CN109117687B - HZE-based lost label iceberg query method for large-scale grouping RFID system - Google Patents
HZE-based lost label iceberg query method for large-scale grouping RFID system Download PDFInfo
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- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/10009—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves
- G06K7/10019—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves resolving collision on the communication channels between simultaneously or concurrently interrogated record carriers.
- G06K7/10079—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves resolving collision on the communication channels between simultaneously or concurrently interrogated record carriers. the collision being resolved in the spatial domain, e.g. temporary shields for blindfolding the interrogator in specific directions
Abstract
The invention relates to a lost label iceberg query method of a large-scale grouping RFID system based on HZE, which comprises the following steps: the lost label query comprises w rounds, when any k-th query is finished, and k is more than or equal to 1 and less than or equal to w rounds, the reading head obtains the estimated values of the lost labels of all groups under the estimation of the current round, and calculates the expected values and the variance of the estimated values; after the estimation process of the k-th round of query is finished, the reading head calculates the mean value of each group of lost label estimation values obtained under each round of estimation in the previous k rounds as each group of lost label estimation values when the current round of estimation is finished, and calculates the expected value and the variance of each group of lost label estimation values; after the w-th round of query is finished, the reading head classifies the tag groups, the accuracy of the query results of the w rounds is verified, if the query accuracy meets the required credibility requirement, the query process is finished, and the tag group series gamma' is obtained; otherwise, the query process is continued until the query accuracy reaches the required credibility requirement. The method and the device can improve the query efficiency of the lost label iceberg and shorten the query time.
Description
Technical Field
The invention belongs to the technical field of radio frequency identification and Internet of things, relates to a radio frequency identification system, and particularly relates to a lost label iceberg query method of a large-scale grouping RFID system based on HZE.
Background
A Radio Frequency Identification (RFID) system generally includes a background server, one or more readers (Reader) and a plurality of tags (Tag), where the readers can simply communicate with the tags in the Radio Frequency transmission range through a wireless channel. The background server prestores the ID of each tag, and can exchange information with the reading head in a wired or wireless mode. The most direct label loss iceberg query method is that a reading head continuously broadcasts the ID of each label group one by one, the label returns response information immediately after receiving the ID information, and the reading head detects the number of unresponsive labels of each label group until the number reaches a threshold value. The method has the advantage that the reliability of the lost label iceberg query can reach 100%. The other method is based on a frame time slot Aloha (framed Slotted Aloha) protocol, a reading head broadcasts a frame length and a random number seed, each label calculates respective response time slots through a hash function based on the received frame length, the random number seed and the ID of the label, the reading head can predict the state of each time slot in advance, and further detects the actual state of each time slot to estimate the number of lost labels of respective label groups. The lost label iceberg query method can be used for monitoring and managing articles in large-scale warehouses or shopping malls, and the label group series with the number of the lost labels larger than a threshold value is determined through the iceberg query of the lost labels, so that the inventory management efficiency is effectively improved. However, the lost tag iceberg query problem still faces several major challenges: (1) how to improve the query efficiency, namely how to accelerate the speed of the lost label iceberg query process; (2) how to satisfy the required query confidence level; (3) how to overcome the interference created by the responses of multiple sets of tags.
In the application of the RFID system, the ID information of the tags in the system is usually stored by a background server, and the reader can acquire the tags in real time, which is called known tags, that is, the ID information reader is known. However, there may be some tags in the system that do not store ID information in the background server, and the reader cannot acquire information of these tags in advance. For example, in a large warehouse, since there are often new incoming goods, the information of the tag attached to the new incoming goods may not be stored in the background server in time, and therefore, the tag becomes an unknown tag. In the process of estimating the number of lost tags by the reading head, the unknown tags and the known tags cannot be distinguished, so that the unknown tags also send corresponding response information to interfere with the process of estimating the number of lost tags.
