Number Of Backlogged Packets Research Articles

A Combined Throughput and Hierarchical Strategies for Medium Access in Wireless Network

Recently, the selfish behavior of mobile users in MAC protocols has been widely analyzed using game theory with all its powerful solution concepts. This selfish behavior causes the lost and collision of more packets. To reduce this phenomenon and to enhance the performance of the networks, in this paper, we propose to combine the learning algorithm, with a partial cooperation in slotted Aloha mechanism. We develop a Stackelberg game where the base station is the leader, and all mobiles are followers. The leader chooses first its strategy and broadcasts it to the followers. We give to the leader the choice of being either selfish by maximizing its own throughput, or being altruistic by maximizing the followers throughputs. We model the system by a three dimensional Markov chain. The states of the Markov chain describe the number of backlogged packets among leader and followers. After, we introduce a learning process, and we study its impact on the system performance. The obtained results showed that this approach has significantly improved the partial cooperative slotted Aloha mechanism and give best results for the utility.

Differentiated Backoff Strategies for Prioritized Random Access Delay in Multiservice Cellular Networks

In this paper, a novel prioritization mechanism for random access strategies in cellular networks is proposed. The proposed prioritized random access strategy sets different retransmission probabilities to users, depending on their priorities. First, a mathematical analysis method for simultaneously evaluating throughput and access delay, considering an infinite population model and different retransmission policies, is developed. Most of the previous related research has been done, considering both finite population and saturation conditions where all the nodes in the system always have a packet ready to be transmitted, and the transmission queue of each station is assumed to be always nonempty. This assumption is a good approximation for a local area network working at full capacity. However, in a cellular system, the assumptions of a finite population and every node in a cell always having a packet to transmit are not very realistic. Here, the analytical results consider a Poisson arrival process-which is more suitable for the traffic model in a cellular system-for the users in the cells. Then, considering slotted ALOHA as a random access strategy and the developed analysis method, the case where two different types of service exist (low-and high-priority users) is mathematically analyzed. With the proposed prioritized random access strategy, the average access delay achieved for the high priority users is always lower than that for the low-priority users. Additionally, a mathematical expression for the throughput is derived with and without service differentiation. Finally, two approaches for finding the optimum retransmission probabilities are developed; in the first approach, the number of backlogged packets is required, whereas a simpler and efficient alternative method requires only the knowledge of the mean new packet arrival rate. For the performance analysis, four of the most common backoff algorithms are considered: (1) Uniform (UB); (2) Binary Exponential (BEB); (3) Negative Exponential (XB); and (4) Geometric (GB).

Slotted Aloha as a game with partial information

This paper studies distributed choice of retransmission probabilities in slotted ALOHA. Both the cooperative team problem as well as the noncooperative game problem are considered. Unlike some previous work, we assume that mobiles do not know the number of backlogged packets at other nodes. A Markov chain analysis is used to obtain optimal and equilibrium retransmission probabilities and throughput. We then investigate the impact of adding retransmission costs (which may represent the disutility for power consumption) on the equilibrium and show how this pricing can be used to make the equilibrium throughput coincide with the optimal team throughput.