1294 IEEE COMMUNICATIONS SURVEYS TUTORIALS.VOL.16.NO.3.THIRD QUARTER 2014 Managing RFID Data: Challenges,Opportunities and Solutions Lei Xie,Member.IEEE,Yafeng Yin,Student Member,IEEE,Athanasios V.Vasilakos,Senior Member,IEEE,and Sanglu Lu,Member IEEE Abstract-The advances of Radio-Frequency Identification In conventional RFID applications,the items are attached (RFID)technology have significantly enhanced the capability of with RFID tags and densely placed in a large scale.The RFID capturing data from pervasive space.It becomes a great challenge tag is a small mircochip attached with an antenna in a package in the information era to effectively understand human behavior, mobility and activity through the perceived RFID data.Focusing During the scanning process,the RFID reader powers up and on RFID data management,this article provides an overview of transmits a continuous wave to energize the tags.The tag then current challenges,emerging opportunities and recent progresses responds to the reader with tag-carried information by mod- in RFID.In particular,this article has described and analyzed ulating the backscattered signals.The reader further decodes the research work on three aspects:algorithm,protocol and performance evaluation.We investigate the research progress in the signal and obtains the corresponding information 678 RFID with anti-collision algorithms,authentication and privacy In this way,the RFID system can not only "identify"but protection protocols,localization and activity sensing,as well as also "locate"the labeled item,by providing the information performance tuning in realistic settings.We emphasize the basic including the "identity"as well as the "location".Here,the principles of RFID data management to understand the state- "identity"is precise information extracted from the tag,while of-the-art and to address directions of future research in RFID. the "location"is usually inaccurate information estimated according to environmental parameters.Furthermore,these Index Terms-RFID,data management,anti-collision algo- RFID applications often involve lots of human activities,in rithms,authentication and privacy protection,localization and order to precisely understand human behavior,mobility and activity sensing,performance evaluation. activity through the perceived RFID data,it is essential to ef- fectively manage RFID data to extract the useful information, I.INTRODUCTION while ensuring the overall performance.How to effectively manage RFID data?As a matter of fact,several properties are S A TECHNOLOGY for automated identification of ob- jects,RFID(Radio-Frequency IDentification)has gained essentially required for effective RFID data management.We elaborate on these properties as follows: significant momentum in the past few years.Recently RFID has been more and more frequently introduced in applications Efficiency:while interrogating a number of tags,two met- like retail and distribution,target monitoring and tracking,etc, rics are highly pertinent to efficiency,i.e.,time efficiency as elaborated in literatures [1],[2],and [3].The most impor- to reduce the total scanning time,and energy efficiency tant reason of such phenomenon is that,by leveraging the to reduce the total power consumption. RFID technology,we are able to embed the intelligence into Trustworthy:the communication between the reader each physical object in a low-cost approach.In this way,the and tags should be both privacy-preserving and anti- "passive intelligence"is effectively realized in the ubiquitous counterfeiting. space,which can be regarded as a right candidate for green Localizability:the objects or people should be accurately communications [4][5].As such a novel technology,RFID located within the specified range of time delay. has provided us with 1)the capability to uniquely identify Reliability:in realistic settings,the RFID system should the objects in the physical world and 2)a passive,battery- be able to tackle with issues like signal interference, free interconnection mechanism.Furthermore,the dropping multi-path effect and energy absorption. tag costs and vigorous RFID standardization have accelerated These properties basically belong to the nonfunctional the wide-spread usage of the RFID technology. requirements for RFID systems.According to the above descriptions,it is essential to provide some mechanisms Manuscript received May 8.2013:revised November 15,2013.L.Xie,Y. to effectively satisfy the above nonfunctional requirements Yin,and S.Lu are supported in part by National Natural Science Foundation of China under Grant No.61100196,61321491.91218302:JiangSu Natural Therefore,several new research topics are necessarily to Science Foundation under Grant No.BK2011559:Key Project of Jiangsu be addressed for RFID data management.Specifically,they Research Program under Grant No.BE2013116:EU FP7 IRSES MobileCloud include anti-collision algorithms,authentication and privacy Project under Grant No.612212.Lei Xie is the corresponding author. L.Xie,Y.Yin,and S.Lu are with the State Key Laboratory for Novel protection protocols,localization and activity sensing,as well Software Technology.Nanjing University,China (e-mail:Ixie@nju.edu.cn as performance tuning in realistic settings.Fig.I illustrates yyf@dislab.nju.edu.cn,sanglu@nju.edu.cn). A.Vasilakos is with University of Western Macedonia,Greece (e-mail: these research topics corresponding to the above properties.In vasilako@ath.forthnet.gr). fact,these research topics are not independent of each other, Digital Object Identifier 10.1109/SURV.2014.022614.00143 but are correlated with each other.Besides,since these topics 1553-877X/14/$31.00©20141EEE1294 IEEE COMMUNICATIONS SURVEYS & TUTORIALS, VOL. 16, NO. 3, THIRD QUARTER 