Performance modelling of access control mechanisms for local and vehicular wireless networks Carrier sense multiple access collision avoidance (CSMACA) is the basic scheme upon which access to the shared medium is regulated in many wireless networks. With CSMACA a station willing to start a transmission has first to find the channel free for a given duration otherwise it will go into emphbackoff, i.e. refraining for transmitting for a randomly chosen delay. Performance analysis of a wireless network employing CSMACA regulation is not an easy task: except for simple network configuration analytical solution of key performance indicators (KPI) cannot be obtained hence one has to resort to formal modelling tools. In this paper we present a performance modelling study targeting different kind of CSMACA based wireless networks, namely: the IEEE 802.11 Wireless Local Area Networks (WLANs) and the 802.11p Vehicular Ad Hoc Networks (VANETs), which extends 802.11 with priorities over packets. The modelling framework we introduce allows for considering: i) an arbitrarily large number of stations, ii) different traffic conditions (saturatednonsaturated), iii) different hypothesis concerning the shared channel (idealnonideal). We apply statistical model checking to assess KPIs of different network configurations.

Performance of the CRMAC with Channel Fading and Capture Effect under Practical Traffic Scenarios for VANETs In this paper, performance of cooperative relaying medium access control (CRMAC) protocol 1 is investigated for vehicular ad hoc networks (VANETs) with channel fading and capture effect under practical traffic scenarios. Though the present analysis based on idle channel condition, in reality, the performance depends on channel fading and capture effect. To understand actual performance the real traffic scenario is needed. An analytical model based on Markov chain model is presented. The expressions of frame capture probability, probability of successful transmission, probability of unsuccessful transmission and throughput are obtained. Realistic traffic model is generated in SUMO. Simulation results are presented.