CN106503603B - A kind of more reader RFID system fast tag recognition methods divided based on time slot - Google Patents
A kind of more reader RFID system fast tag recognition methods divided based on time slot Download PDFInfo
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Abstract
本发明公开了一种基于时隙划分的多阅读器RFID系统快速标签识别方法，包括以下步骤：在第一阶段，帧开始时，阅读器组同时给标签广播一个查询命令，然后等待接收标签回复，成功接收到某个阅读器询问的标签根据查询命令中包含的参数，使用哈希函数选择答复时隙，然后该标签在其选择的时隙将自带的RN传回给阅读器，在时隙中，如果阅读器成功接收RN，该阅读器记录这个RN，其他没收到RN的阅读器或者检测到信号冲突的阅读器统一等待一段时间，然后阅读器组同步发送一个QueryRep命令开始一个新的时隙；第二个阶段，在每个时隙中，阅读器组中所有阅读器发送包含先前各自接收到的RN的ACK，具有相同的RN的标签给阅读器发送该标签的ID。本发明可以完全地消除RT冲突。
The invention discloses a fast label identification method for a multi-reader RFID system based on time slot division. , the tag that successfully receives a query from a certain reader uses the hash function to select the reply time slot according to the parameters contained in the query command, and then the tag transmits its own RN back to the reader in the time slot it selects. In the slot, if the reader successfully receives the RN, the reader records the RN. Other readers that have not received the RN or readers that detect signal conflict wait for a period of time, and then the reader group sends a QueryRep command synchronously to start a new one. Time slot; in the second stage, in each time slot, all readers in the reader group send ACKs containing the RNs they received previously, and the tags with the same RN send the IDs of the tags to the readers. The present invention can completely eliminate RT conflicts.
Description
Technical field
The present invention relates to a kind of more reader RFID system fast tag recognition methods divided based on time slot.
Background technique
Nowadays radio frequency identification (RFID) technology is widely used in many fields, including supply chain monitoring, storehouse management and
Storage controlling.In such applications, physical object is labeled with the RFID label tag being passively or actively, and each label includes one unique
ID.RFID reader collects the presence of the ID detection object of appended label by wireless channel.Because of the inquiry of reader
Region is limited, and large-scale RFID system is usually deployed multiple reader cooperations and covers all labels.However, in more readers
In RFID system, there is three kinds of important conflicts between label and reader: tag-tag (Tag-Tag, TT) conflict is read
Read device-label (RT) conflict and reader-reader (RR) conflict.It is defined as follows (schematic diagram is shown in Fig. 1):
Tag-tag (TT) conflict: when two or more labels in the interrogation of the same reader are same
When sending a signal to the same reader (Fig. 1 (a)), TT conflict occurs.
Reader-Tags (RT) conflict: RT conflict occurs when a reader is in the interference region of another reader
When (Fig. 1 (b)).In this case, the signal of B can interfere the signal from label 3 to A to transmit, this makes A that can not identify label 3.
Worse, this conflict may prevent A from receiving the response from any label in the whole process.
Reader-reader (RR) conflict a: if label is located at the read area of two (or multiple) adjacent readers
Then when the label is received from the signal of two (or multiple) readers simultaneously RR conflict (Fig. 1 occurs for the overlapping place in domain
(c)).Although reader still can be read it should be noted that RR conflict can make the label of overlapping region that can not be accessed
Other labels in oneself interrogation.
Existing list reader-tag recognizer is primarily upon the tag-tag punching how solved in single reader system
It is prominent, such as document [1,7,15].Other two kinds of conflicts that present invention is primarily concerned with points in more readers: Reader-Tags conflict
(Fig. 1 (b)) and reader-reader conflict (Fig. 1 (c)).This respect has had a few thing, as document [9,20,23,
30].These have work and focus mainly in different times running adjacent reader scheduling to avoid RT conflict and RR
Conflict.Although reducing conflict, the reader that management and running simultaneously are capable of in these systems is only all readings in system
The sub-fraction of device, this significantly limits the identification handling capacity of label in system.The Season method proposed in document [30]
By dispatching all readers simultaneously come the label in identifying system.However, this method not can solve RT conflict, performance pole
The big deployment way dependent on reader.When reader random placement, performance can decline to a great extent.
