Aiming at the data acquisition in large sparse sensor networks, a network architecture using the ubiquitous existence of mobile agents in environment to connect sparse sensors and a 2-dimensional grid random walk analysis model are proposed in this paper. The proposed sensor network model consists of three abstract layers, namely, bottom layer composed of wireless sensors, the middle layer composed of various transportation agents, and the top layer composed of access points/central repositories. The specific implementation principle is that the mobile transport agents located in the middle layer collect data from the wireless sensors distributing at the bottom layer and buffer the data, and after wandering transport, finally deliver the data collected from the wireless sensors at the bottom layer to the necessary access points at the top layer for necessary storage and processing, so as to achieve the data acquisition of the entire sensor network. The theoretical analysis and simulation experiment results show that the proposed sensor netwoks model based on mobile transport agents not only has robustness and scalability, but also has obvious advantages over base station network model and Ad-hoc network model in terms of sensor power consumption, data success rate and infrastructure invested cost.