2272 IEEE TRANSACTIONS ON MOBILE COMPUTING.VOL.14.NO.11.NOVEMBER 2015 Exploring the Gap between Ideal and Reality:An Experimental Study on Continuous Scanning with Mobile Reader in RFID Systems Lei Xie,Member,IEEE,Qun Li,Member,IEEE,Chuyu Wang,Student Member,IEEE, Xi Chen,and Sanglu Lu,Member,IEEE Abstract-In this paper,we show the first comprehensive experimental study on mobile RFID reading performance based on a relatively large number of tags.By making a number of observations regarding the tag reading performance,we build a model to depict how various parameters affect the reading performance.Through our model,we have designed very efficient algorithms to maximize the time-efficiency and energy-efficiency by adjusting the reader's power and moving speed.Our experiments show that our algorithms can reduce the total scanning time by 50 percent and the total energy consumption by 83 percent compared to the prior solutions. Index Terms-RFID,model,realistic settings,continuous scanning,algorithm design,optimization 1 INTRODUCTION Me5Rpnaieyhsnas First,previous experiments were usually conducted in a small scale (fewer than 20 tags),which does not capture the Scanning books in a library or a bookstore,tracking mer- complication for a large number of tags.Second,previous chandises in a store,all require a mobile reader to be used work has been focused on reading performance in a close to for continuous scanning over the tags attached to the physi- free space scenario.In reality,path loss,multi-path effect cal goods and assets.The mobile reader moves continuously and mutual interference are common and have a big impact to scan a large number of tags effectively compensating for to RFID reading process.Third,previous work mainly its limited reading range.In those types of mobile reader examined how factors such as distance,coding scheme and systems,two performance metrics are highly pertinent: frequency,affect reading performance.Very important fac- time efficiency to reduce the total scanning time,and energy tors,i.e.,the reader's power and tag density,were efficiency to reduce the total power consumption.Unfortu-neglected.Therefore,the previous work does not give a nately,there is no realistic model to characterize the perfor- model for RFID reading process in a realistic and large scale mance for mobile RFID reading for a large scale setting.The setting;in particular,it does not include the power and tag factors that affect the mobile reading performance are very density.Indeed,before we started our work,there was no complicated.For example,the actual scanning time for a realistic model which can guide us in designing an efficient number of tags in a realistic scenario is much longer than tag identification solution in our setting. the time computed for free space,as shown in our experi- We have,thus,conducted comprehensive measurements ments.In addition,RFID readers have a wide range of over a large number of tags in realistic settings by varying power selections,e.g.,the Alien-9900 reader has a maxi-various parameters.Surprisingly,we have a few important mum power 30.7 dBm,which is 30 times larger than the new findings from the experiments.For example,we have minimum power 15.7 dBm.There is no guideline,however, found that the probabilistic backscattering is a ubiquitous in selecting a suitable power.Therefore,we aim to design phenomenon of the RFID system in realistic settings,i.e., an efficient solution to continuous scanning problem for a during every query cycle each tag randomly responds with mobile RFID reader based on experimental study. a certain probability,which has an important effect on the Although there have been some experimental studies on reading performance.This observation is contrary to the reading performance in a stationary RFID system [1],[21, previous belief that tags respond to a reader with either [3],the previous studies have the following limitations. probability 1 or 0.We have also found it is not wise to blindly increase the reader's power for tag identification, .L.Xie,C.Wang,X.Chen,and S.Lu are with the State Key Laboratory for which can degrade the overall performance including the Novel Software Technology,Nanjing UIniversity,Nanjing 210023,China. effective throughput and energy consumption.These find- E-mail:(lxie,sanglu@nju.edu.cn,(wangcyu217,hawkxcl@dislab.nju. ings are essential to improving reading performance for a ed1l.C几. Q.Li is with the Department of Computer Science,College of William and mobile RFID system.Most importantly,we can (1)model Mary,Williamsburg,Virginia 23187.E-mail:liqun@cs.wm.edu. the patterns of reading a large number of tags by giving Manuscript received 7 Jan.2014;revised 8 Nov.2014;accepted 15 Jan.2015. a probabilistic model to capture the major and minor detec- Date of publication 21 Jan.2015;date of current version 29 Sept.2015. tion region,and(2)model how the reading power and tag For information on obtaining reprints of this article,please send e-mail to: reprints@ieee.org,and reference the Digital Object Identifier below. density affect the reading performance by proving an Digital Object Identifier no.10.1109/TMC.2015.2395426 empirical mapping. mission
Exploring the Gap between Ideal and Reality: An Experimental Study on Continuous Scanning with Mobile Reader in RFID Systems Lei Xie, Member, IEEE, Qun Li, Member, IEEE, Chuyu Wang, Student Member, IEEE, Xi Chen, and Sanglu Lu, Member, IEEE Abstract—In this paper, we show the first comprehensive experimental study on mobile RFID reading performance based on a relatively large number of tags. By making a number of observations regarding the tag reading performance, we build a model to depict how various parameters affect the reading performance. Through our model, we have designed very efficient algorithms to maximize the time-efficiency and energy-efficiency by adjusting the reader’s power and moving speed. Our experiments show that our algorithms can reduce the total scanning time by 50 percent and the total energy consumption by 83 percent compared to the prior solutions. Index Terms—RFID, model, realistic settings, continuous scanning, algorithm design, optimization Ç 1 INTRODUCTION MOBILE RFID reading performance is critical to a number of applications that rely on mobile readers. Scanning books in a library or a bookstore, tracking merchandises in a store, all require a mobile reader to be used for continuous scanning over the tags attached to the physical goods and assets. The mobile reader moves continuously to scan a large number of tags effectively compensating for its limited reading range. In those types of mobile reader