The existing lost label iceberg query method of the large-scale grouping RFID system is an ES method. The ES method (see l.xie, h.han, q.li, j.wu, s.lu. efficient Protocols for Collecting databases in Large-Scale RFID Systems. ieee Transactions on Parallel and Distributed Systems, 2015.9, pp.2421-2433.) is a lost tag number estimation method based on time slot Aloha, including multiple rounds of estimation. In each round of estimation process, a reading head firstly broadcasts information containing r and f, wherein r is a random seed number, f is the number of time slots of each Frame (Frame), each tag selects a response time slot of the tag according to parameter information broadcast by the reading head and the ID of the tag, the reading head counts the number of the time slots selected by only one tag in the execution Frame and the number of the time slots individually selected by the tags in each tag group, and the number of lost tags of each tag group is estimated according to the number of the time slots, so that the lost tag icehill query of the large-scale grouping RFID system is realized. However, the above-mentioned lost tag iceberg query method of the large-scale packet RFID system has a general defect that the query process is slow, thereby resulting in low efficiency of the lost tag iceberg query.
Disclosure of Invention
Aiming at the defects of low query efficiency and the like caused by slow query process in the prior art, the invention provides the HZE-based lost label iceberg query method of the large-scale grouping RFID system, which can improve the query efficiency of the lost label iceberg and shorten the query time.
In order to achieve the above object, the present invention provides an HZE-based method for querying lost tags in iceberg of a large-scale packet RFID system, wherein the large-scale packet RFID system comprises a background server, a read head and n tags divided into
Known tags of subgroups, each subgroup of tags comprising niA label, wherein miA tag is lostThe number of the labels is such that,
each tag has a unique 96-bit ID; the query method comprises the following steps:
when any query of the kth round is finished, and k is more than or equal to 1 and less than or equal to w, the reading head calculates the estimation values of all groups of lost tags under the estimation of the current round, and calculates the expected values and the variance of the estimation values; the specific process comprises the following steps:
at the initial moment of any kth wheel, the reading head sets the frame length fkIs composed of
Generating a random number seed; the reading head predicts the state of each time slot of the current frame to obtain an expected frame based on the frame length, the random number seeds and the ID of each label; if the prediction state of the current time slot is only selected by the labels in the same group, the time slot is called as an isomorphic time slot, and if the prediction state of the current time slot is not selected by the labels, the time slot is called as an empty time slot; the reading head broadcasts the frame length and the random number seed, and each tag receives the frame length and the random number seed information to calculate the number of the response time slot of the tag; the reading head executes each time slot of the expected frame one by one, and each label returns 1 bit of response information in the label response time slot; the reading head detects the actual state of each time slot to obtain an execution frame; read head statistics CiThe time slots selected by the tags in the tag group correspond to the number of time slots which are 'isomorphic time slots' in the expected frame and 'null time slots' in the executed frame, and are used
Indicating that the lost label estimation value of each label subgroup under the k-th estimation
Comprises the following steps:
further calculating the estimated value of the lost label
The expected value and variance of (c) are:
in the formula (I), the compound is shown in the specification,
estimate value for lost tag
The expected value of (c) is,
estimate value for lost tag
Variance of (m)iIs CiThe number of missing tags in the tag subgroup.
After the estimation process of the k-th round of query is finished, the reading head calculates the mean value of each group of lost label estimation values obtained under each round of estimation in the previous k rounds as each group of lost label estimation values when the current round of estimation is finished, and calculates the expected value and the variance of the estimation values;
after the w-th round of query is finished, classifying the tag groups by the reading head according to whether the estimated value of the number of the lost tags of each group is greater than a given tag number threshold T, verifying the accuracy of the query result of the w round, and finishing the query process and obtaining a tag group series gamma' if the query accuracy meets the required reliability requirement; otherwise, the query process is continued until the query accuracy reaches the required credibility requirement.
Preferably, in the step (two), after the estimation process of the read head in the k-th round of query is finished, the read head averages the small groups of lost tag estimation values obtained under each round of estimation in the front k-th round by using a formula (4), where the expression of the formula (4) is:
in the formula (I), the compound is shown in the specification,
the mean value of each group lost label estimated value obtained under each estimation in the front k rounds is obtained;
calculating to obtain the mean value of the estimated values of the lost labels of each group
As the estimated value of each group lost label when the current wheel is finished, and further calculating the average value
The expected value and variance of (c) are:
in the formula (I), the compound is shown in the specification,
mean values of missing label estimates for each subgroup
The expected value of (c) is,
losing tags for groupsMean value of estimated values
The variance of (c).
