In wireless sensor networks, continued operation of battery-powered devices plays a crucial role particularly in remote deployment. The lifetime of a wireless sensor is primarily dependent upon battery capacity and energy efficiency. In this paper, reduction of the energy consumption of heterogeneous devices with different power and range characteristics is introduced in the context of duty scheduling, dynamic adjustment of transmission ranges, and the effects of IEEE 802.15.4-based data aggregation routing. Energy consumption in cluster-based networks is modeled as a mixed-integer linear and nonlinear programming problem, an NP-hard problem. The objective function provides a basis by which total energy consumption is reduced. Heuristics are proposed for cluster construction (Average Energy Consumption and the Maximum Number of Source Nodes) and data aggregation routing (Cluster-based Data Aggregation Routing) such that total energy consumption is minimized. The simulation results demonstrate the effectiveness of balancing cluster size with dynamic transmission range. The heuristics outperform other modified existing algorithms by an average of 15.65% for cluster head assignment, by an average of 22.1% for duty cycle scheduling, and by up to 18.6% for data aggregation routing heuristics. A comparison of dynamic and fixed transmission ranges for IEEE 802.15.4-based wireless sensor networks is also provided.