systems, two performance metrics are highly pertinent: time efficiency to reduce the total scanning time, and energy efficiency to reduce the total power consumption. Unfortunately, there is no realistic model to characterize the performance for mobile RFID reading for a large scale setting. The factors that affect the mobile reading performance are very complicated. For example, the actual scanning time for a number of tags in a realistic scenario is much longer than the time computed for free space, as shown in our experiments. In addition, RFID readers have a wide range of power selections, e.g., the Alien-9900 reader has a maximum power 30.7 dBm, which is 30 times larger than the minimum power 15.7 dBm. There is no guideline, however, in selecting a suitable power. Therefore, we aim to design an efficient solution to continuous scanning problem for a mobile RFID reader based on experimental study. Although there have been some experimental studies on reading performance in a stationary RFID system [1], [2], [3], the previous studies have the following limitations. First, previous experiments were usually conducted in a small scale (fewer than 20 tags), which does not capture the complication for a large number of tags. Second, previous work has been focused on reading performance in a close to free space scenario. In reality, path loss, multi-path effect and mutual interference are common and have a big impact to RFID reading process. Third, previous work mainly examined how factors such as distance, coding scheme and frequency, affect reading performance. Very important factors, i.e., the reader’s power and tag density, were neglected. Therefore, the previous work does not give a model for RFID reading process in a realistic and large scale setting; in particular, it does not include the power and tag density. Indeed, before we started our work, there was no realistic model which can guide us in designing an efficient tag identification solution in our setting. We have, thus, conducted comprehensive measurements over a large number of tags in realistic settings by varying various parameters. Surprisingly, we have a few important new findings from the experiments. For example, we have found that the probabilistic backscattering is a ubiquitous phenomenon of the RFID system in realistic settings, i.e., during every query cycle each tag randomly responds with a certain probability, which has an important effect on the reading performance. This observation is contrary to the previous belief that tags respond to a reader with either probability 1 or 0. We have also found it is not wise to blindly increase the reader’s power for tag identification, which can degrade the overall performance including the effective throughput and energy consumption. These findings are essential to improving reading performance for a mobile RFID system. Most importantly, we can (1) model the patterns of reading a large number of tags by giving a probabilistic model to capture the major and minor detection region, and (2) model how the reading power and tag density affect the reading performance by proving an empirical mapping. L. Xie, C. Wang, X. Chen, and S. Lu are with the State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China. E-mail: {lxie, sanglu}@nju.edu.cn, {wangcyu217, hawkxc}@dislab.nju. edu.cn. Q. Li is with the Department of Computer Science, College of William and Mary, Williamsburg, Virginia 23187. E-mail: liqun@cs.wm.edu. Manuscript received 7 Jan. 2014; revised 8 Nov. 2014; accepted 15 Jan. 2015. Date of publication 21 Jan. 2015; date of current version 29 Sept. 2015. For information on obtaining reprints of this article, please send e-mail to: reprints@ieee.org, and reference the Digital Object Identifier below. Digital Object Identifier no. 10.1109/TMC.2015.2395426 2272 IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 14, NO. 11, NOVEMBER 2015 1536-1233 2015 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information
XIE ET AL.:EXPLORING THE GAP BETWEEN IDEAL AND REALITY:AN EXPERIMENTAL STUDY ON CONTINUOUS SCANNING WITH... 2273 Based on the effective models,we consider to tackle the information gathered in the previous scanning operations following problem in a typical scenario of RFID applica- to reduce the scanning time of the succeeding ones. tions,i.e.,using a mobile reader to identify a large volume In order to verify the impact of the physical layer's unre- of tags deployed over a wide area.We seek to execute con- liability,a number of researchers conduct experimental tinuous scanning over the tags along a certain direction, studies in realistic settings,while trying to explore the gap while respectively considering a situation where the tags are between the ideal situation and the realistic situation for continuously placed with a uniform/nonuniform density. RFID systems.Buettner and Wetherall [1]examine the per- We focus on several critical metrics like time-efficiency, formance of the C1G2 RFID system in a realistic setting. energy-efficiency and coverage ratio.We design efficient They identify factors that degrade overall performance and and practical algorithms for continuous scanning,by skill- reliability with a focus on the physical layer.Jeffery et al.[3] fully adjusting the reader's power and moving speed,which conduct experiments in realistic settings and find that can dramatically improve the performance,as shown in our within each reader's detection range,a large difference real experiments.By exploring the inherent regularities in exists in reading performance.Zheng and Li investigate continuous scanning,we aim to give some fundamental into the physical layer information of tag responses for guidance for future RFID system design towards more com- missing tag identification [281.Realizing that the reader's plicated realistic settings.We make the following contribu- transmission power actually has a significant impact on the tions in this paper (a preliminary version of this work reading performance of the RFID system,Xu et al.investi- appeared in [41).1)We are the first to conduct an extensive gate the impact of transmission power on reading perfor- experimental study and performance evaluation over a rela- mance through extensive empirical study on passive tags tively large number of tags (up to 160 tags for experimental [29],[30].Su et al.find that,when the transmission power is study and up to 480 tags for performance evaluation)and a set to a reasonable range,the "capture effect"can be used to rather high tag density (up to 90 tags per square meter)in resolve the collision slots into singleton slots [31].Therefore, realistic settings.To the best of our knowledge,this is the they propose a progressing scanning algorithm to improve first work to propose a model for investigating how the the reading throughput. important parameters including reader's power,moving speed and tag density jointly affect the reading performance. 