2014 Managing RFID Data: Challenges, Opportunities and Solutions Lei Xie, Member, IEEE, Yafeng Yin, Student Member, IEEE, Athanasios V. Vasilakos, Senior Member, IEEE, and Sanglu Lu, Member, IEEE Abstract—The advances of Radio-Frequency Identification (RFID) technology have significantly enhanced the capability of capturing data from pervasive space. It becomes a great challenge in the information era to effectively understand human behavior, mobility and activity through the perceived RFID data. Focusing on RFID data management, this article provides an overview of current challenges, emerging opportunities and recent progresses in RFID. In particular, this article has described and analyzed the research work on three aspects: algorithm, protocol and performance evaluation. We investigate the research progress in RFID with anti-collision algorithms, authentication and privacy protection protocols, localization and activity sensing, as well as performance tuning in realistic settings. We emphasize the basic principles of RFID data management to understand the state￾of-the-art and to address directions of future research in RFID. Index Terms—RFID, data management, anti-collision algo￾rithms, authentication and privacy protection, localization and activity sensing, performance evaluation. I. INTRODUCTION AS A TECHNOLOGY for automated identification of ob￾jects, RFID (Radio-Frequency IDentification) has gained significant momentum in the past few years. Recently RFID has been more and more frequently introduced in applications like retail and distribution, target monitoring and tracking, etc, as elaborated in literatures [1], [2], and [3]. The most impor￾tant reason of such phenomenon is that, by leveraging the RFID technology, we are able to embed the intelligence into each physical object in a low-cost approach. In this way, the “passive intelligence” is effectively realized in the ubiquitous space, which can be regarded as a right candidate for green communications [4][5]. As such a novel technology, RFID has provided us with 1) the capability to uniquely identify the objects in the physical world and 2) a passive, battery￾free interconnection mechanism. Furthermore, the dropping tag costs and vigorous RFID standardization have accelerated the wide-spread usage of the RFID technology. Manuscript received May 8, 2013; revised November 15, 2013. L. Xie, Y. Yin, and S. Lu are supported in part by National Natural Science Foundation of China under Grant No. 61100196, 61321491, 91218302; JiangSu Natural Science Foundation under Grant No. BK2011559; Key Project of Jiangsu Research Program under Grant No. BE2013116; EU FP7 IRSES MobileCloud Project under Grant No. 612212. Lei Xie is the corresponding author. L. Xie, Y. Yin, and S. Lu are with the State Key Laboratory for Novel Software Technology, Nanjing University, China (e-mail: lxie@nju.edu.cn, yyf@dislab.nju.edu.cn, sanglu@nju.edu.cn). A. Vasilakos is with University of Western Macedonia, Greece (e-mail: vasilako@ath.forthnet.gr). Digital Object Identifier 10.1109/SURV.2014.022614.00143 In conventional RFID applications, the items are attached with RFID tags and densely placed in a large scale. The RFID tag is a small mircochip attached with an antenna in a package. During the scanning process, the RFID reader powers up and transmits a continuous wave to energize the tags. The tag then responds to the reader with tag-carried information by mod￾ulating the backscattered signals. The reader further decodes the signal and obtains the corresponding information [6][7][8]. In this way, the RFID system can not only “identify” but also “locate” the labeled item, by providing the information including the “identity” as well as the “location”. Here, the “identity” is precise information extracted from the tag, while the “location” is usually inaccurate information estimated according to environmental parameters. Furthermore, these RFID applications often involve lots of human activities, in order to precisely understand human behavior, mobility and activity through the perceived RFID data, it is essential to ef￾fectively manage RFID data to extract the useful information, while ensuring the overall performance. How to effectively manage RFID data? As a matter of fact, several properties are essentially required for effective RFID data management. We elaborate on these properties as follows: • Efficiency: while interrogating a number of tags, two met￾rics are highly pertinent to efficiency, i.e., time efficiency to reduce the total scanning time, and energy efficiency to reduce the total power consumption. • Trustworthy: the communication between the reader and tags should be both privacy-preserving and anti￾counterfeiting. • Localizability: the objects or people should be accurately located within the specified range of time delay. • Reliability: in realistic settings, the RFID system should be able to tackle with issues like signal interference, multi-path effect and energy absorption. These properties basically belong to the nonfunctional requirements for RFID systems. According to the above descriptions, it is essential to provide some mechanisms to effectively satisfy the above nonfunctional requirements. Therefore, several new research topics are necessarily to be addressed for RFID data management. Specifically, they include anti-collision algorithms, authentication and privacy protection protocols, localization and activity sensing, as well as performance tuning in realistic settings. Fig. 1 illustrates these research topics corresponding to the above properties. In fact, these research topics are not independent of each other, but are correlated with each other. Besides, since these topics 1553-877X/14/$31.00 c 2014 IEEE