Existing tag identification technologies can be divided into two major classes, the tag recognition algorithm in single reader system and more readings
Tag recognition algorithm in device system.Single reader-tag recognition methods is there are mainly two types of technology: technology based on ALOHA [1,
6,7,15] technology [9] and based on tree decomposed.However, the tag recognition algorithm in single reader system does not account for reader-
Reader collision and Reader-Tags conflict, therefore the effect that cannot have been obtained in more reader systems.
Prior art in more reader systems mainly includes [21,22,23,30].This kind of algorithm is adjacent by dispatching
The reader that may cause conflict works in different times, so as to avoid reader-reader conflict and Reader-Tags
Conflict.However, this method prevents adjacent reader from working at the same time, therefore it is capable of readding for management and running simultaneously in system
The sub-fraction that device only accounts for all reader numbers in system is read, the tag recognition handling capacity of system is strongly limited.Document
[30] it is proposed in and ignores conflict first, dispatch all readers to carry out the Season method of tag recognition.However, this method
R-T conflict is not solved, (the case where i.e. reader rule is disposed in the case where non conflicting region is much smaller than conflict area is only capable of
Under) obtain better effects.When reader random placement, performance sharply declines.
EPC C1G2 agreement is one of single reader-tag identification protocol most widely used at present.It uses multiple frames
Mode identifies label.When, there are when unidentified label, reader is joined by broadcast one comprising frame sign in identification region
The order of f is counted to start a frame, wherein f indicates how many time slot in the frame.When label receives the order, each label
A random value is selected from [0, f-1], and the value is loaded into the time slot counter of oneself.Meanwhile each label by using
Randomizer generates 16 random numbers, i.e. RN.Then duplicate transmission QueryRep order instruction is next for reader
The beginning of a time slot.Whenever a label receives a QueryRep order of reader, which subtracts its time slot counter
1.When the value of the time slot counter of label is zero, which is sent RN by the method (Backscatter) of back scattering
To reader.
As shown in Fig. 2, according to the difference of the number for the label for sending RN simultaneously, in EPC C1G2 there are three types of it is different when
Gap: single time slot, conflict time slot and empty slot, wherein have one respectively, it is more than one, and and RN is sent to reader without label.
The duration of different time-gap is different, and consequently leads to the asynchronism between different readers, and reads just because of this
The asynchronism read between device results in Reader-Tags conflict.For example, it is assumed that the time slot sequence of reader A and B in Fig. 1 (b)
Column are (conflict, single, sky) and (single, conflict, empty) respectively, then the QueryRep order of reader B, which would interfere with label 3, arrives A's
ID transmission, so that RT conflict occur (because the order that reader B is broadcasted when label 3 sends ID to A can interfere with reader A
To the signal identification of label 3).Due to the time-slot sequence of each reader be it is random, be based on traditional EPC C1G2 agreement
Reader-Tags conflict can not be can solve.
Radio frequency identification, RFID (Radio Frequency Identification) technology, also known as radio frequency identification are
A kind of communication technology can be identified specific objective by radio signals and read and write related data, without identifying system with it is specific
Mechanical or optical contact is established between target.
Reader:, can be with computer by being wirelessly or non-wirelessly connected to the network for the equipment identified to label.
Label: it can adhere on object and object be identified and records the equipment of its information.
Frame: the mode that reader is communicated with label.Each frame includes multiple time slots, and each time slot is carried out by reader
It is synchronous.In each time slot, reader is first to all tag broadcast querying commands, and label returns to corresponding letter to reader
Breath.Each label only selects that a time slot in each frame to send the information of oneself to reader.
The random number of RN16: one 16 bit.Channel contention is used only in conventional labels identification protocol, and at me
Agreement in can be also used for judging whether label is overlapping tags and new label.
Summary of the invention
The technical problem to be solved by the present invention is in view of the shortcomings of the prior art, provide a kind of reader-tag identification side
Method.
In order to solve the above technical problems, the technical scheme adopted by the invention is that: a kind of more readings divided based on time slot
Device RFID system fast tag recognition methods, comprising the following steps:
1) when in the first stage, frame starts, reader group gives tag broadcast one querying command simultaneously, then etc. to be received
Tag return is successfully received the label of some reader inquiry according to the parameter for including in querying command, uses hash function
Selection replies time slot, and then included RN is returned to reader in the time slot of its selection by the label, in a slot, if read
Device is properly received RN, which records this RN, other are confiscated the reader of RN or detect the reading of signal conflict
Device uniformly waits for a period of time, and then reader group is synchronous sends QueryRep order one new time slot of beginning；
2) second stage, in each time slot, all readers are sent comprising being previously respectively received in reader group
RN ACK, the label of RN having the same sends the ID of the label to reader.
