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Modeling mobility and user behavior is of fundamental importance in testing the performance of protocols for wireless data networks. While several models have been proposed in the literature, none of them can at the same time capture important features such as geographical mobility, user generated traffic, and wireless technology at hand. When collectively considered, these three aspects determine the user-perceived QoS-level, which, in turn, might have an influence on mobility of those users (we call them QoSdriven users) who do not display constrained mobility patterns, but they can decide to move to less congested areas of the network in case their perceived QoS-level becomes unacceptable. In this paper, we introduce the WiQoSM model which collectively considers all the above mentioned aspects of wireless data networks. WiQoSM is composed of i) a user mobility model, ii) a user traffic model, iii) a wireless technology model, and iv) a QoS model. Components i), ii), and iii) provide input to the QoS model, which, in turn, can influence the mobility behavior of QoS-driven users. WiQoSM is very simple to use and configure, and can be used to generate user and traffic traces at the APs composing a wireless data network. WiQoSM is shown to be able to generate traces which resemble statistical features observed in traces extracted from real-world WLAN deployments. Furthermore, WiQoSM has the nice feature of allowing fine tuning of disjoint set of parameters, in order to influence different statistical properties of the generated traces, and of providing the network designer with a high degree of flexibility in choosing network parameters such as number of users and APs, wireless channel technology, traffic mix, and so on. Given the above features, WiQoSM can be a valuable tool in the simulation of wireless data network protocols.
Mobility modeling, user behavior modeling, QoS-driven mobility, wireless data networks

G. Resta and P. Santi, "WiQoSM: An Integrated QoS-Aware Mobility and User Behavior Model for Wireless Data Networks," in IEEE Transactions on Mobile Computing, vol. 7, no. , pp. 187-198, 2007.
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