Energy-efficient data transmission is an important issue for mobile communication devices. In this paper, we study throughput and value-based packet scheduling over a wireless link under time and energy constraints. A mobile node is required to deliver multiple data streams to multiple receivers. These data streams may have different importance and incur different energy costs. In this research, point-to-point wireless data transmission is studied. The objective is to develop schemes that selectively transmit data streams at certain power levels so that the data throughput or the value of data delivery is maximized without violating the energy and time constraints. Exploiting the special properties of the throughput maximization problem, we propose an iterative algorithm that yields the optimal transmission schedule. The value maximization problem is formulated as a convex optimization problem and the optimal results can be obtained by solving the Kuhn-Tucker conditions. When time and transmission power are allocated at discrete slots and levels, respectively, a dynamic programming approach is proposed to find the optimal value.