The reader group selection process are as follows:
1) initialization enlivens reader set A as sky；
2) when new reader is added, the subregion si of unlabelled maximum weight is found, and this sub-regions is set
It is set to marked state；
3) all readers for being associated with above-mentioned subregion are tested in turn, is actively read if some reader is added to
It reads in device collection A, enliven the reading efficiency value of reader set and be E (rj)=eff ({ rj } ∪ A)；eff
({ rj }) is the reading efficiency of reader rj；For the reader group that can cover subregion si；
4) picking out can make system effectiveness increase maximum reader rk, so that enlivening the reader of reader set A
Efficiency increases, and the reader is added to A；
5) the rk all subregions covered are arranged to flag state；
6) step 1)~5 are repeated), until not new reader is added.
The length of the frame are as follows:
Wherein, nriThe ID number collected for reader ri；trnFor the length of each time slot of RN collection phase；tidFor ID receipts
The length of collection stage each time slot.
Compared with prior art, the advantageous effect of present invention is that: the present invention can fully eliminate RT conflict, together
When propose a kind of dispatching method the influence that RR conflicts to tag recognition efficiency is effectively reduced.Compared to existing tag recognition side
Method, the present invention can effectively improve tag recognition handling capacity 198%.
Detailed description of the invention
Fig. 1 (a), Fig. 1 (b), Fig. 1 (c) are respectively TT conflict, RT conflict, RR conflict in more reader systems；
Fig. 2 is EPC C1G2 protocol implementation；
Fig. 3 is the schematic diagram of time slot partitioning technology；
Fig. 4 is subregion schematic diagram；
Fig. 5 is maximum throughput reader selection algorithm process；
Fig. 6 is the optimal frame length in 100 simulating scenes, and 100 readers, weight is between 100 to 200；
Fig. 7 (a) and Fig. 7 (b) is the scheduling time of algorithms of different；
Fig. 8 (a) and Fig. 8 (b) is the handling capacity of algorithms of different；
Fig. 9 (a), Fig. 9 (b) and Fig. 9 (c) are that the identification delay of different-scale systems in random placement is compared；
Figure 10 is the identification delay in regular deployment scheme；
Figure 11 (a) is the duration of EPC C1G2 different time-gap；Figure 11 (b) is the signal during time slot divides；
Figure 12 is to enliven reader to select example.
Specific embodiment
The present invention is observed to be required to carry out same behavior to be to collect RN in all readers of each time slot: being read
Device broadcasts QueryRep in each time slot, and label is waited to send RN (s).Only when reader is successfully received a RN, read
Device is read by replying the ACK including received RN, label could be required to send its ID.Single time slot has maximum duration, because
ID is needed to transmit for it.If reader single time slot only collect RN (s) without reply ACKs (thus not causing ID to transmit),
Single time slot will have duration identical with the time slot that conflicts.I.e. reader directly transmits one after receiving RN (s) from label
QueryRep order starts next time slot.In addition, if the duration of empty slot is expanded to and is conflicted time slot/mono- time slot phase
Together, then all readers can all execute simultaneously operating, i.e., they understand transmission QueryRep order simultaneously and connect from label
Receive RN (or waiting, but this obviously will not influence other readers).This technology is called time slot and divides (Slot by we
Splitting).Tag recognition process using time slot partitioning technology includes two stages: RN collection phase and ID collect rank
Section.In RN collection phase, all readers send QureyRep order and receive RN (or waiting)；In ID collection phase, institute
Some readers send the ACK comprising the RN having successfully received in single time slot in the first stage and collect corresponding ID.Utilize this
Kind technology, all readers are carried out same movement at any time or send signal or receive signal, without
It will appear reader and send signal and another reader the problem of receiving, to completely eliminate Reader-Tags punching
It is prominent.Specific step is as follows for time slot division:
Step 1:RN collection phase: reader only collects RNs.When frame starts, reader gives tag broadcast one first
Inquire the answer time slot to select them.Its RN is transferred to reader in the time slot of its selection by label.If reader success
Receive RN, it records this RN.Then, do not have to reply ACK, it by send QueryRep order beginning one it is new when
Gap.