2)This is also the first work to give a framework of optimiz- 3 PROBLEM FORMULATION ing reading performance based on experimental study.We We consider a typical scenario of continuous scanning in apply our model to solve the problem of continuous scan- realistic settings,i.e.,using a mobile reader to identify a ning with mobile reader.By carefully adjusting the power large volume of tags deployed over a wide area.We respec- and moving speed,we design efficient algorithms to opti- tively consider a situation where the tags are continuously mize time-efficiency and energy-efficiency.We have a num- placed with a uniform/nonuniform density,we seek to exe- ber of novel techniques in making our algorithms practical. cute continuous scanning over the tags along a certain direc- 3)Being compatible with RFID standard(with no changes to tion.The performance metrics in our consideration are as the C1G2 protocols or low-level parameters for commercial follows:1)Time-efficiency:considering it is time-consuming RFID readers),our solutions can deliver significant perfor- to identify a large volume of tags in realistic settings,the mance gain.Experiment results indicate that,while achiev- overall scanning time should be as small as possible.2) ing the same coverage ratio,our practical solutions Energy-efficiency:considering the mobile reader is conven- respectively reduce scanning time by 50 percent and energy tionally battery powered,e.g.,a typical battery for the consumption by 83 percent compared to the prior solutions. mobile reader has a capacity of 3,200 mAh with output volt- age 3.7 v,if we scan the tags with a maximum radiation 2 RELATED WORK power 36 dBm,the mobile reader can execute continuous scanning for only 3 hours,therefore,the overall energy In RFID systems,a reader needs to receive data from multi- used should be as small as possible.3)Coverage ratio:due to ple tags.These tags are unable to self-regulate their radio various issues like path loss in realistic settings,it is difficult transmissions to avoid collisions.In light of this,a series of to identify all tags with a high probability for one single slotted ALOHA-based anti-collision protocols [5],[6],[7],as scanning cycle,therefore,the coverage ratio,i.e.,the ratio of well as tree-based anti-collision protocols [8],[9],[10],[111, the number of identified tags to the total number of tags, are designed to resolve collisions in RFID systems.In order should be guaranteed,while each tag should have a uni- to deal with the collision problems in multi-reader RFID form probability to be identified. systems,scheduling protocols for reader activation are In regard to the continuous scanning,we define the scan- explored in [12],[13].Recently,a number of polling-based ning time as T,the overall energy used as E,and the cover- protocols [141,[15],[161,[17]are proposed,aiming to collect age ratio as C.Assuming the tag density is p and the length information from RFID tags in a time/energy efficient of the scanning area is l,then the total tag size is n =l.p, approach.In order to estimate the number of tags without we denote the overall tag set as S.We assume that each tag collecting tag IDs,a number of protocols are proposed [181,tiEs is successfully identified with probability of pi after [191,[20l,[21),[22l,[23,[24,[25l,[26]to leverage the infor- the continuous scanning.The reader's antenna is deployed mation gathered in slotted ALOHA protocol for fast estima- towards the tags with a distance of d.We can adjust the tion of tag size.In regard to tag identification with the parameters including the reader's power p and the moving mobile reader,Sheng et al.develop efficient schemes for speed u to improve the reading performance.Therefore, continuous scanning operations [271,aiming to utilize the during the continuous scanning,the problem is how to
Based on the effective models, we consider to tackle the following problem in a typical scenario of RFID applications, i.e., using a mobile reader to identify a large volume of tags deployed over a wide area. We seek to execute continuous scanning over the tags along a certain direction, while respectively considering a situation where the tags are continuously placed with a uniform/nonuniform density. We focus on several critical metrics like time-efficiency, energy-efficiency and coverage ratio. We design efficient and practical algorithms for continuous scanning, by skillfully adjusting the reader’s power and moving speed, which can dramatically improve the performance, as shown in our real experiments. By exploring the inherent regularities in continuous scanning, we aim to give some fundamental guidance for future RFID system design towards more complicated realistic settings. We make the following contributions in this paper (a preliminary version of this work appeared in [4]). 1) We are the first to conduct an extensive experimental study and performance evaluation over a relatively large number of tags (up to 160 tags for experimental study and up to 480 tags for performance evaluation) and a rather high tag density (up to 90 tags per square meter) in realistic settings. To the best of our knowledge, this is the first work to propose a model for investigating how the important parameters including reader’s power, moving speed and tag density jointly affect the reading performance. 2) This is also the first work to give a framework of optimizing reading performance based on experimental study. We apply our model to solve the problem of continuous scanning with mobile reader. By carefully adjusting the power and moving speed, we design efficient algorithms to optimize time-efficiency and energy-efficiency. We have a number of novel techniques in making our algorithms practical. 3) Being compatible with RFID standard (with no changes to the C1G2 protocols or low-level parameters for commercial RFID readers), our solutions can deliver significant performance gain. Experiment results indicate that, while achieving the same coverage ratio, our practical solutions respectively reduce scanning time by 50 percent and energy consumption by 83 percent compared to the prior solutions. 