Modeling and simulation of the IEEE 802.11e wireless protocol with hidden nodes using Colored Petri Nets

Abstract

Wireless technologies are continuously evolving, including features such as the extension to mid- and long-range communications and the support of an increasing number of devices. However, longer ranges increase the probability of suffering from hidden terminal issues. In the particular case of Wireless Local Area Networks (WLANs), the use of Quality of Service (QoS) mechanisms introduced in IEEE 802.11e compromises scalability, exacerbates the hidden node problem, and creates congestion as the number of users and the variety of services in the network grow. In this context, this paper presents a configurable Colored Petri Net (CPN) model for the IEEE 802.11e protocol with the aim of analyzing the QoS support in mid- and long-range WLANs The CPN model covers the behavior of the protocol in the presence of hidden nodes to examine the performance of the RTS/CTS exchange in scenarios where the QoS differentiation may involve massive collision chains and high delays. Our CPN model sets the basis for further exploring the performance of the various mechanisms defined by the IEEE 802.11 standard. We then use this CPN model to provide a comprehensive study of the effectiveness of this protocol by using the simulation and monitoring capabilities of CPN Tools.

Lightweight Anonymous Authentication and Key Agreement Protocol Based on CoAP of Internet of Things

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Modeling and Performance Analysis of Satellite Network Moving Target Defense System with Petri Nets

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Performance Analysis of Wireless Local Area Network for a High-/Low-Priority Traffic Ratio at Different Numbers of Access Categories

“…Nowadays, many works are devoted to study and improve the access method to the physical environment defined by IEEE 802.11 standard. A variety of research methods are used, for example, network simulator [2]; Markov chain [3]; Colored Petri Net [4]; machine learning [5]; to provide QoS to specific flows in network traffic, such as voice [11]; video [12]; downloading large files [13]; signaling [14], and integrated traffic [15].…”

“…As the higher-priority frames now have a better chance to be transmitted, the channel utilization is reduced. Many research works [2][3][4][5][6][7][8][9][10] are aimed to improve the performance of MAC sublayer by using different methods and research approaches [2,4,5]. Moreover, most of them aims to ensure the transmission of various traffic types with different requirements, however, the impact of different ratios of various traffic types on the network performance has not yet been studied.…”