Step 2:ID collection phase: reader collects tag ID according to the RNs that the first stage receives.In each time slot,
Reader sends the ACK comprising previously received RN.The label of RN having the same sends its ID to reader.Obviously,
The number of labels of collection is solely dependent upon the quantity of the RNs collected in the first stage.
Time slot division easily can carry out rearranging realization by the sequential relationship of original EPC C1G2 agreement.To mark
Label do not change: label replys RNs when time slot counter is zero, and receive include before send RNs ACK when reply
Tag ID.And for reader, unique modification is that they change the time for sending ACK.Fig. 3 gives a time slot
The example of division.
1) it is based on the maximized reader-reader conflict avoidance of reading efficiency
Based on time slot partitioning technology, all readers can be worked at the same time without by reader-mark in system
Sign the interference of (RT) conflict.But reader-reader (RR) conflict still remains, so that collectively covering area by multiple readers
Label in domain can not be successfully identified.As soon as every increase enlivens reader, also it is likely to increase reader-reader
(RR) region to conflict, causes the more more effects instead of the reader worked at the same time in some cases poorer.
In order to further increase reading efficiency, the invention proposes a kind of reader dispatching algorithms to pick out one group of reading
Device works so that system reading efficiency highest, the algorithm are known as Federal.For the clearer description for providing this agreement,
We are provided first as given a definition:
1) subregion.One sub-regions are such a regions, and all points can be by identical reader collection in region
Close covering.As shown in figure 4, each reader has the reading area of oneself.The reading area of adjacent reader is overlapped, will
Region division where whole system is multiple subregions.
2) associate reader/association subregion.If subregion s, in the read range of reader r, s is referred to as the association of r
Subregion, r are referred to as the associate reader of s.In more reader systems, a reader can usually be associated with multiple subregions,
And a sub-regions can also be associated with multiple readers.All associate reader collection of subregion s are combined intoAs shown in figure 4, readding
It reads device r1 and is associated with { s1, s2, s8, s9 } 4 sub-regions.Likewise, subregion s2 is associated with { r1, r2 } two readers.
3) single covering subregion/more cover subregion.If just there is one to be scheduled in the associate reader of a sub-regions
Work, then the region is referred to as single covering subregion.If there is more than one scheduled work in the associate reader of a sub-regions,
Then the region is referred to as more covering subregions.Label in the domain of multiple coverage areas can be because receiving the information of multiple readers and sending out simultaneously
Raw reader-reader (RR) conflict.Obviously the label in only single covering subregion can be successfully identified.
4) weight/reader weight of subregion.The weight w (s) of one sub-regions s is defined as in the subregion not yet
Identified number of tags.The weight w (r) of one reader r is defined as the weights sum of single overlay area in the reader.
5) reading efficiency.The set A={ r1, r2 ..., rm } of a given reader, and assume w=Max w (ri) | ri
∈A}.Then the reading efficiency of any reader ri is defined as eff (ri)=w (ri)/w in the reader set.
It can be proved that assume that A is one group and enlivens reader set, then in A reader reading efficiency and higher, system
Tag recognition handling capacity it is bigger.The variation for enlivening reader set also results in the variation of single covering subregion.It is every to increase by one
It is a to enliven reader, it often will increase single covering subregion, but be also possible to become to cover by existing single covering subregion more
Subregion reduces the sum of reader reading efficiency so that the label in the region can not be identified instead.Therefore, under us
Face provides an algorithm and enlivens reader for one group to find in system, is reduced between reader by maximizing reader efficiency
RR conflict, to effectively improve system identification handling capacity.
The algorithm successively tests each reader by way of iteration, and satisfactory reader is added to and is actively read
It reads in device set A.Most starting A is empty set.When needing to be added new reader every time, which finds unlabelled maximum weight
Subregion si, and this sub-regions is arranged to marked state.Then to all reading device wheels for being associated with this sub-regions
Stream is tested, and is calculated and is assumed for some reader to be added to enliven in reader collection A, enlivens the reading efficiency value of reader collection
SumPicking out can make system effectiveness increase maximum that reader rk, so thatAnd it adds it to and enlivens reader collection.This process is repeated until without new
Reader can be added into.
The detailed process of algorithm is presented in Fig. 5.
The setting of optimal frames length:
Due to the weight number of the unidentified label in i.e. each reader coverage area (different) of each reader, because
It is optimal frame length setting for all readers that this, which is not present one,.Here we provide a setting optimal frame length
The method of degree.Since the frame length of ID collection phase depends on the RN number that is collected into of first stage, so it is contemplated that how
First stage minimizes the acquisition time of each RN frame length is arranged.
