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首页> 外文期刊>Journal of supercomputing >Group improved enhanced dynamic frame slotted ALOHA anti-collision algorithm
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Group improved enhanced dynamic frame slotted ALOHA anti-collision algorithm

机译:组改进的增强型动态帧时隙ALOHA防冲突算法

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摘要

With the development of information technology and declining in the cost of tags, radio frequency identification (RFID) system has become more and more popular, which has been widely used in a lot of areas, such as logistics tracking, animals identification, medicine, electronic toll collection, inventory, asset management, manufacturing, etc. However, when we use RFID technology to identify the objects, tag collision is one of the important factors to influence the identification efficiency. Currently, Aloha-based algorithm is one of the popular anti-collision algorithms which performs well when the number of tags is small. But it is not very efficient for cases with large number of tags and some areas which tags' number can be estimated, such as warehouse, supermarket, the production lines of smart factory and so on. So in this paper, we proposed a new anti-collision algorithm called group improved enhanced dynamic frame slotted ALOHA (GroupIEDFSA) by estimating the number of unread tags first, comparing the maximum frame size and dividing tags into groups when the number of tags which are activated is large. What is more, compared with enhanced dynamic frame slotted ALOHA (EDFSA) algorithm in the process of identification, GroupIEDFSA algorithm will combine new group based on the unread tags' number. Simulation results show that the efficiency of GroupIEDFSA algorithm system improves by 20 % in time and over 50 % in rounds than EDFSA algorithm in the standard mode, and increases by 1 % in time when we used fast mode.
机译:随着信息技术的发展和标签成本的下降,射频识别(RFID)系统越来越流行,已广泛应用于物流跟踪,动物识别,医药,电子等许多领域。收费,库存,资产管理,制造等。但是,当我们使用RFID技术识别对象时,标签碰撞是影响识别效率的重要因素之一。当前,基于Aloha的算法是流行的防冲突算法之一,当标签数量较少时,该算法表现良好。但是对于具有大量标签并且在某些可以估计标签数量的区域(例如仓库,超级市场,智能工厂的生产线等)的情况,效率不是很高。因此,在本文中,我们提出了一种新的防冲突算法,称为组改进增强型动态帧时隙ALOHA(GroupIEDFSA),方法是先估计未读标签的数量,然后比较最大帧大小,然后在标签数量为激活很大。而且,在识别过程中,与增强型动态帧时隙ALOHA(EDFSA)算法相比,GroupIEDFSA算法将根据未读标签的编号组合新的组。仿真结果表明,与标准模式下的EDFSA算法相比,GroupIEDFSA算法系统的效率在时间上提高了20%,在轮次中提高了50%以上,而在使用快速模式时,效率提高了1%。

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