Power efficiency is the most constraining requirement for viable operation of battery-powered networked sensors. Conventionally, dynamic power management (DPM) is used to put sensor nodes into different states such as active, idle, and sleep, each consuming a certain level of power. Within the active state, communication operational states, such as receive and transmit consume different levels of nodal power. This thesis shows how DPM states and protocol operational states can be combined into a single stochastic model to finely evaluate the power consumption performance of a medium access control (MAC) protocol. The model is formulated as a semi-Markov decision process (SMDP) wherein the node's states, sojourn times, and transition probabilities are controlled by a virtual node controller. The overall operation of a communication protocol is viewed as a randomized policy for the SMDP, and the long-run average cost per unit time measures the energy efficiency of the protocol.