Preferably, in the step (iii), after the w-th round of query is completed, the reader classifies the tag groups, and if the estimated number of missing tags in a certain group is greater than a given tag number threshold T, the group is divided into a tag group series Γ.
Preferably, in the step (three), after the w-th round of query is finished, the reading head performs accuracy verification on the query result, that is, the reading head judges whether the query result meets the following two limiting conditions under the conditions that a given tag number threshold value T, an error threshold value epsilon, 0< epsilon <1 and a required reliability delta, 0< delta < 1:
if the query result simultaneously meets the two limiting conditions, the query accuracy meets the required credibility requirement, the query process is ended, and the tag group gamma' is obtained; if the query result does not satisfy the two limiting conditions at the same time, which indicates that the query accuracy does not meet the required reliability requirement, the reading head continues the query process round by round until the required reliability requirement is satisfied.
Preferably, when the reading head performs accuracy verification on the query result, if CiThe tag subgroup belongs to the tag group series Γ, and the inequality
If true, Pr [ m ] is obtainedi≥(1-ε)T]Delta is more than or equal to; if CiThe tag subgroup does not belong to the tag group series Γ, and the inequality
If true, Pr [ m ] is obtainedi≤(1+ε)T]Delta is more than or equal to; where phi is a standard normal distribution function, phi-1(. cndot.) is the inverse of the standard normal distribution function.
Compared with the prior art, the invention has the beneficial effects that:
(1) the invention can effectively complete iceberg query of lost labels of a large-scale packet radio frequency identification system, and the accuracy of query results can meet the required reliability requirement.
(2) In the invention, the quantity of the lost tags of each group is estimated in the process of inquiring the tags by the reading head, and the counting of C is carried out by the reading headiThe number of the time slots of which the time slots selected by the tags in the tag groups correspond to the number of the time slots of which the expected frames are isomorphic time slots and the executing frames are empty time slots, so that the estimated lost tag estimation value of each tag group is obtained, the reliability required by a radio frequency identification system can be met, the iceberg query efficiency of the lost tags is effectively improved, and the query time is shortened.
Drawings
FIG. 1 is a block diagram of a large scale packet RFID system.
Fig. 2 is a process diagram of a lost label iceberg query method of a large-scale packet RFID system based on HZE according to an embodiment of the present invention.
Fig. 3 is a schematic diagram comparing execution time of the lost label iceberg query method of the large-scale packet RFID system based on HZE with the execution time of the existing method varying with the number of label sets when δ is 0.85.
Fig. 4 is a comparison diagram of execution time of the lost label iceberg query method of the large-scale packet RFID system based on HZE according to the embodiment of the present invention when δ is 0.95, and the execution time of the existing method varies with the number of label sets.
Fig. 5 is a comparison diagram of actual credibility of the lost label iceberg query method of the large-scale packet RFID system based on HZE and the existing method as a function of the number of label sets at 0.85.
Fig. 6 is a comparison diagram of actual credibility of the missing tag iceberg query method of the large-scale packet RFID system based on HZE and the existing method as a function of tag group number when δ is 0.95.
Detailed Description
The invention is described in detail below by way of exemplary embodiments. It should be understood, however, that elements, structures and features of one embodiment may be beneficially incorporated in other embodiments without further recitation.
Referring to fig. 1, a large-scale grouping RFID system includes a background server 1, a reader 2, and n divided into
Known tags 3 of subgroups, each subgroup of tags comprising niA label, wherein miThe individual tag is a missing tag 4,
the remaining are existing tags 5, each having a unique 96-bit ID. The reading head carries out one-to-one communication with the tags in the radio frequency range of the reading head through a wireless channel, and the background server prestores the ID of each tag and carries out information exchange with the reading head in a wired or wireless mode. In order to effectively avoid packet collision, the reading head communicates with the tag by adopting a frame time slot-based Aloha protocol.
