摘要： 精准描述无线传感器网络(WSN)中受干扰节点的性能,对拥塞控制和速率分配等无线协议的有效运作具有重要意义。研究表明物理模型(PRR-SINR模型)在现有干扰模型中准确率较高,为此,分别提出集中式和分布式算法用于建立WSN节点的PRR-SINR模型。集中式算法通过一个中心节点控制节点收发测量包,使每个节点可以进行逐步建模;分布式算法则依赖每个节点自主控制收发包状况进行建模。在含有17个TelosB节点的WSN中对算法进行性能评估,结果表明,2种算法均能在保证高精确度的情况下,快速、低开销地对网络中的所有节点建立PRR-SINR模型。

关键词: 无线干扰, 干扰建模, 物理模型, 无线传感器网络, 集中式算法, 分布式算法

Abstract: Measuring the performance of those nodes in Wireless Sensor Network(WSN) suffering from interference is meaningful for protocols such as congestion control and link scheduling.Recent studies suggest that the physical model(PRR-SINR model) is significantly more accurate than existing interference models.This paper proposes a central algorithm and a distributed algorithm to build the PRR-SINR model for every node in a WSN respectively.The central algorithm uses a node to send commands to tell other nodes in the network when to receive/broadcast measurement packets.Thereby each node will build the PRR-SINR model according to the commands.In the distributed algorithm,however,each node builds the model all by itself.This paper evaluates the two algorithms in a network which is composed of 17 TelosB nodes.Experimental result shows that the models built by both of the proposed algorithms achieve high accuracy,while the overhead is significantly low.

Key words: wireless interference, interference modeling, physical model, Wireless Sensor Network(WSN), central algorithm;distributed algorithm 

中图分类号: 

• TP393