2 RELATED WORK In RFID systems, a reader needs to receive data from multiple tags. These tags are unable to self-regulate their radio transmissions to avoid collisions. In light of this, a series of slotted ALOHA-based anti-collision protocols [5], [6], [7], as well as tree-based anti-collision protocols [8], [9], [10], [11], are designed to resolve collisions in RFID systems. In order to deal with the collision problems in multi-reader RFID systems, scheduling protocols for reader activation are explored in [12], [13]. Recently, a number of polling-based protocols [14], [15], [16], [17] are proposed, aiming to collect information from RFID tags in a time/energy efficient approach. In order to estimate the number of tags without collecting tag IDs, a number of protocols are proposed [18], [19], [20], [21], [22], [23], [24], [25], [26] to leverage the information gathered in slotted ALOHA protocol for fast estimation of tag size. In regard to tag identification with the mobile reader, Sheng et al. develop efficient schemes for continuous scanning operations [27], aiming to utilize the information gathered in the previous scanning operations to reduce the scanning time of the succeeding ones. In order to verify the impact of the physical layer’s unreliability, a number of researchers conduct experimental studies in realistic settings, while trying to explore the gap between the ideal situation and the realistic situation for RFID systems. Buettner and Wetherall [1] examine the performance of the C1G2 RFID system in a realistic setting. They identify factors that degrade overall performance and reliability with a focus on the physical layer. Jeffery et al. [3] conduct experiments in realistic settings and find that within each reader’s detection range, a large difference exists in reading performance. Zheng and Li investigate into the physical layer information of tag responses for missing tag identification [28]. Realizing that the reader’s transmission power actually has a significant impact on the reading performance of the RFID system, Xu et al. investigate the impact of transmission power on reading performance through extensive empirical study on passive tags [29], [30]. Su et al. find that, when the transmission power is set to a reasonable range, the “capture effect” can be used to resolve the collision slots into singleton slots [31]. Therefore, they propose a progressing scanning algorithm to improve the reading throughput. 3 PROBLEM FORMULATION We consider a typical scenario of continuous scanning in realistic settings, i.e., using a mobile reader to identify a large volume of tags deployed over a wide area. We respectively consider a situation where the tags are continuously placed with a uniform/nonuniform density, we seek to execute continuous scanning over the tags along a certain direction. The performance metrics in our consideration are as follows: 1) Time-efficiency: considering it is time-consuming to identify a large volume of tags in realistic settings, the overall scanning time should be as small as possible. 2) Energy-efficiency: considering the mobile reader is conventionally battery powered, e.g., a typical battery for the mobile reader has a capacity of 3,200 mAh with output voltage 3.7 v, if we scan the tags with a maximum radiation power 36 dBm, the mobile reader can execute continuous scanning for only 3 hours, therefore, the overall energy used should be as small as possible. 3) Coverage ratio: due to various issues like path loss in realistic settings, it is difficult to identify all tags with a high probability for one single scanning cycle, therefore, the coverage ratio, i.e., the ratio of the number of identified tags to the total number of tags, should be guaranteed, while each tag should have a uniform probability to be identified. In regard to the continuous scanning, we define the scanning time as T, the overall energy used as E, and the coverage ratio as C. Assuming the tag density is r and the length of the scanning area is l, then the total tag size is n ¼ l r, we denote the overall tag set as S. We assume that each tag tj 2 S is successfully identified with probability of pj after the continuous scanning. The reader’s antenna is deployed towards the tags with a distance of d. We can adjust the parameters including the reader’s power pw and the moving speed v to improve the reading performance. Therefore, during the continuous scanning, the problem is how to XIE ET AL.: EXPLORING THE GAP BETWEEN IDEAL AND REALITY: AN EXPERIMENTAL STUDY ON CONTINUOUS SCANNING WITH... 2273
2274 IEEE TRANSACTIONS ON MOBILE COMPUTING.VOL.14.NO.11.NOVEMBER 2015 efficiently set the parameters p and v such that the follow- 80 ing objectives can be achieved: 70 Time-efficiency: 60 minimize T (1) 50 subject to (2) 40 E≤a energy constraint 30 PC≥d≥B coverage constraint (3) 29 t;∈Spj=p coverage constraint (4) .5 1.5 2.5 Distance(m) Fig.1.The number of tags read for various distances. Energy-efficiency: bookshelf is composed of 16 grids with four columns and minimize E four rows,the height and width of each grid are respec- subject to tively 60 cm and 75 cm.In the experiments we only consider (6) T≤Y the grids in the three rows of upper layers,since the grids in time constraint the bottom layer may be greatly affected by the multi-path PrC20≥B coverage constraint (7) effect.Therefore,we choose to deploy the tags in the 12 grids with four columns and three rows.The RFID reader is stati- t∈Sp防=p coverage constraint (8) cally deployed by facing its antenna towards the book shelf. Note that in order to set an appropriate value for the dis- tance between the reader and the bookshelf,it is difficult to According to the above formulation,in regard to the time-efficiency,the objective is to minimize the overall directly derive the optimal distance from geometry accord- scanning time T while the energy constraint and the cover- ing to the beamwidth,due to issues like the multi-path age constraint should be satisfied.The energy constraint effect.Therefore,we vary the distance from 0.5 to 3 m and requires the energy used should be no greater than a certain measure the number of effectively identified tags while threshold a.In regard to the coverage constraint,due to the scanning 160 tags uniformly distributed on the shelf. random factors in the anti-collision scheme and the com- As shown in Fig.1,we find that the reader achieves the munication environment,the coverage ratio C cannot guar- maximum coverage when the distance is 1.5 m.Thus,we antee to be deterministically equal or greater than a set the distance to 1.5 m to guarantee the reading perfor- threshold 0,hence we use the probabilistic approach to mance.This setting is close to a typical noisy condition, denote the requirement.The probability for the coverage which is distinct from