In this work we address the problem of coverage control of a group of mobile sensors in a convex and bounded environment which is subject to an isotropic Gaussian mixture (GM) model. We consider the case that the GM model is introduced by a known number of information sources with time-varying locations. We show by examples that in such a dynamic environment, it may not be possible and feasible for sensors to gain a nondecreasing and maximal reward. Instead, in the case of allowing sensors act

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... utonomously in the environment, we present the upper and lower bound of rewards of sensors. Finally, we give an algorithm using the sweep-pursuit-capture strategy for a group of sensors. Our result shows that after a finite time, we can possess upper and lower bounds of rewards for sensors at each time step before their next deployment.