Design of wireless sensor nodes based on the characteristics of wireless sensor networks

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Design of wireless sensor nodes based on the characteristics of wireless sensor networks [Copy link]

Based on the characteristics of wireless sensor networks, this paper designs a wireless sensor node for temperature and humidity measurement with CC2430 chip as the core. In order to reduce the power consumption of nodes, improvements are made on the basis of ZigBee protocol stack, and three working modes, namely idle, triggered and active, are designed for sensor nodes, so that nodes can control the timing and rate of sampling according to actual needs to reduce the energy consumption of sensor nodes for wireless communication, thereby meeting the design requirements of wireless sensor networks for low power consumption of nodes. At the same time, the life of sensor nodes is predicted based on known parameters and verified through experiments.

0 Introduction

Wireless Sensor Networks (WSN) is a multi-hop self-organizing network system composed of a large number of cheap micro sensor nodes deployed in the monitoring area, which is formed by wireless communication. Its purpose is to collaboratively sense, collect and process the information of the sensed objects in the network coverage area and send it to the observer. Wireless sensor networks help people better perceive the objective world, greatly expand the functions of existing networks and the ability of human beings to understand the world, and have broad application prospects.

Nodes in wireless sensor networks are generally powered by batteries, which have very limited power. For wireless sensor networks with tens of thousands of nodes, it is very difficult or even impossible to replace the batteries. However, the survival time of wireless sensor networks is required to be as long as several months or even years. Therefore, how to save the battery energy of wireless sensor networks as much as possible without affecting the functions has become a core issue in the design of wireless sensor network software and hardware, and is also the focus of current research institutions at home and abroad.

The sensor node consists of four parts: processor module, communication module, sensor module and energy supply module. Among them, the first three modules consume energy. Since the sensor module consumes relatively low energy, the current research focuses on the processor module and the communication module. The energy-saving strategies of the processor module usually include dynamic voltage scaling (DVS) and dynamic power management (DPM). The working principle of the former is that when the computing load is low, by reducing the operating voltage and frequency of the microprocessor, thereby reducing the processing power, the energy consumption of the microprocessor can be saved; the latter is to use the fact that when there is no event of interest around the node, some modules are in an idle state, and these components are turned off or adjusted to a lower energy consumption state to extend the life of the node. The communication module consumes the most energy, so it is particularly important to formulate an effective energy-saving strategy for it, mainly including controlling the node communication traffic, reasonably arranging the work sleep time, and adopting multi-hop communication methods.

This paper adopts three alternative working modes through the selection and configuration of hardware and flexible design of software, so that the nodes can set parameters according to the actual situation, reduce the energy consumption of the nodes for wireless communication, achieve the low power consumption goal of wireless sensor network nodes, and complete relevant tests to verify the design scheme.

1 Node Hardware Design

ZigBee technology is a short-range, low-power, low-data-rate, low-complexity bidirectional wireless communication technology suitable for wireless sensor networks. Currently, many companies have their own mainstream ZigBee chips, as shown in Table 1. After comprehensive comparison, the design uses the CC2430 chip, which is the world's first SoC solution supporting the ZigBee protocol provided by Chipcon. It integrates the ZigBee RF front end, memory and microcontroller on a single chip. The maximum working current consumption of 27 mA and the current consumption of 0.9μA in sleep mode make it very suitable for the low power consumption requirements of wireless sensor nodes.

In this paper, the TSZ-CC2430 development system of Shenzhen Jintu Xuang Co., Ltd. is used, the streamlined ZigBee protocol stack of the University of Mississippi is transplanted, and a temperature and humidity sensor node for environmental monitoring is designed with the CC2430 chip as the core. The low power consumption goal of the sensor node is achieved through software and hardware design methods.

The hardware connection is shown in Figure 1. The RF chip CC2430 integrates the processor module and the wireless communication module, which greatly simplifies the design of the RF circuit.

Figure 1 Schematic diagram of wireless sensor node hardware connection

The operating voltage of the temperature and humidity sensor SHT10 is 2.4~5.5 V, the humidity measurement accuracy is ±4.5%RH, and the temperature measurement accuracy is ±0.5℃ at 25℃. SHT10 uses two serial lines to communicate data with the processor. The serial clock line SCK is responsible for the communication synchronization between the two, and the data line DATA is used to read data. DATA changes state after the falling edge of SCK and is only valid on the rising edge of the SCK clock. During data transmission, DATA must remain stable when the SCK clock is high. To avoid signal conflicts, the microprocessor should drive DATA at a low level, so the DATA line uses a 10 kΩ pull-up resistor.

For the power supply module, the node volume was considered during the initial design, and a button battery was used. However, in later tests, it was found that the voltage of the CR2032 button lithium battery with a capacity of 210 mAh immediately dropped from 3.0V to 2.4V when the node was started, making it difficult to drive the sensor node to work normally. The reason for this was that the current consumption of the CC2430 radio frequency exceeded the load capacity of the battery, so two ordinary No. 7 batteries were used to provide a 3.3V power supply.

