传感器网络能量有效空中重编程协议研究

项目名称： 传感器网络能量有效空中重编程协议研究

项目编号： No.61461017

项目类型： 地区科学基金项目

立项/批准年度： 2015

项目学科： 无线电电子学、电信技术

项目作者： 沈重

作者单位： 海南大学

项目金额： 43万元

中文摘要： 无线传感器网络一旦部署，需通过有效方式对节点及传感系统进行更新与功能改造。课题针对现有空中重编程协议进展，以传感器节点能量有效为目标，提出基于MAC层、网络层与传输层的跨层无线空中重编程协议。课题主要研究IEEE 802.15.4自适应接入机制，解决基于竞争与随机访问的MAC层自适应最优竞争窗口算法；研究节点最优节点度选择策略，解决基于节点发射功率的分布式功率控制算法；最终集信道接入、功率控制与拓扑控制于一体，构建系统仿真平台和实际测试平台。课题目标提出优化协议，最大限度的减少接入碰撞概率并获得较高的吞吐量，同时减少节点能量损耗，打破传感节点程序低效更新僵局，在无线传感器网络空中重编程协议关键技术的信道接入、功率控制等方面寻求突破与创新，形成具有自主创新的知识产权与专利。

中文关键词： 无线传感器网络；空中重编程协议；自适应最优化竞争窗口；分布式传输功率控制；拓扑控制

英文摘要： Once a wireless sensor network is set up, embedded nodes and the sensing system requires functional update and reprogramming.This proposal is based on state-of-the-art WSN reprogramming over the air protocols, initiates a novel cross-layer WSN reprogramming over the air protocol regarding MAC，routing and networking layers aiming at nodes and system engergy-efficiency.The study focuses on the research of IEEE 802.15.4 adaptive access mechanism, which can provide MAC layer adaptive optimal contention window algorithm considering competition and random access. Besides, it studys the best node degree selection strategy which can solve the distributed power control issues considering node transmission power. Ultimately, The study assemblages channel access, power control and topology control in one set, builds up a system simulation platform and tests reprogramming over the air algorithms using TinyOS platform. The optimised protocols reduce the collide probability during accessing, attain relatively high throughput capacity and also reduces node energy loss to boost the energy efficiency. The study seeks for new breakthroughs and innovations on key technologies in WSN reprogramming over the air protocol regarding aspects such as channel access and power control, which will also establish new patents and intellectual property right.

英文关键词： Wireless Sensor Networks;Reprogramming over the Air;Adaptive Optimal Contention Window;Distributed Transmission Power Control;Topolopy control