Network lifetime maximization has received continuous attention as green computing in wireless sensor networks. Recently, controlled mobility–based green computing has witnessed significant attention from academia and industrial research labs. It is due to the growing number of sensor-based services in mobility friendly nonhostile environments in our daily life. The intelligent mobility–aided repositioning of sensors is significantly challenging considering the critical constraints including irregular power depletion, static normal sensors, the correlation between sensor position, and coverage and connectivity. In this context, this paper proposes a network lifetime maximization framework based on balanced tree node switching. Specifically, a balanced tree–based network model for wireless sensor networks is designed focusing on energy consumption of sensor nodes in tree-based networks. The problem of lifetime maximization in tree-based network is identified considering energy loss rate, path load, and balancing factor. Two node-shifting algorithms are developed, namely, energy-based shifting and load-based shifting for balancing tree-based network in terms of energy. Analytical and simulation experiment–based comparative performance evaluation attests the benefit of the proposed framework as compared to the state-of-the-art techniques considering a number of energy-oriented metrics for wireless networks.