the free space condition,since the ratio C to be equal or greater than 6 should be no less than issues in the realistic applications like the path loss,multi- B.Moreover,there could exist multiple feasible solutions to path effect and energy absorption all exist.Considering that guarantee the coverage constraint,in some of the solutions we deploy a relatively large number of tags (up to 160 tags the tags are detected with nonuniform probabilities.In fair- in experimental study and 480 tags in performance evalua- ness,we require that each tag ti in the set S should be tion)and a rather high tag density (up to 90 tags per square detected with a uniform probability p,i.e.,the detection meter)in realistic settings,the experimental findings from probability pi should be equal to p.Similarly,in regard to the high tag density deployment can be highly scalable and the energy-efficiency,the objective is to minimize the over- generalized to rather large scale settings.Specifically,we attach each tag to a book and put these books back-to-back all energy E,while the time constraint and the coverage constraint should be satisfied.The time constraint requires in a very dense approach.We believe this tag density (up to that the scanning time should be no greater than a certain 90 tags per m2)should be close to extreme case in scale for threshold,y. conventional RFID applications.Since we use the mobile RFID reader to scan the tags within its limited scanning range,hence,after the whole process of continuous scan- 4 DERIVING A MODEL FROM REALISTIC ning,all tags can be effectively identified.Therefore,as long EXPERIMENTS as we can tackle the problem in this situation,it can be In order to understand how the reader's power and tag den- guaranteed that our solution is scalable to any large scale sity affect the reading performance,while dealing with during the continuous scanning. issues like the path loss,energy absorption,and mutual On the whole,it took us over 300 hours to conduct an interference,we illustrate several original findings from our extensive experimental study of up to 160 tags in realistic realistic experiments.In our experiments,we use the Alien- settings.In order to sufficiently understand how the param- 9900 reader and Alien-9611 linear antenna with a directional eters separately/jointly affect the actual reading perfor- gain of 6 dB.The 3 dB beamwidth is 40 degrees.The RFID mance,we conduct up to 100 various experiments,carrying tags used are Alien 9640 general-purpose tags which sup- out lots of experimental comparisons and analysis on port the EPC C1G2 standards.We attach the RFID tags onto the obtained results.In the following experiments,we the books which are placed in a large bookshelf.Each tag is vary the tag density,p,from 10 to 40 tags/grid,while attached onto a distinct book with a unique ID.The adjusting the reader's power from 20.7 dBm to 30.7 dBm for
efficiently set the parameters pw and v such that the following objectives can be achieved: Time-efficiency: minimize T (1) subject to E a energy constraint (2) Pr½C u b coverage constraint (3) 8tj 2 S pj ¼ p coverage constraint (4) Energy-efficiency: minimize E (5) subject to T g time constraint (6) Pr½C u b coverage constraint (7) 8tj 2 S pj ¼ p coverage constraint: (8) According to the above formulation, in regard to the time-efficiency, the objective is to minimize the overall scanning time T while the energy constraint and the coverage constraint should be satisfied. The energy constraint requires the energy used should be no greater than a certain threshold a. In regard to the coverage constraint, due to the random factors in the anti-collision scheme and the communication environment, the coverage ratio C cannot guarantee to be deterministically equal or greater than a threshold u, hence we use the probabilistic approach to denote the requirement. The probability for the coverage ratio C to be equal or greater than u should be no less than b. Moreover, there could exist multiple feasible solutions to guarantee the coverage constraint, in some of the solutions the tags are detected with nonuniform probabilities. In fairness, we require that each tag tj in the set S should be detected with a uniform probability p, i.e., the detection probability pj should be equal to p. Similarly, in regard to the energy-efficiency, the objective is to minimize the overall energy E, while the time constraint and the coverage constraint should be satisfied. The time constraint requires that the scanning time should be no greater than a certain threshold, g. 4 DERIVING A MODEL FROM REALISTIC EXPERIMENTS In order to understand how the reader’s power and tag density affect the reading performance, while dealing with issues like the path loss, energy absorption, and mutual interference, we illustrate several original findings from our realistic experiments. In our experiments, we use the Alien- 9900 reader and Alien-9611 linear antenna with a directional gain of 6 dB. The 3 dB beamwidth is 40 degrees. The RFID tags used are Alien 9640 general-purpose tags which support the EPC C1G2 standards. We attach the RFID tags onto the books which are placed in a large bookshelf. Each tag is attached onto a distinct book with a unique ID. The bookshelf is composed of 16 grids with four columns and four rows, the height and width of each grid are respectively 60 cm and 75 cm. In the experiments we only consider the grids in the three rows of upper layers, since the grids in the bottom layer may be greatly affected by the multi-path effect. Therefore, we choose to deploy the tags in the 12 grids with four columns and three rows. The RFID reader is statically deployed by facing its antenna towards the book shelf. Note that in order to set an appropriate value for the distance between the reader and the bookshelf, it is difficult to directly derive the optimal distance from geometry according to the beamwidth, due to issues like the multi-path effect. Therefore, we vary the distance from 0.5 to 3 m and measure the number of effectively identified tags while scanning 160 tags uniformly distributed on the shelf. As shown in Fig. 1, we find that the reader achieves the maximum coverage when the distance is 1.5 m. Thus, we set the distance to 1.5 m to guarantee the reading performance. This setting is close to a typical noisy condition, which is distinct from the free space condition, since the issues in the realistic applications like the path loss, multipath effect and energy absorption all exist. Considering that we deploy a relatively large number of tags (up to 160 tags in experimental study and 480 tags in performance