In this paper, we consider the problem of modelling the average delay experienced by a packet in a single cell IEEE 802.11 DCF wireless local area network. The packet arrival process at each node i is assumed to be Poisson with rate parameter . Since the nodes are sharing a single channel, they have to contend with one another for a successful transmission. The mean delay for a packet has been approximated by modelling the system as a 1-limited Random Polling system with zero switchover time. We show that even for non-homogeneous packet arrival processes, the mean delay of packets across the queues are same and depends on the system utilization factor and the aggregate throughput of the MAC. Extensive simulations are conducted to verify the analytical results.
In @cite_2 , the authors propose System Centric and User Centric Queuing Models for IEEE 802.11 based Wireless LANs. @cite_2 assumes the server to allocate its resources to users in a round robin manner. In the System Centric Model, the arrivals are assumed to be Poisson, thus the resource sharing model takes the form of an M G 1 PS system with the mean delay being the same as that in an equivalent M M 1 system. In the User Centric Model, each user queue is modeled as a separate G G 1 queue.
@cite_2
2107403026 2136340918 2101280440 2163707289
We consider the following two views of an IEEE 802.11 based Wireless LAN: (i) as seen by the WLAN medium and (ii) as seen by a user. In the system centric view, we model the WLAN medium as a server that allocates its resources to users in a round Robin manner. This resource sharing model not only provides a simple model for the system, it also enables us to derive the channel service rate and the total delay incurred in transmitting a packet. For Poisson arrivals, the resource sharing model takes the form of an M G 1 PS system with the mean delay being the same as that in an equivalent M M 1 system. We then take a user centric view and model each user's queue as a separate G G 1 queue. We derive the probability distributions for the different delay sources, i.e., random back-off time, random number of collisions and random number of successful transmissions from other users. This user centric model can provide insights into understanding access and queuing delays in 802.11 DCF. Finally, we discuss the utility of these models for functions such as capacity analysis, admission control and QoS enforcement. We consider the problem of resource allocation in downlink OFDMA systems for multi service and unknown environment. Due to users' mobility and intercell interference, the base station cannot predict neither the Signal to Noise Ratio (SNR) of each user in future time slots nor their probability distribution functions. In addition, the traffic is bursty in general with unknown arrival. The probability distribution functions of the SNR, channel state and traffic arrival density are then unknown. Achieving a multi service Quality of Service (QoS) while optimizing the performance of the system (e.g. total throughput) is a hard and interesting task since it depends on the unknown future traffic and SNR values. In this paper we solve this problem by modeling the multiuser queuing system as a discrete time linear dynamic system. We develop a robust H∞ controller to regulate the queues of different users. The queues and Packet Drop Rates (PDR) are controlled by proposing a minimum data rate according to the demanded service type of each user. The data rate vector proposed by the controller is then fed as a constraint to an instantaneous resource allocation framework. This instantaneous problem is formulated as a convex optimization problem for instantaneous subcarrier and power allocation decisions. Simulation results show small delays and better fairness among users. We present an analytic model for evaluating the queueing delays at nodes in an IEEE 802.11 MAC based wireless network. The model can account for arbitrary arrival patterns, packet size distributions and number of nodes. Our model gives closed form expressions for obtaining the delay and queue length characteristics. We model each node as a discrete time G G 1 queue and derive the service time distribution while accounting for a number of factors including the channel access delay due to the shared medium, impact of packet collisions, the resulting backoffs as well as the packet size distribution. The model is also extended for ongoing proposals under consideration for 802.11e wherein a number of packets may be transmitted in a burst once the channel is accessed. Our analytical results are verified through extensive simulations. The results of our model can also be used for providing probabilistic quality of service guarantees and determining the number of nodes that can be accommodated while satisfying a given delay constraint. This paper presents an analytic model for evaluating the MAC layer queueing delays at wireless nodes using the distributed coordination function of IEEE 802.11 MAC specifications. Our model is valid for finite loads and can account for arbitrary arrival patterns, packet size distributions and number of nodes. Each node is modeled as a discrete time G G 1 queue and we obtain closed form expressions for the delay and queue length characteristics at each node. We derive the service time distribution for the packets at each node while accounting for a number of factors including the channel access delay due to the shared medium, impact of packet collisions, the resulting backoffs as well as the packet size distribution. Our analytical results are verified through extensive simulations and are more accurate than existing models.