## 1 Introduction  
With the rapid development of microprocessor technology and embedded systems, the number, function, and handling capacity of sensing devices has rapidly developed [1; 2]. A significant number of sensing devices is being applied to various applications in a large scale [3; 4; 5; 6], such as intelligent transportation systems [7; 8] and smart grids or smart health [9; 10], among others. These capabilitiescan also be extended into production, manufacturing, logistics, and maintenance areas, in which communication capabilities combined with data analysis and advances in Cyber Physical Systems (CPS) provide the grounds for the advent of industry 4.0 environments [11; 12; 13; 14]. Reports from Cisco show that the size of various embedded perceptual devices connected to the network is now unprecedented [15; 16]. Since 2011, devices connected to the Internet of things on the earth (such as industrial sensing devices and smart phones, etc.) have exceeded the human population, reaching nine billion devices. It is expected that by 2020, 24 billion sensing devices will be connected to the network [15; 16]. This large number of sensing devices is linked to the network, forming a new network structure and computing model called the Internet of Things (IoTs) [2; 8; 13; 15; 16; 17; 18], or the Edge network [19]. The sensor network and cloud network combine to form the Sensor-Cloud Network (SCN) [20; 21; 22]. In SCN, the deployed sensor nodes are no longer just for specific applications, but are unified by the cloud to accept application requests. Then, the cloud releases the requirements of the application to the sensor nodes for the corresponding perception and data collection. The sensor nodes then accept the cloud command and operate the site accordingly. Thus, the application, scope, and depth of sensor networks are significantly augmented. Industrial Wireless Sensor Networks (IWSNs) are an important application field of Wireless Sensor Networks [13; 14]. The trend in the field of industrial automation is the use of wireless technology and wireless control applications [23]. In all kinds of industrial applications, wireless sensor nodes are widely used because of their small size, flexible deployment, low requirements for deployment in an environment, and wireless automatic networking [24; 25; 26; 27; 28]. WirelessHART, the first open wireless communication standard, which is specially designed for applications in industrial automation, was released in September 2007. Unlike general sensor networks, in the WirelessHART network, normal sensors are connected to actual devices to collect specific environmental data [29]. For example, in an industrial production line, wireless sensor nodes can be deployed flexibly and change with the production line, allowing for the accurate collection of images and sounds during production. As a result, the mechanical conditions in the production line can be monitored in real time. Once an abnormal situation is monitored, it is quickly reported to the control center and corresponding control measures to ensure the efficiency and safety of production are initiated to avoid loss of property and personnel [13; 14]. However, an industrial wireless sensor network is relatively sensitive to communication delay when compared to other applications. If an emergency is not handled in a timely manner, this may result in significant loss of personnel and property [13; 14; 18; 23; 30; 31; 32; 33]. For example, in the monitoring of an industrial smelting furnace, when the temperature of the smelting furnace reaches a certain value it must be treated in time. If the temperature is too high and not processed in time, it will cause the explosion of the smelting furnace and the loss of personnel and property. If the temperature is too low, it will solidify the metal liquid of the smelting furnace and damage the smelting furnace and cause property loss [13; 14]. While in the industrial setting, these critical values last for a short time and must be processed in a timely manner.