## 1 Introduction  
Wireless sensor and actuator networks (WSANs) comprise groups of sensors and actuators linked by a wireless medium [1, 2]. Sensor nodes collect environment information and send their sensory data to actuators via wireless multi-hop communications. Actuators make decisions and then take actions upon the environment based on the available sensor data. Due to the use of actuators, WSANs have ability to change the behavior of environments. Consequently, they can be widely adopted for many applications, including environmental monitoring and control, industrial machine condition, building automation, _etc._ In the building automation application [3, 4, 5], WSANs can be utilized to control and maintain the temperature inside buildings. Sensors gather the temperature in the zones of interest and send their signals to the controller. The controller with the control algorithm uses the error between the set-point and the measured temperature values to find an appropriate supply air temperature, and then commands the actuator to perform actions. This procedure continues until the temperature in the zones reaches the desired value. In WSANs, there are several node constraints in bringing the sensing data from the network to actuators, such as limited energy resources, transmission powers, and radio ranges of the wireless medium. Accordingly, sensor nodes cannot directly send their sensing data to actuators. All nodes in the network must help each other by relaying the sensing data. Routing plays an important role in this multi-hop communication scenario. Due to the limited power of sensor nodes [1, 2, 6, 7, 8, 9], an energy-efficient route setup is required. Nodes should not consume much of their energy resources due to the influence of the routing mechanism [1, 10, 11, 12]. If sensor nodes cannot transmit the sensing data to the actuators due to insufficient power and the actuators do not update their actions, the desirable control objective will not be achieved. Thus, energy-efficient schemes for prolonging the network lifetime should be considered in WSAN routing design. In addition, the communication among sensors and actuators over unreliable wireless channels can cause the occurrence of packet loss and delay, which degrades the performance of the control system [2, 7]. If we neglect the characteristics of the wireless connection, a desired control application will not be working properly. Accordingly, the understanding of the relationship between the wireless network and the control system is required. According to the research literature, as presented in Section 2, most work related to routing protocols for WSANs [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26] concentrates on either the wireless communication or the control perspectives. Little work has been done on studying the cooperation between the communication and the control [3, 4, 27]. Furthermore, the energy consumption of sensor nodes as a major concern in WSANs [1, 2] has not been yet investigated in the existing works. Based on these knowledge gaps, how to design an efficient routing protocol for WSANs is still an open research issue. In this paper, we are going to investigate how to design a new routing algorithm for WSANs that can satisfy both communication and control perspectives according to the simulation study. For this purpose, we first study the effects of the AODV routing algorithm on WSANs. We focus on the energy consumption of nodes in a network and the control system response which are the major concerns from wireless networking and control perspectives [2]. Secondly, the proposed routing solution for improving both the energy consumption and the control system response is introduced. The major contributions of our paper include:* How the AODV routing mechanism impacts the energy consumption and the resulting control performances are investigated. We provide both multi-hop wireless networks and control functions with communication and control performance metrics for studying this issue.