An HZE-based method for inquiring lost labels of a large-scale grouping RFID system in iceberg, which is used for inquiring the lost labels of the large-scale grouping RFID system in iceberg and comprises the following steps:
the method comprises the following steps: the lost label query comprises w rounds, when any k-th query is finished, and k is more than or equal to 1 and less than or equal to w rounds, the reading head calculates the estimated value of each group of lost labels under the estimation of the current round, and calculates the expected value and the variance of the estimated value; the specific process comprises the following steps:
at the initial moment of any kth wheel, the reading head sets the frame length fkIs composed of
Generating a random number seed; the reading head is based on the frame length, the random number seed andthe ID of each label predicts the state of each time slot of the current frame to obtain an expected frame; if the prediction state of the current time slot is only selected by the labels in the same group, the time slot is called as an isomorphic time slot, and if the prediction state of the current time slot is not selected by the labels, the time slot is called as an empty time slot; the reading head broadcasts the frame length and the random number seed, and each tag receives the frame length and the random number seed information to calculate the number of the response time slot of the tag; the reading head executes each time slot of the expected frame one by one, and each label returns 1 bit of response information in the label response time slot; the reading head detects the actual state of each time slot to obtain an execution frame; read head statistics CiThe time slots selected by the tags in the tag group correspond to the number of time slots which are 'isomorphic time slots' in the expected frame and 'null time slots' in the executed frame, and are used
Indicating that the lost label estimation value of each label subgroup under the k-th estimation
Comprises the following steps:
further calculating the estimated value of the lost label
The expected value and variance of (c) are:
in the formula (I), the compound is shown in the specification,
estimate value for lost tag
The expected value of (c) is,
estimate value for lost tag
Variance of (m)iIs CiThe number of missing tags in the tag subgroup.
Step two: after the estimation process of the k-th round of query is finished, the reading head calculates the average value of each group of lost tag estimation values obtained under each round of estimation in the front k round through a formula (4), wherein the expression of the formula (4) is as follows:
in the formula (I), the compound is shown in the specification,
the mean value of each group lost label estimated value obtained under each estimation in the front k rounds is obtained;
calculating to obtain the mean value of the estimated values of the lost labels of each group
As the estimated value of each group lost label when the current wheel is finished, and further calculating the average value
The expected value and variance of (c) are:
in the formula (I), the compound is shown in the specification,
mean values of missing label estimates for each subgroup
The expected value of (c) is,
mean values of missing label estimates for each subgroup
The variance of (c).
Step three: after the w-th round of query is finished, the reading head classifies the tag groups according to whether the estimated value of the number of the lost tags of each group is larger than a given tag number threshold T, and if the estimated value of the number of the lost tags of a certain group is larger than the given tag number threshold T, the group is divided into a tag group series gamma. The reading head carries out accuracy verification on the query result, namely the reading head judges whether the query result meets the following two limiting conditions under the conditions of a given label quantity threshold T, an error threshold epsilon, epsilon which is more than 0 and less than or equal to 1 and required reliability delta, delta which is more than or equal to 0 and less than 1:
if the query result simultaneously meets the two limiting conditions, the query accuracy meets the required credibility requirement, the query process is ended, and the tag group gamma' is obtained; if the query result does not satisfy the two limiting conditions at the same time, which indicates that the query accuracy does not meet the required reliability requirement, the reading head continues the query process round by round until the required reliability requirement is satisfied.
Read head pair lookupWhen the query result is subjected to accuracy verification, if CiThe tag subgroup belongs to the tag group series Γ, and the inequality
If true, Pr [ m ] is obtainedi≥(1-ε)T]Delta is more than or equal to; if CiThe tag subgroup does not belong to the tag group series Γ, and the inequality
If true, Pr [ m ] is obtainedi≤(1+ε)T]Delta is more than or equal to; where phi is a standard normal distribution function, phi-1(. cndot.) is the inverse of the standard normal distribution function.
The method of the invention is used for conducting iceberg query on the lost labels of the large-scale RFID system, and the accuracy of the query result can meet the required credibility requirement, namely, the two limiting conditions are met. The method of the invention effectively reduces the execution time of the query and improves the query efficiency under the early stage of meeting the reliability requirement.