evaluation) and a rather high tag density (up to 90 tags per square meter) in realistic settings, the experimental findings from the high tag density deployment can be highly scalable and generalized to rather large scale settings. Specifically, we attach each tag to a book and put these books back-to-back in a very dense approach. We believe this tag density (up to 90 tags per m2) should be close to extreme case in scale for conventional RFID applications. Since we use the mobile RFID reader to scan the tags within its limited scanning range, hence, after the whole process of continuous scanning, all tags can be effectively identified. Therefore, as long as we can tackle the problem in this situation, it can be guaranteed that our solution is scalable to any large scale during the continuous scanning. On the whole, it took us over 300 hours to conduct an extensive experimental study of up to 160 tags in realistic settings. In order to sufficiently understand how the parameters separately/jointly affect the actual reading performance, we conduct up to 100 various experiments, carrying out lots of experimental comparisons and analysis on the obtained results. In the following experiments, we vary the tag density, r, from 10 to 40 tags/grid, while adjusting the reader’s power from 20.7 dBm to 30.7 dBm for 0.5 1 1.5 2 2.5 3 20 30 40 50 60 70 80 Distance(m) Effective tag size Fig. 1. The number of tags read for various distances. 2274 IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 14, NO. 11, NOVEMBER 2015
XIE ET AL.:EXPLORING THE GAP BETWEEN IDEAL AND REALITY:AN EXPERIMENTAL STUDY ON CONTINUOUS SCANNING WITH... 2275 22.7dBm =24.7dB -30.7 02* 0.4 0.6 0.8 Gnd ID 140 10 10 (a)Histogram of read ratio (b)Probability density functions gB (a)Histogram of read ratio for various moving speeds Fig.2.Probabilistic backscattering in static situation. performance evaluation.Unless otherwise specified,by default we fix the reader towards the center of the book- shelf,set the reader's power to 30.7 dBm,and repetitively scan the tags for 50 query cycles. 4.1 Experimental Findings 4.1.1 Probabilistic Backscattering (b)Proportion of identified (c)Average read ratio for each tag During the query cycles,each tag responds to the reader with a number of tags certain probability between 0 and 1.We uniformly deploy 96 Fig.3.Probabilistic backscattering in mobile situation. tags in the bookshelf with eight tags in each grid.The grids on the left/middle/right side are respectively numbered current round.In regard to the change of multi-path condi- (1,23)/(4,5,6,7,8,9)/(10,11,12.First,we use a static RFID tions,since we use the mobile RFID reader to continuously reader to scan these tags for 100 times. interrogate the surrounding RFID tags while the reader is In Fig.2a,we respectively compute the read ratios of moving,the reader's antenna continuously changes its posi- each tag in the 12 grids,i.e.,the ratio of successful number tion,the incident angle and distance of the signal wave of responses to the expected number of responses for each from the reader to the tag is continuously changing,which tag,and illustrate them in histogram grouped by grid ID. causes the multi-path conditions change a lot during the We note that the tags respond to the reader with various continuous scanning.Therefore,the change of multi-path probabilities between 0 and 1,although basically no param- conditions is essentially caused by the movement of the eters are changed during the repetitive scanning.This reader. observation is contrary to the popular idea that each tag Fig.3a shows the histogram of read ratio for various either responds thoroughly or does not respond at all.We moving speeds.We observe that most of the tags which can- think this is probably due to the randomness in the back- not be identified in static cases can be effectively identified scattering factors,like the power scattering,multi-path in the mobile cases.Each tag tends to have close response propagation.Furthermore,we vary the reader's power,p, probability in mobile scanning.Fig.3b further shows the from 22.7 to 30.7 dBm and obtain the probability density proportion of identified tags for various moving speeds,i.e., functions for the read ratio.According to Fig.2b,we note the ratio of the number of identified tags to the overall num- that as the reader's power varies,the distribution of the ber of tags.We find that the mobile scanning approach can read ratio also varies.The above observation further implies greatly increase the overall ratio of identification in compar- that,due to the probabilistic backscattering,multiple query ison to the static approach.Fig.3c further shows the read cycles are essential to successfully identify a typical tag in ratio for each tag for various moving speeds.We find that the tag set,which may cause massive duplicated readings while mobile scanning can effectively increase the read ratio over other tags in the scanning area. than the static approach,the one with lower moving speed According to the experiments in static situations,we can achieve more efficiency in read ratio than the one with observe that,although the tags respond to the reader with larger moving speed. various probabilities,a majority of the tags still respond with probability either close to 100 percent or 0.Due to the ambient multi-path effect in indoor environment,we find 4.1.2 Major Detection Region versus Minor Detection that even in very close positions from the reader,some tags Region can be easily identified and some tags cannot be identified Within each reader's detection range,there are two distinct at all.Moreover,we further conduct continuous scanning in regions:the major detection region where the tags can be identified mobile environment,by varying the moving speed of the with high probability,and the minor detection region where the mobile reader from 0 to 100 cm/s.We set the reader's power tags can be identified with low probability.We uniformly to 25.7 dBm and make it continuously interrogate the sur-deploy the tags in a row with four grids in the bookshelf, rounding tags while moving.We continuously scan tags in where the tag IDs are sequentially numbered from left to four grids,and the tag density is 40 tags/grid.During the right.The reader's power is set to 30.7 dBm.Figs.4a,4b,4c, continuous scanning,as the multi-path effect is continu-and 4d show the histogram of each tag's read ratio in the ously changing,we find that some tags which cannot be order of tag ID,while varying the tag density,ie.,the num- identified in the previous round can be easily identified in ber of tags per grid
