Research On MAC Layer Energy-efficient For ZigBee Wireless Sensor Network

As communication technology, MEMS technology, embedded technology, orsomething is kept a watchful eye on at home and abroad. Wireless sensornetworks technology has been applied to remote control of dengerous areas,biomedical, national defense and some other. The majority nodes of wirelesssensor networks are to be energy-effcient and low-cost equipments, so theenergy problem has become the bottleneck to limit the development of WSNs,and energy-effcient issues have become hot spots. As the characteristics ofWSNs are energy-effcient, low-rate, ad-hoc networks, ZigBee suits Wirelesssensor networks. Therefore, the research on energy-effcient of WSNs becomevery meaningful based on Zigbee, espically MAC protocol based on Zigbee.MAC protocol not only deals with the issues, such as wireless channelcompetition, but also controls how to communication with RF wireless. SoMAC protocol based on ZigBee becomes the focus.In this paper, first review the development of ZigBee WSNs and energystrategy about ZigBee WSNs at home and abroad; then the design of ZigBeeis overviewed. Contexts are that ZigBee wireless sensor networks nodes arecomposed of ARM7+μC/OS-II. Hardware mainly is composed of controllerLPC2136based on32-bit ARM that produce in Philips and RF wirelesscommunication module is composed of CC2520and CC2591that produce inTI. Software mainly is composed of μC/OS-II which is the hard real-timeoperating system and ZigBee protocol stack. Last, MAC protocol isoverviewed. As Low Power Listening (LPL) Schemes using in asynchronousMAC protocol exist deficiencies, for example LPL Schemes use static valueof the polling interval, put forward the algorithm-adaptive listening, and builds the model that introduces the polling interval which can adjust thelength of the interval. As a result, the model can reduce the consumption aftersimulation verification.According to result of power consumption and communication distance,the node has good performance. Then introduce the adaptive listening modelin the node and do experiment to prove that node reduce the powerconsumption after using the model.