CN103929499A - Internet of things heterogeneous identification recognition method and system - Google Patents
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Abstract
The invention relates to an internet of things heterogeneous identification recognition method and system. The method includes the steps that the characteristics of internet of things identification are collected and described through an individual character rule, a length rule and a function rule, and then corresponding rule information is acquired and stored, wherein the individual character rule describes positions and the value range of bytes in the identification, the length rule describes the length of the identification, and the function rule describes the relations between the bytes in the identification; rule matching is conducted on an internet of things identification character string recorded by users according to the stored rule information, the identification type to which the recorded identification character string belongs is acquired, and an identification recognition result is output. The system comprises a rule extraction module, an identification rule storage module, an identification input module, an identification recognition algorithm module and an identification recognition result output module. Storage efficiency of the internet of things heterogeneous identification can be improved, the recognition accuracy of the internet of things heterogeneous identification can be improved, the recognition speed of the internet of things heterogeneous identification can be increased, and the internet of things application interconnection and interworking requirement can be met.
Description
Technical field
The invention belongs to information technology, technology of Internet of things field, be specifically related to one Internet of Things isomery index identification method and system fast and accurately.
Background technology
In recent years, the correlation technique of Internet of Things, application and industry development have become the strategic high ground of our times new round economy and development in science and technology.Internet of Things has been broken through interpersonal communication pattern, introduces perception and control to physical world, makes communication between people and thing, thing and thing become possibility with cooperating.To realize above communication and basis and the prerequisite applied as being used for identifying with the Internet of Things mark of distinguishing different physics and logic entity and information resources.At present, Internet of Things mark research has become one of international and domestic study hotspot, and each field has occurred that maturity differs, range of application multiple Indicator system not etc., has also presented the state that numerous identification technologies coexist and apply present situation complexity.
At present, all kinds of related application on market have very strong demand to the parsing of Internet of Things mark.Some similar micro-letters, I see etc., and emphasis application is numerous and confused releases the service of scanning Quick Response Code.Experience for promoting user, this class is applied all requirements can identify Quick Response Code mark rapidly, so market is in the urgent need to a kind of technology of quick identification isomeric compound networking mark.Certainly, Internet of Things mark not only comprises Quick Response Code, has also comprised all kinds of isomery marks such as one dimension code, RFID, be all faced with same problem about the application of these isomery marks: how to identify rapidly this class isomery mark?
For advancing interconnecting between the Internet of Things application that uses different identification, in the urgent need to a kind of algorithm that can identify all kinds of isomeric compound networking marks, to connect isolated Internet of Things application isolated island, promote the further fusion development of Internet of Things.In the Internet of Things world, the form of Internet of Things mark is various, omnifarious.The length of Internet of Things mark is not from several to hundreds of positions etc.; The span of Internet of Things mark is also not quite similar, and what have is made up of numeral, and what have is made up of letter; Even the Internet of Things being made up of numeral identifies, its system adopting is also mutual difference, has plenty of hexadecimally, has plenty of metricly, has plenty of binary.In addition, in an Internet of Things mark, also may comprise complicated logical relation, such as checking algorithm etc.Thereby how identifying given arbitrary Internet of Things mark is current a difficult problem, exploitation Internet of Things mark related algorithm is conducive to promote the further fusion development of Internet of Things industry.
Summary of the invention
The invention provides a kind of method of identifying all kinds of isomeric compound networking marks, can improve accuracy and the recognition speed of the identification of Internet of Things isomery mark, meet Internet of Things and apply the needs that interconnect.
For achieving the above object, the technical solution used in the present invention is as follows:
A kind of Internet of Things isomery index identification method, its step comprises:
1) gather the feature that all kinds of Internet of Things identify, use individual character rule, length rule and functional rule to describe identification characteristics, obtain corresponding Rule Information storage, wherein position and the span of byte in individual character rule description mark, the length of length rule description mark, functional rule is described the relation between byte in mark;
2) according to the Rule Information of the Internet of Things identification characteristics of storage, the Internet of Things identification strings of user's typing is carried out to rule match, obtain the affiliated marking type of identification strings of typing, and output identification recognition result.
Further, described individual character rule adopts data structure [Index, Bitmap] to describe, and wherein, Index is index, is used to refer to the position of the corresponding byte of individual character rule in mark; Bitmap is the data structure of 8 bytes, is used for describing the span of this byte.The span of described byte is generally numeral, upper and lower case letter.
Further, described functional rule by reference other algorithm is described certain relation, and its describing mode comprises three parts: algorithm title, algorithm index list and algorithmic descriptions.
Further, user adopts one or more typing Internet of Things marks in following manner: the input of Web interface, smart mobile phone APP typing, Quick Response Code scanning record, one dimension code scanning record, RFID scanning record.