2 Node Software Design

The main process of the node program is shown in Figure 2, which mainly includes two parts: data acquisition and wireless communication. Considering the low power consumption of the sensor node, the software design focuses on the processing of the working mode.

Most of the node energy consumption is consumed in the wireless communication part. The energy consumed by the sensor node to transmit 1b to 100m by wireless can be used to execute 3000 instructions. It can be seen that how to effectively transmit data and reasonably arrange the working sleep time has a direct impact on saving the energy consumption of sensor nodes, which is also an issue that should be considered in software design.

In order to achieve low power consumption and better measurement performance of sensor nodes, the design adopts the selection of working mode. By wirelessly configuring the working parameters of sensor nodes, the nodes can control the timing and rate of collection according to actual needs, thereby reducing energy consumption and extending the life of nodes. The node work is divided into three modes: idle mode, trigger mode, and active mode. Among them, the node in idle mode is in a dormant state most of the time, and only wakes up periodically to check whether there is a control command from the server to better save energy consumption; in trigger mode, RF is turned off, and only when the sensor measurement value reaches the set threshold will RF be triggered for wireless data transmission and reception. At the same time, the corresponding sampling rate can be selected according to different thresholds, which is suitable for monitoring and early warning of emergencies such as forest fires; in active mode, the sensor node collects and sends data according to the configured sampling rate, periodically goes into dormancy and wakes up automatically. The mode selection and corresponding parameter configuration are all from the sensor network server. For sensor nodes, this work is completed during the wireless reception process.

3 Low power consumption test

In view of the characteristics of power consumption test, the working mode of the sensor node is set to active mode, that is, the node periodically collects, sends, and sleeps to obtain working parameters at different stages, and performs life prediction and verification based on certain methods.

The node working parameters obtained through testing are shown in Table 2, and the working voltage is 3.3 V. It can be seen that the current consumption of the node is large when it is working, and much smaller in the sleep state. Therefore, in order to ensure a longer working life under limited power supply, it is necessary to set the node to intermittent working mode, that is, work and sleep are alternated periodically. The following formula is the node life prediction formula:

Where: Td is the number of working days of the node; Qb is the available battery capacity; tw is the working time in each cycle; ts is the sleep time in each cycle; Iw is the working current; Is is the sleep current. According to the pre-humidity formula and assuming that the available battery capacity is 1 000 mAh, the number of working days under different sleep times can be predicted as shown in Table 3. For a specific sensor node, the working time occupied by data collection, processing, and transmission in a single cycle is certain, and the variable is the sleep time. By controlling the different sleep times of the sensor node, its corresponding working life characteristics can be obtained. It can be seen from Table 3 that with the increase of the sleep time, the working life of the node is extended. When the sleep time is 60s, that is, 1 min for 1 data collection and transmission, the sensor node can be used continuously for about 1 year.

In the actual test process, the comparison experiment was conducted using Fuant lithium battery ER14250H and ordinary No. 7 Nanfu alkaline battery. The former has a battery capacity of 1,200 mAh, while the latter has no capacity mark. However, according to the test instructions on its official website, it is estimated to be around 1,200 mAh. Considering the self-discharge effect of the battery during long-term testing, its actual available capacity must be smaller, and the prediction results of the assumed value of 1,000 mAh are still used for comparison. The actual number of working days of the node obtained from the experiment is shown in Table 3. The test results are generally consistent with the predicted trend. The number of working days of the sensor node is related to its sleep time in a working cycle. Therefore, in order to extend the life of the sensor node, it is necessary to determine the working sleep time of the node according to the actual situation, and try to arrange more sleep time under the premise of ensuring network stability and data reliability. In addition, in the networking test, the single-hop distance of the sensor node is about 60 m, the self-organizing characteristics are good, the sensor node can choose a better route to enter the network, and the server's data acquisition, monitoring, and control functions for the terminal sensor node are normal. The temperature and humidity sensing node implemented by this design is shown in Figure 3. The circuit consists of a CC2430 RF board and a sensor baseboard, which are connected through a 12 pin×2 interface for easy installation and use.

4 Conclusion

This paper introduces the design and implementation of a wireless sensor network node based on ZigBee technology, and conducts tests. The experimental results show that the sensor node has low power consumption characteristics, can implement flexible measurement and control through wireless, and meet the requirements of wireless sensor networks. At the same time, the node design method has a certain reference value, is easy to transplant and improve, and can be used for the measurement and control of other parameters. It is true that reducing power consumption can extend the service life of wireless sensor network nodes. If external energy such as light, wind, vibration, etc. can be used to enable sensor nodes to effectively self-supply, this will have positive significance for wireless sensor networks deployed in the field.