze the operating mechanism of a connection-oriented Internet service. Considering the finite buffer size in a connection-oriented Internet service, we establish a Geom/Geom/1/K queueing model with setup-close delay-close down feature for user-initiated sessions. Using a simulation approach, we study the performance measures of Quality of Service (QoS) in terms of system throughput, system response time, and system blocking probability. Based on the simulation results, we discuss the influence of the upper limit of close delay period and the capacity of the buffer on the performance measures. Findings from such an analysis may potentially be applied in the design, resource assigning, and optimal setting for the next generation Internet.