期刊名称：International Journal of Computer Information Systems and Industrial Management Applications
印刷版ISSN：2150-7988
电子版ISSN：2150-7988
出版年度：2021
卷号：13
页码：160-171
语种：English
出版社：Machine Intelligence Research Labs (MIR Labs)
摘要：In this paper, we propose a novel pricing mechanism to enhance the performance of the Slotted ALOHA mechanism combined with ZigZag Decoding (SA-ZD). We model the system using a stochastic game approach where the game state is given as a Markov process. We assume a cooperative game framework where users seek to optimize the same utility function. In our previous pricing mechanism [1], we associated a cost C ∈ [0, 1] for every transmission and retransmission attempt. Thus, if the transmission succeeds, the user receives a reward equal to 1 − C. Otherwise, in the case of collision, he pays a penalty equal to C. Following this approach, users prefer to not take the risk of paying the penalty cost, which means they choose to wait rather than transmitting, especially in heavy traffic conditions. Even though it seems optimal to not transmit in such conditions, our results show that this behavior yields a dramatic decrease in the system performance. Besides, it leads to an inherent tradeoff between the backlogged and newly arrived traffic. Toward this end, we propose in this paper a novel pricing strategy where we associate a cost not only to transmission attempts but also to the idle event (i.e when no one is transmitting). Moreover, we address the tradeoff problem by associating different costs Cb and Cs, respectively, to backlogged and newly arrived packets. Therefore, when a successful transmission is going through the channel, users pay a cost denoted by Cs or Cb. If a collision occurs, they pay a cost Cc, and when no one is transmitting, they pay the idling cost Cidle. Compared to the old pricing mechanism, our results show that the proposed approach achieves the best performance and maintains a fairness level between backlogged and newly arrived packets.