Assuming that being n in the ID number that second stage reader ri is collectedri.The length of each time slot of RN collection phase is assumed simultaneously
Degree is trn, and the length of each time slot of ID collection phase is tid.During so entire tag recognition needed for each tag recognition
Time be
It is easy to obtain
Then to maximize tag recognition handling capacity, then should be minimized, so optimal the average time of tag recognition
Frame length should be
Since analytic solutions are not present in above formula, we have proposed two methods: one is by f1It is set as in all w (ri)
Between be worth, another kind is by f1It is set as the average value of all w (ri).Fig. 6 gives setting for the optimal frames in 100 simulated scenarios
It sets as a result, showing f1Substantially all readers of optimal value w (ri) median or so.
1) performance of the time slot partitioning technology in single reader system
Label in single reader system be averaged recognition time derive it is as follows.Without loss of generality, consider any one frame.With
TtotalIndicate the total time (including stage 1 and stage 2) of this wheel.N ' is allowed to indicate the number of labels determined in this wheel.Then know
The average time of an other label is
The time-slot duration in two stages is different.It is taken more time since ID transmission needs to transmit than RN,
It is longer than the time-slot duration trn in stage 1 in the time-slot duration tid in stage 2.F is used respectively1And f2Expression stage 1 and rank
The frame sign of section 2.Then, total time Ttotal=f1×trn+f2× tid: frame sign f2Equal to the RNs number collected in the stage 1
Amount, i.e. f2=n '=f1×P1；P1 is the ratio in single time slot in stage 1.N indicates the label unidentified when this wheel starts
Sum.It is known as f1=n, a time slot is the maximum probability of single time slot, in this case
Wherein e is natural constant.Number of labels n '=f1 of collection × P1 ≈ n × e-1.To divide identification one with time slot
The expeced time of a label is
2) the identification handling capacity in more reader systems
We conducted a large amount of emulation to come Federal method more proposed by the present invention and other two kinds of main readings
Device dispatching algorithm: Season [28] and EGA [31].The index used in assessment includes scheduling time (being defined as collection system
In the time needed for all label), tag recognition handling capacity (quantity for being defined as the label of collection per second) and tag recognition
Delay.For calculating the scheme that clocks of scheduling time, it then follows EPC C1G2 standard criterion [5], it is assumed that data rate is
62.5Kbps.Duration for Season and EGA, empty slot, single time slot and conflict time slot is respectively 0.184ms, 2.4ms
And 0.44ms.It is 0.44ms in the duration of one time slot of RN collection phase for Federal, and in ID collection phase one
The duration of a time slot is 1.96ms.
It is contemplated that the system of three kinds of different scales: it is small, in, greatly.For each scale, it is contemplated that two kinds of readers
Deployment strategy: rule deployment is deployed to a mesh model in reader wherein, random placement is in reader wherein
Random distribution.In randomized policy, we delete extra reader and keep their quantity minimum.For identical scale,
Reader quantity in randomized policy is twice or so of reader quantity in regular strategy.Label is evenly distributed on system
In, each reader covers about 500 labels.Interference radius is set as 1.5 times of inquiry radius.Simulation parameter is listed in table 1.
The setting of 1 simulation parameter of table
| System size | It is small | In | Greatly |
| Reader number (rule deployment) | 16 | 64 | 121 |
| Reader number (random placement) | About 30 | About 130 | About 250 |
| Number of tags | 4000 | 16000 | 36000 |
C. simulation result
Median and average: as previously mentioned, frame sign should be set as all " centre " values for enlivening reader weight.I
Compare two kinds of heuristics: median, use the median of all reader weights as frame sign；Average makes
With the average weight of all readers.Table 2 lists two kinds of tactful scheduling times and handling capacity in a minisystem.It is flat
Mean method is slightly better than median method.Therefore, we use average counting method in following emulation.