When the method of the invention is used for calculating the number estimated value of the lost tags, the reading head predicts the state of each time slot of the current frame to obtain an expected frame based on the frame length, the random number seeds and the ID of each tag; if the prediction state of the current time slot is only selected by the labels in the same group, the time slot is called as an isomorphic time slot, and if the prediction state of the current time slot is not selected by the labels, the time slot is called as an empty time slot; the reading head broadcasts the frame length and the random number seed, and each tag receives the frame length and the random number seed information to calculate the number of the response time slot of the tag; the reading head executes each time slot of the expected frame one by one, and each label returns 1 bit of response information in the label response time slot; the reading head detects the actual state of each time slot to obtain an execution frame; read head statistics CiThe slots selected by the tags in the tag group correspond to the number of slots that are "homogeneous slots" in the expected frame and "empty slots" in the executed frame. The above process is abbreviated as "HZE".
To further illustrate the advantages of the above-described method of the present invention, the present invention is further described below with reference to the accompanying drawings and examples.
Example (b): referring to fig. 2, there are three tag subgroups C1, C2, and C3 in the RFID system, where t4, t5, t9, t10, t14, t15, and t16 are missing tags and the rest are existing tags. In the process of querying lost labels in the iceberg of any kth round, the reading head sets the frame length fkIs composed of
And generating a random number seed, broadcasting the frame length and the random number seed, and calculating the number of the response time slot of each label after each label receives the frame length and the random number seed information. The reading head predicts the state of each slot to obtain the expected frame as in fig. 2, and the slots selected by the tags in the same small group are called "isomorphic slots", and the slots not selected by any tags are called "empty slots". As shown in fig. 2, slot 2 and slot 4 in the desired frame are "isomorphic slots" as identified by the label in group C1, and slot 3, slot 5, slot 9, slot 11, and slot 14 in the desired frame are "empty slots". The reading head executes each time slot of the expected frame one by one, each tag sends 1 bit response information in the tag response time slot, and the reading head detects the actual state of each time slot to obtain the execution frame as shown in fig. 2. The reading head selects the number of time slots which are 'isomorphic time slots' in the expected frame and 'empty time slots' in the executed frame according to the state difference of the corresponding time slots in the expected frame and the executed frame, namely the labels in each small group
Namely:
the missing tag estimation value of each tag subgroup under the k-th round estimation
Is composed of
The reading head averages the estimated values of the lost tags of each group obtained by each round of query
Namely, it is
As the estimation value of each group missing tag at the end of the current round of inquiry, it is immediately judged whether the limiting condition formula (7) and the limiting condition formula (8) are simultaneously satisfied by the reading head. If the two limiting conditions are simultaneously met, the query result meets the required credibility requirement, the reading head ends the query process and obtains a tag group series gamma' meeting the two limiting conditions; otherwise, the readhead will continue the round and round of the interrogation process until both of the defined conditions are met simultaneously.
When the reliability δ required by the large-scale grouping RFID system is 0.85, the iceberg query method for the lost tag of the large-scale grouping RFID system based on HZE (hereinafter referred to as MAC-HZE method) and the existing ES method are adopted to perform iceberg query on the lost tag of the large-scale grouping RFID system, referring to fig. 3, although the execution time of the MAC-HZE method and the existing ES method of the present invention is increased along with the increase of the number of tag groups, the execution time of the MAC-HZE method of the present invention is obviously shortened compared with the existing ES method under the condition that the number of tag groups is the same.
When the reliability δ required by the large-scale grouping RFID system is 0.95, the lost tags of the large-scale grouping RFID system are subjected to iceberg query by adopting the MAC-HZE method and the conventional ES method, referring to FIG. 4, although the execution time of the MAC-HZE method and the conventional ES method is increased along with the increase of the number of tag groups, the execution time of the MAC-HZE method is obviously shortened compared with the conventional ES method under the condition that the number of tag groups is the same.
When the reliability delta-0.85 required by a large-scale grouping RFID system is adopted, the lost tags of the large-scale grouping RFID system are subjected to iceberg query by adopting the MAC-HZE method and the conventional ES method, referring to fig. 5, the actual reliability of the MAC-HZE method and the conventional ES method is basically unchanged along with the increase of the number of tag groups, and the actual reliability of the MAC-HZE method and the actual reliability of the conventional ES method both meet the required reliability under the condition that the number of tag groups is the same.
