文献类型：期刊文献

英文题名：On MAC optimization for large-scale wireless sensor network

作者：Wang, Ji[1];Ren, Xiaoli[1];Chen, Fang-jiong[2];Chen, Yankun[2];Xu, Guobao[1]

机构：[1]Guangdong Ocean Univ, Sch Informat, Zhanjiang 524088, Guangdong, Peoples R China;[2]South China Univ Technol, Inst Elect & Informat, Guangzhou 510641, Guangdong, Peoples R China

年份：2016

卷号：22

期号：6

起止页码：1877

外文期刊名：WIRELESS NETWORKS

收录：SCI-EXPANDED(收录号：WOS:000379511200009)、、EI(收录号：20154301438375)、Scopus(收录号：2-s2.0-84944674880)、WOS

基金：This research was partially supported by the National Natural Science Foundation of China (NSFC) (Grant No. 41306050), the Guangdong Provincial Natural Science Foundation of China (Grant Nos. S2012010008261; 2015A030313617), and project of enhancing school with innovation of Guangdong Ocean University under Grant No. GDOU2014050228. Evaluation experts of this paper put forward the precious opinion, and his advice is very helpful to improving the quality of this paper, thank you.

语种：英文

外文关键词：Large-scale wireless sensor networks; Multi-level integrated MAC protocol; Overall network performance optimization

外文摘要：The media access control (MAC) performance of a large-scale wireless sensor network (L-WSN) determines the efficiency of the wireless communication channel. A good MAC protocol could reduce network energy consumption and network delay, which are two problems to be solved urgently in L-WSN. In this paper, we proposed a multi-level integrated MAC protocol (MI-MAC) to solve the overall performance optimization problem of L-WSN. Compared with other protocols, MI-MAC has two mainly improved performances: (1) It improved binary exponential backoff algorithm by twice back off strategy; (2) It designed a sending and receiving algorithm based on the threshold value to recognize control frames (small frames), which effectively avoids the collision probability of data frame. The simulation results show that the MI-MAC protocol improves network throughput and delay performance, significantly reduces energy consumption, and obtains overall network optimization.