Research And Design Of Wireless Sensor Networks Node Based On TinyOS

In order to meet high reliability and high real-time of monitoring system of dangerous cargo transport based on the wireless sensor networks, it must requested low power consumption of sensor nodes and the real time response in events processing system, so that to implement real time data acquisition and processing in vehicle's running process, for dangerous goods vehicles provide a reliable guarantee of timely warning.In this paper, first of all, it introduced the concepts of wireless sensor networks, analyzed in depth the features of the sensor's each module and proposed a low power node design proposal based on micro-controller of Atmegal281 and RF chip of AT86RF230 to complete the circuit designing and implementation of each functional module. Secondly, there is a shortcoming of Tiny OS scheduling algorithm in wireless sensor networks system that it responses slowly on strong real-time tasks and with lowly task throughput. To solve this problem, paper analyzed the drawbacks of the current improvement strategies and proposes a new scheduling algorithm for multi-tasking queue. The algorithm uses real-time task scheduling and hierarchical scheduling in priority task. It not only can dynamically change the priority of the task, but also increase the task time-out interrupt mechanism so that it meets the response of high real-time and priority task and lower priority tasks can be executed in the appropriate time. Thus it increases the throughput of the system executes tasks. The test showed that for the limited resource of wireless sensor networks, the scheduling algorithm is very practical. Finally, the paper designed a small monitoring system for dangerous cargo. It not only completes the program design of the root nodes and sensor nodes and designs the monitoring software on computer to show the data that the sensor nodes collected.Overall test showed that it reduces loss of data and delay of waiting for receiving data in the running process of the system, therefore, it improves the timeliness and stability of system. The collected data is accuracy to meet the requirements of dangerous cargo monitoring.