When the reliability delta-0.95 required by a large-scale grouping RFID system is adopted, the lost tags of the large-scale grouping RFID system are subjected to iceberg query by adopting the MAC-HZE method and the conventional ES method, referring to fig. 6, the actual reliability of the MAC-HZE method and the conventional ES method is basically unchanged along with the increase of the number of tag groups, and the actual reliability of the MAC-HZE method and the actual reliability of the conventional ES method both meet the required reliability under the condition that the number of tag groups is the same.
Therefore, the missing label iceberg query method of the HZE-based large-scale grouping RFID system can greatly reduce the query execution time, improve the query efficiency, effectively complete the missing label iceberg query of the large-scale grouping RFID system, and the accuracy of the query result can meet the required reliability requirement.
The above-mentioned embodiments are merely provided for the convenience of illustration of the present invention, and do not limit the scope of the present invention, and various simple modifications and modifications made by those skilled in the art within the technical scope of the present invention should be included in the above-mentioned claims.
Claims (5)
1. An HZE-based lost tag iceberg query method for a large-scale grouping RFID system is characterized in that the large-scale grouping RFID system comprises a background server, a reading head and n known tags which are divided into I small groups, and each small group of tags comprises n tagsiA label, wherein miEach label is a lost label, i is more than or equal to 1 and less than or equal to l, and each label has a unique 96-bit ID; the query method comprises the following steps:
when any query of the kth round is finished, and k is more than or equal to 1 and less than or equal to w, the reading head calculates the estimation values of all groups of lost tags under the estimation of the current round, and calculates the expected values and the variance of the estimation values; the specific process comprises the following steps:
HZE the process is: at the initial moment of any kth wheel, the reading head sets the frame length fkIs composed of
Generating a random number seed; the reading head predicts the state of each time slot of the current frame to obtain an expected frame based on the frame length, the random number seeds and the ID of each label; if the prediction state of the current time slot is only selected by the labels in the same group, the time slot is called as an isomorphic time slot, and if the prediction state of the current time slot is not selected by the labels, the time slot is called as an empty time slot; the reading head broadcasts the frame length and the random number seed, and each tag receives the frame length and the random number seed information to calculate the number of the response time slot of the tag; the reading head executes each time slot of the expected frame one by one, and each label returns 1 bit of response information in the label response time slot; the reading head detects the actual state of each time slot to obtain an execution frame; read head statistics CiThe time slots selected by the tags in the tag group correspond to the number of time slots which are 'isomorphic time slots' in the expected frame and 'null time slots' in the executed frame, and are used
Indicating that the lost label estimation value of each label subgroup under the k-th estimation
Comprises the following steps:
further calculating the estimated value of the lost label
The expected value and variance of (c) are:
in the formula (I), the compound is shown in the specification,
estimate value for lost tag
The expected value of (c) is,
estimate value for lost tag
Variance of (m)iIs CiThe number of missing tags in the tag subgroup;
after the estimation process of the k-th round of query is finished, the reading head calculates the mean value of each group of lost label estimation values obtained under each round of estimation in the previous k rounds as each group of lost label estimation values when the current round of estimation is finished, and calculates the expected value and the variance of the estimation values;
after the w-th round of query is finished, classifying the tag groups by the reading head according to whether the estimated value of the number of the lost tags of each group is greater than a given tag number threshold T, verifying the accuracy of the query result of the w round, and finishing the query process and obtaining a tag group series gamma' if the query accuracy meets the required reliability requirement; otherwise, the query process is continued until the query accuracy reaches the required credibility requirement.