2 median of table is compared with average value
| Time (second) | Handling capacity (label is per second) | |
| Using median (random/rule) | 1.627/2.092 | 2462/1917 |
| Using average value (random/rule) | 1.576/1.958 | 2540/2045 |
2) scheduling time: as shown in Fig. 7 (a), when the deployment of reader rule, when the systems get large, all three algorithms
Scheduling time only increases a bit.Federal and Season is substantially better than EGA, and Federal ratio Season is further reduced about
30% time.When reader is by random placement (Fig. 7 (b)), when system becomes larger, the scheduling time of Season and EGA are dramatically increased,
Because they need more wheel numbers to arrange all readers.In contrast, the scheduling time of Federal only slightly increases
Add.The time that all labels save 66% and 68% is collected compared to Season and EGA, Federal.In addition, when system is advised
When mould rises, improvement is become readily apparent from.We can also be observed that Season is compared to EGA when reader is by random placement
Improvement start to become less significant, Season is because most of label is located at overlapping region, Bu Neng in this case
Its first stage effectively identifies label.
Handling capacity: as shown in Fig. 8 (a) and Fig. 8 (b), when system scale increases, more readers can parallel work
Make, to improve the handling capacity of all three algorithms.When the deployment of reader rule, Season and EGA is executed good, such as Fig. 8
(a) shown in.However, when reader is by random placement, they execute variation, as shown in Fig. 8 (b), because of a reader
It may be than interfering more readers under regular deployment mode.This makes Season and EGA using more wheels to dispatch
There is reader.In contrast, Federal realizes similar handling capacity under both deployment scenarios.Compared to Season and
EGA, in rule deployment, Federal increases handling capacity up to 36% and 78%, is more up in the case where random placement
194% and 218%.In addition, Federal becomes readily apparent from the improvement of Season and EGA when system becomes much larger.
D. identification delay
Fig. 9 (a)~Fig. 9 (c) depicts the duration of the identification delay in reader random placement in algorithms of different.
As can be seen that can quickly identify label (in the initial 500ms of mini system, in medium-and-large-sized system in three kinds of algorithms of scheduling initial stage
Initial 1000ms).However, over time, the identification delay of Season and EGA obviously increase, because only that one is small
Part reader can arrange work, and wait the label except these reader interrogations before recognition for a long time.
In contrast, label can be constantly identified in most of readers of Federal.Compared to Season and EGA, in Federal
49% (1831ms vs.3601ms) and 48% (1831ms vs.3574ms) is reduced the time required to the label of identification 80% respectively.
We can also be observed that in random placement scheme Season performance close to EGA.However, in regular deployment scheme, Season
It is more far better than EGA, as shown in Figure 10.Under regular deployment scheme, the speed of label is identified even in incipient stage Season
Faster than Federal.This is because labeling requirement all in Federal waits RN collection phase to terminate.Crosspoint occurs
Label 70% has been identified, and later, Federal can faster identify label than Season.
Platform validation: we USRP software definition platform realize time slot divides and use may be programmed WISP label Verification its can
Row.There are two can be in the USRP platform of the RFX900 daughter board of 900MHz band operation for our uses.USRP stage+module two
A antenna is simultaneously connected to a laptop as reader.Four WISP Programmables based on 4.1 firmware of DL-WISP
Part is as label.Because most of common operation (such as QUERY, ACK) realizes that we only need in USRP and WISP firmware
Slight modifications firmware code is wanted to realize the prototype of our time slot partitioning technologies.The experiment is can be same in order to verify time slot division
The action of reader is walked, and meets existing tag recognition standard.
The present invention realizes that time slot is drawn as reader and four programmable WISP labels by the USRP1 of two antennas
Point.
Figure 11 (a) and Figure 11 (b) shows the duration of the different time-gap in EPC C1G2 and time slot are divided.Such as Figure 11
(a) shown in, there is the different duration in EPC C1G2 different time-gap.Figure 11 (b) shows the signal in time slot division.It is same
All time slots in stage duration all having the same.Note that reader is sending next QueryRep in empty slot
A very short time is waited, before to keep the duration of empty slot identical with other time slots.In order to preferably may be used in figure
We stretch the duration of time slot to the property read, but it is constant to be to maintain its relative scale, i.e. tE:tS:tC=1:13:2.4, tE, tS
It is empty slot respectively with tC, the duration of single time slot and conflict time slot.
Figure 12 shows the example for enlivening reader selection.There are five reader R={ a, b, c, d, e } in system.
In its weight of the digital representation of each subregion.According to reader selection algorithm, reader a, c, d, e, b are successively surveyed
Examination.It is last the result is that A={ a, c, d, e } because of reader efficiency Eff (a, c, d, e, b) < Eff (a, c, d, e).
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