performance evaluation. Unless otherwise specified, by default we fix the reader towards the center of the bookshelf, set the reader’s power to 30:7 dBm, and repetitively scan the tags for 50 query cycles. 4.1 Experimental Findings 4.1.1 Probabilistic Backscattering During the query cycles, each tag responds to the reader with a certain probability between 0 and 1. We uniformly deploy 96 tags in the bookshelf with eight tags in each grid. The grids on the left/middle/right side are respectively numbered (1,2,3)/(4,5,6,7,8,9)/(10,11,12). First, we use a static RFID reader to scan these tags for 100 times. In Fig. 2a, we respectively compute the read ratios of each tag in the 12 grids, i.e., the ratio of successful number of responses to the expected number of responses for each tag, and illustrate them in histogram grouped by grid ID. We note that the tags respond to the reader with various probabilities between 0 and 1, although basically no parameters are changed during the repetitive scanning. This observation is contrary to the popular idea that each tag either responds thoroughly or does not respond at all. We think this is probably due to the randomness in the backscattering factors, like the power scattering, multi-path propagation. Furthermore, we vary the reader’s power, pw, from 22.7 to 30.7 dBm and obtain the probability density functions for the read ratio. According to Fig. 2b, we note that as the reader’s power varies, the distribution of the read ratio also varies. The above observation further implies that, due to the probabilistic backscattering, multiple query cycles are essential to successfully identify a typical tag in the tag set, which may cause massive duplicated readings over other tags in the scanning area. According to the experiments in static situations, we observe that, although the tags respond to the reader with various probabilities, a majority of the tags still respond with probability either close to 100 percent or 0. Due to the ambient multi-path effect in indoor environment, we find that even in very close positions from the reader, some tags can be easily identified and some tags cannot be identified at all. Moreover, we further conduct continuous scanning in mobile environment, by varying the moving speed of the mobile reader from 0 to 100 cm/s. We set the reader’s power to 25.7 dBm and make it continuously interrogate the surrounding tags while moving. We continuously scan tags in four grids, and the tag density is 40 tags/grid. During the continuous scanning, as the multi-path effect is continuously changing, we find that some tags which cannot be identified in the previous round can be easily identified in current round. In regard to the change of multi-path conditions, since we use the mobile RFID reader to continuously interrogate the surrounding RFID tags while the reader is moving, the reader’s antenna continuously changes its position, the incident angle and distance of the signal wave from the reader to the tag is continuously changing, which causes the multi-path conditions change a lot during the continuous scanning. Therefore, the change of multi-path conditions is essentially caused by the movement of the reader. Fig. 3a shows the histogram of read ratio for various moving speeds. We observe that most of the tags which cannot be identified in static cases can be effectively identified in the mobile cases. Each tag tends to have close response probability in mobile scanning. Fig. 3b further shows the proportion of identified tags for various moving speeds, i.e., the ratio of the number of identified tags to the overall number of tags. We find that the mobile scanning approach can greatly increase the overall ratio of identification in comparison to the static approach. Fig. 3c further shows the read ratio for each tag for various moving speeds. We find that, while mobile scanning can effectively increase the read ratio than the static approach, the one with lower moving speed can achieve more efficiency in read ratio than the one with larger moving speed. 4.1.2 Major Detection Region versus Minor Detection Region Within each reader’s detection range, there are two distinct regions: the major detection region where the tags can be identified with high probability, and the minor detection region where the tags can be identified with low probability. We uniformly deploy the tags in a row with four grids in the bookshelf, where the tag IDs are sequentially numbered from left to right. The reader’s power is set to 30.7 dBm. Figs. 4a, 4b, 4c, and 4d show the histogram of each tag’s read ratio in the order of tag ID, while varying the tag density, i.e., the number of tags per grid. Fig. 2. Probabilistic backscattering in static situation. Fig. 3. Probabilistic backscattering in mobile situation. XIE ET AL.: EXPLORING THE GAP BETWEEN IDEAL AND REALITY: AN EXPERIMENTAL STUDY ON CONTINUOUS SCANNING WITH... 2275
2276 IEEE TRANSACTIONS ON MOBILE COMPUTING.VOL.14.NO.11.NOVEMBER 2015 10 30 22 60 Missing tag ID 100 (a)Histogram of read ratiolp (b)Histogram of read ratio (p= (a)The randomness of missing (b)The number of tags identified 10) 20) tag ID with various deployment Fig.5.Power density over the tags. radiation area.As the power increases,we note that the identified tag size in uniform distribution is always larger than the centered distribution.This is because the power density in the former case is much larger than the latter 20 40 Tag ID 0 100 120 100 150 case,more tags in the former case respond to the reader. (c)Histogram of read ratio (p (d)Histogram of read ratio (p Therefore,in order to statistically depict the probabilistic 30) 40) backscattering property in the major detection region,the Fig.4.Major detection region versus minor detection region. average detection probability is essential to be used. In order to see the two distinct regions,we use red window 4.1.4 Marginal Decreasing Effect to depict the boundary of the major detection region.We observe that within each reader's detection range,the major As the reader's power is increasing,the exact read efficiency includ- detection region is the area directly in front of the reader,giv- ing the scanning range,the detection probability,as well as the ing high detection probability,and the minor detection region number of identified tags,is not increasing equally with the power. extends from the end of the major detection region to the edge In Figs.6a-6c,we respectively measure the width of major detection region,the average detection probability (i.e.,read of the detection range,where the read ratio drops off to zero at the end of the detection range.As the tag density