2. The method for missing tag iceberg query of large-scale grouping RFID system based on HZE as claimed in claim 1, wherein in step (two), after the estimation process of the k-th round of query is finished, the reading head averages the small groups of missing tag estimation values obtained under each estimation in the previous k-th round by formula (4), and the expression of formula (4) is:
in the formula (I), the compound is shown in the specification,
the mean value of each group lost label estimated value obtained under each estimation in the front k rounds is obtained;
calculating to obtain the mean value of the estimated values of the lost labels of each group
As the estimated value of each group lost label when the current wheel is finished, and further calculating the average value
The expected value and variance of (c) are:
in the formula (I), the compound is shown in the specification,
mean values of missing label estimates for each subgroup
The expected value of (c) is,
mean values of missing label estimates for each subgroup
The variance of (c).
3. The method for missing tag iceberg query of large-scale packet RFID system based on HZE, wherein in step (three), after the w-th round of query is finished, the reader head classifies the tag subgroups, and if the estimated number of missing tags of a certain subgroup is greater than the given tag number threshold T, the subgroup is divided into tag group series Γ.
4. The method for missing tag iceberg query of large-scale grouping RFID system based on HZE as claimed in claim 3, wherein in step (three), after the w round of query is finished, the reading head verifies the accuracy of the query result, i.e. the reading head judges whether the query result satisfies the following two conditions under the condition of given tag number threshold T, error threshold ε,0< ε ≦ 1 and required reliability δ,0 ≦ δ < 1:
if the query result simultaneously meets the two limiting conditions, the query accuracy meets the required credibility requirement, the query process is ended, and the tag group gamma' is obtained; if the query result does not satisfy the two limiting conditions at the same time, which indicates that the query accuracy does not meet the required reliability requirement, the reading head continues the query process round by round until the required reliability requirement is satisfied.
5. The method for missing tag iceberg query of large scale grouping RFID system based on HZE as claimed in claim 4, wherein the reading head performs accurate query resultWhen verifying, if CiThe tag subgroup belongs to the tag group series Γ, and the inequality
If true, Pr [ m ] is obtainedi≥(1-ε)T]Delta is more than or equal to; if CiThe tag subgroup does not belong to the tag group series Γ, and the inequality
If true, Pr [ m ] is obtainedi≤(1+ε)T]Delta is more than or equal to; wherein phi (·) is a standard normal distribution function, phi-1(. cndot.) is the inverse of the standard normal distribution function.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1934575A (en) * | 2004-02-06 | 2007-03-21 | Zih公司 | Rfid group selection method |
| CN103544459A (en) * | 2013-10-25 | 2014-01-29 | 上海交通大学 | Method and system for estimation of sum of radio frequency identification tags |
| CN103761494A (en) * | 2014-01-10 | 2014-04-30 | 清华大学 | Method and system for identifying lost tag of RFID system |
| CN106096466A (en) * | 2015-04-27 | 2016-11-09 | 张大强 | Large-scale wireless radio system is lost the method for quick of label |
| CN107644185A (en) * | 2017-10-23 | 2018-01-30 | 中国石油大学(华东) | The recognition methods of loss crucial label of the anonymous radio-frequency recognition system based on vector |
-
2018
- 2018-09-28 CN CN201811140730.6A patent/CN109117687B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1934575A (en) * | 2004-02-06 | 2007-03-21 | Zih公司 | Rfid group selection method |
| CN103544459A (en) * | 2013-10-25 | 2014-01-29 | 上海交通大学 | Method and system for estimation of sum of radio frequency identification tags |
| CN103761494A (en) * | 2014-01-10 | 2014-04-30 | 清华大学 | Method and system for identifying lost tag of RFID system |
| CN106096466A (en) * | 2015-04-27 | 2016-11-09 | 张大强 | Large-scale wireless radio system is lost the method for quick of label |
| CN107644185A (en) * | 2017-10-23 | 2018-01-30 | 中国石油大学(华东) | The recognition methods of loss crucial label of the anonymous radio-frequency recognition system based on vector |
Non-Patent Citations (2)
| Title |
|---|
| Cardinality Estimation for Large-Scale RFID Systems;Chen Qian,et al.;《IEEE Transaction on Parallel and Distributed Systems》;20110930;第22卷(第9期);第1441-1454页 * |
| Efficient Unknown Tag Identification Protocols in large-scale RFID Systems;Xiulong Liu，et al.;《IEEE Transaction on Parallel and Distributed Systems》;20141231;第25卷(第12期);第3145-3155页 * |
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