Self-triggered sampling is an attractive paradigm for closed-loop control over energy-constrained wireless sensor networks (WSNs) because it may give substantial communication savings. The understanding of the performance of self-triggered control systems when the feedback loops are closed over IEEE 802.15.4 WSNs is of major interest, since the communication standard IEEE 802.15.4 is the de-facto reference protocol for energy-efficient WSNs. In this paper, a new approach to control several processes over a shared IEEE 802.15.4 network by self-triggered sampling is proposed. It is shown that the sampling time of the processes, the protocol parameters, and the scheduling of the transmissions must be jointly selected to achieve a good performance of the closed-loop system and an energy-efficient utilization of the network. The challenging part of the proposed analysis is ensuring globally uniformly ultimately boundedness of the controlled processes while providing efficient scheduling of the process state transmissions. Such a scheduling is difficult when asynchronous multiple control loops share the network, because transmissions over IEEE 802.15.4 are allowed only at certain time slots. The proposed approach establishes that the joint design of self-triggered samplers and the network protocol (1) ensures globally uniformly ultimately boundedness of each control loop, (2) reduces the number of sensor transmissions, and (3) increases the sleep time of the transmitting nodes. A new dynamic scheduling problem is proposed for the joint control of each process and network protocol adaptation. An algorithm is derived, which adapts the network parameters according to the self-triggered sampler of every control loop. Numerical examples illustrate the analysis and show the benefits of the approach. It is concluded that self-triggered control strategies over WSNs ensure desired control performance, reduce the network utilization, and reduce energy consumption only if the protocol parameters are appropriately regulated. (C) 2012 Elsevier Ltd. All rights reserved.