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Due to the characteristics of wireless channels, utility-based resource management in wireless networks requires a set of mechanisms that are different from those for wireline networks. This paper explores in detail why and how the requirements are different. In particular, we analyze the wireless network performance to find out the scheduling algorithm that maximizes total utility of the system. Unlike previous studies, this paper focuses on scenarios in which wireless networks are not fully loaded and all of the users are best-effort data users, i.e., there is no streaming user. Our first key conclusion is that Kleinrock's Conservation Law provides a valuable means to accurately capture the perceived rates of best-effort users in such systems. The queueing analysis further indicates that, within periods during which channel conditions are stable for each user, albeit differ from user to user, the max-utility scheduling algorithm can be derived using queueing theorem and can be readily implemented in actual systems for utility functions that are of exponential or log format. When further taking into account the time-variant nature of wireless channel conditions, our simulation results demonstrate that dynamic weighted fair queueing, with weights adjusted according to the channel conditions, can achieve highly desirable performance with great flexibility.