increases, ratio)in major detection region,as well as the overall number the major detection region gradually shrinks. of identified tags,while varying the reader's power from 20.7 to 30.7 dBm.All three variables are increasing while the reader's power increases.However,as the power is 4.1.3 Power Density Over the Tags increased by 2 dB (i.e,1.58 times in watt),they mainly The power density,i.e.,the radiative energy diffused to per tag, increase with a much smaller speed on average.This obser- has a big effect on the reading performance.According to vation implies that the read efficiency cannot be sufficiently Figs.4a,4b,4c,and 4d,we find that even within the major enhanced by purely increasing the reader's power. detection region,there are a certain number of tags which still remain unidentified.While in the minor detection 4.1.5 region,there are several tags which have high read ratios. Query Cycle Duration versus the Number of This observation is related to the power density over the Identified Tags Per Cycle tags:according to Figs.4a and 4b,while the tag density is As the reader's power increases,the query cycle duration does not low,the power density is fairly large,nearly all tags in the increase linearly with the number of identified tags per cycle, major detection region have high probability to respond; according to Figs.4c and 4d,while the tag density increases 10 to a large value,the diffused power is diluted among the tags,and the power density is thus reduced,causing some of the tags in the major detection region fail to respond. Besides,we observe that the missing tags in the major detec- tion region is fairly random.According to the deployment in Fig.4d,we randomly issue five query cycles and collect 30 22 Rerpen3p,(e the missing tag IDs,by slightly adjusting the antenna's posi- (a)Width of major detection re- (b)The average detection proba- tion for each query cycle.Fig.5a illustrates the missing tag gion bility in major detection region IDs in the major detection region,where the points denote the missing tags.We note that most of the missing tag's IDs are fairly random,except a small number of tags which are always missing due to the inappropriate deployment.In order to further verify the effect of the power density,we deploy 30 tags in two distinct distributions (uniform and centered)and measure the effective identified tag size in Fig.5b.In the uniform distribution,we uniformly deploy (c)Overall number of identified the tags within two adjacent grids;while in the centered dis- tags after 50 query cycles tribution,we deploy all tags in the center of the antenna's Fig.6.Marginal decreasing effect
In order to see the two distinct regions, we use red window to depict the boundary of the major detection region. We observe that within each reader’s detection range, the major detection region is the area directly in front of the reader, giving high detection probability, and the minor detection region extends from the end of the major detection region to the edge of the detection range, where the read ratio drops off to zero at the end of the detection range. As the tag density increases, the major detection region gradually shrinks. 4.1.3 Power Density Over the Tags The power density, i.e., the radiative energy diffused to per tag, has a big effect on the reading performance. According to Figs. 4a, 4b, 4c, and 4d, we find that even within the major detection region, there are a certain number of tags which still remain unidentified. While in the minor detection region, there are several tags which have high read ratios. This observation is related to the power density over the tags: according to Figs. 4a and 4b, while the tag density is low, the power density is fairly large, nearly all tags in the major detection region have high probability to respond; according to Figs. 4c and 4d, while the tag density increases to a large value, the diffused power is diluted among the tags, and the power density is thus reduced, causing some of the tags in the major detection region fail to respond. Besides, we observe that the missing tags in the major detection region is fairly random. According to the deployment in Fig. 4d, we randomly issue five query cycles and collect the missing tag IDs, by slightly adjusting the antenna’s position for each query cycle. Fig. 5a illustrates the missing tag IDs in the major detection region, where the points denote the missing tags. We note that most of the missing tag’s IDs are fairly random, except a small number of tags which are always missing due to the inappropriate deployment. In order to further verify the effect of the power density, we deploy 30 tags in two distinct distributions (uniform and centered) and measure the effective identified tag size in Fig. 5b. In the uniform distribution, we uniformly deploy the tags within two adjacent grids; while in the centered distribution, we deploy all tags in the center of the antenna’s radiation area. As the power increases, we note that the identified tag size in uniform distribution is always larger than the centered distribution. This is because the power density in the former case is much larger than the latter case, more tags in the former case respond to the reader. Therefore, in order to statistically depict the probabilistic backscattering property in the major detection region, the average detection probability is essential to be used. 4.1.4 Marginal Decreasing Effect As the reader’s power is increasing, the exact read efficiency including the scanning range, the detection probability, as well as the number of identified tags, is not increasing equally with the power. In Figs. 6a–6c, we respectively measure the width of major detection region, the average detection probability (i.e., read ratio) in major detection region, as well as the overall number of identified tags, while varying the reader’s power from 20.7 to 30.7 dBm. All three variables are increasing while the reader’s power increases. However, as the power is increased by 2 dB (i.e, 1.58 times in watt), they mainly increase with a much smaller speed on average. This observation implies that the read efficiency cannot be sufficiently enhanced by purely increasing the reader’s power. 4.1.5 Query Cycle Duration versus the Number of Identified Tags Per Cycle As the reader’s power increases, the query cycle duration does not increase linearly with the number of identified tags per cycle, Fig. 4. Major detection region versus minor detection region. Fig. 5. Power density over the tags. Fig. 6. Marginal decreasing effect. 2276 IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 14, NO. 11, NOVEMBER 2015