{"title":"QoS and Selfish Users: A MAC Layer Perspective","authors":"P. Nuggehalli, M. Sarkar, R. Rao","doi":"10.1109/GLOCOM.2007.895","DOIUrl":null,"url":null,"abstract":"Many wireless network standards include quality-of-service (QoS) features at the MAC layer. These features provide nodes transmitting real-time traffic such as voice and video preferential access to the channel over nodes carrying best-effort traffic. The success of these QoS mechanisms requires that nodes be honest and truthfully report their application's QoS category. However rational nodes will, if they can, deviate from a standard's specification to maximize their utility. Network interfaces are becoming increasingly programmable and it is possible for nodes to falsely classify their best-effort traffic as real-time traffic to obtain increased throughput. In this paper, we provide a game-theoretic analysis for a slotted Aloha like MAC that resembles the IEEE 802.11e MAC in many essential respects. Our MAC model allows traffic to be classified as either high-priority (HP) or low-priority (LP), and allows for both random access (contention) and polled (contention-free) channel access. We advocate the use of the contention-free access feature as an efficient and protocol-compliant mechanism to incentivize LP users to be truthful. We discuss appropriate utility functions for HP and LP traffic and analyze the performance of the system using the Nash bargaining solution (NBS) concept from cooperative game theory. The NBS concept is used to find a fair and Pareto-optimal operating point for our system. Since users are strategic, we then use the framework of non-cooperative game theory to find the set of Nash equilibria. Somewhat remarkably, we find that the NBS operating point is a Nash equilibrium, implying that our strategy is both efficient and strategy-proof.","PeriodicalId":370937,"journal":{"name":"IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOCOM.2007.895","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Many wireless network standards include quality-of-service (QoS) features at the MAC layer. These features provide nodes transmitting real-time traffic such as voice and video preferential access to the channel over nodes carrying best-effort traffic. The success of these QoS mechanisms requires that nodes be honest and truthfully report their application's QoS category. However rational nodes will, if they can, deviate from a standard's specification to maximize their utility. Network interfaces are becoming increasingly programmable and it is possible for nodes to falsely classify their best-effort traffic as real-time traffic to obtain increased throughput. In this paper, we provide a game-theoretic analysis for a slotted Aloha like MAC that resembles the IEEE 802.11e MAC in many essential respects. Our MAC model allows traffic to be classified as either high-priority (HP) or low-priority (LP), and allows for both random access (contention) and polled (contention-free) channel access. We advocate the use of the contention-free access feature as an efficient and protocol-compliant mechanism to incentivize LP users to be truthful. We discuss appropriate utility functions for HP and LP traffic and analyze the performance of the system using the Nash bargaining solution (NBS) concept from cooperative game theory. The NBS concept is used to find a fair and Pareto-optimal operating point for our system. Since users are strategic, we then use the framework of non-cooperative game theory to find the set of Nash equilibria. Somewhat remarkably, we find that the NBS operating point is a Nash equilibrium, implying that our strategy is both efficient and strategy-proof.