Adopt an Internet of Things isomery mark recognition system for said method,
Rule Extraction module, for using individual character rule, length rule and functional rule to describe the feature of Internet of Things mark, obtains corresponding Rule Information;
Mark rule memory module, connects described Rule Extraction module, for storing the Rule Information of identification characteristics of acquisition;
Mark input module, for typing Internet of Things identification strings to be identified;
Mark recognizer module, connect described mark rule memory module and described mark input module, for according to the Rule Information of the Internet of Things identification characteristics of storage, the Internet of Things identification strings of user's typing is carried out to rule match, obtain the affiliated marking type of identification strings of typing;
Mark recognition result output module, connects described mark recognizer module, for output identification recognition result.
Compared with prior art, beneficial effect of the present invention is as follows:
1) store based on BITMAP mechanism the feature that Internet of Things isomery identifies, promoted storage efficiency; Can all kinds of different Internet of Things of identification mark, thus lay the foundation for Internet of Things identification (RNC-ID) analytic.
2) recognizate networking identifies fast, by rule is carried out to weight sequence, is conducive to arrange fast the mark that input of character string can not belong to, thereby reaches the object of quick identification.
Brief description of the drawings
Fig. 1 is the Organization Chart of Internet of Things isomery mark mark recognition system of the present invention.
Fig. 2 is the basic structure schematic diagram of Internet of Things mark of the present invention.
Embodiment
Below by specific embodiments and the drawings, the present invention will be further described.
1. Internet of Things mark recognition system block diagram
The system framework figure of Internet of Things mark identification as shown in Figure 1.
In the present invention, the recognizer identifying for Internet of Things is based on Internet of Things identification characteristics.So, the present invention first gather the feature of all kinds of Internet of Things mark and by these characteristic storage in feature database.Describe identification characteristics by three kinds of rules in the present invention, these three kinds of rules comprise: length rule, byte rule and functional rule.Based on these three kinds of rules, Internet of Things mark received text is processed, obtained corresponding Rule Information, and store the Rule Information of collection into mark rule memory module, call for mark recognizer.
User can be by mark input module to system typing Internet of Things mark, and mark input module is supported all kinds of typing modes, for example: the input of web interface, smart mobile phone APP typing, Quick Response Code, one dimension code scanning record, RFID scanning record etc.
Mark recognizer module receives mark typing module and passes after the identification strings of coming, call the rule of storing in mark rule memory module, carry out rule match, judge the affiliated marking type of this typing identification strings, and result is presented by mark recognition result output module.
Mark recognition result output module shows that the approach of recognition result is varied, can export by ordinary desktop computer interface, also can export by smart mobile phone interface.
2. Internet of Things mark rule extracts
The structure of Internet of Things mark varies, by analysis, the present invention has designed a kind of describing method of describing all kinds of isomeric compound networking marks, the method service regeulations are described identification characteristics, comprise altogether three kinds of rules, be specially: individual character rule (also claiming byte rule), length rule, functional rule.First specifically introduce regular definition and grammer below, and then introduce corresponding isomery mark recognizer.
1) as shown in Figure 2, a mark is generally made up of several bytes the structure of mark, and each byte can represent with corresponding index.And rule can be used to describe the feature that a kind of all or part of byte of mark has aspect value.For example, a kind of length of mark (such as 20) can be a kind of rule; The span of the 1st of mark is numeral and a lowercase, and this is also a kind of rule.
2) at present rule is roughly divided into following a few class with its characteristic: individual character rule, length rule, functional rule.
A) individual character rule is mainly used to the span of some bytes of describing a kind of mark.The available following data structure of individual character rule is described: [Index, Bitmap].Wherein, " Index " is index (2 byte integer), is used to refer to the position of the corresponding byte of individual character rule in mark.Bitmap is the data structure (can be the double type variable of array or 8 bytes) of 8 bytes, and Bitmap is used for describing the span (being generally numeral, upper and lower case letter) of this byte.Totally 64 of Bitmap, and upper and lower case letter and numeral one have 62 kinds of values.Therefore can describe span with Bitmap.From left to right representative digit, lowercase, capitalization successively of Bitmap.The, the 1st---10 bit representation numerals; The 11st---36 bit representation lowercases; The 37th---62 bit representation capitalizations.63,64 of Bitmap is to retain position, wouldn't use.
B) length rule: data available structure [Len1, Len2 ..., LenN] represent.If length is-1, its not limit for length is described, length is uncertain.
C) functional rule: it is mainly used to describe the complex relationship existing between multiple bytes in an Internet of Things mark.For example, a kind of one or more adjacent byte of mark may, not by explicit definition, need just can obtain (for example checking algorithm) by corresponding algorithm, and this situation can be described with functional rule.Functional rule mainly by reference other algorithm (or function) certain relation is described.If quoted other algorithm, should this functional rule be described by mode below, this describing mode comprises 3 parts: algorithm title; Algorithm index list; Algorithmic descriptions.Now be described below respectively:
A) algorithm title
Its format is as follows: "(# ALGNAME = XXXXX?)".Wherein character "? # " shows that this is annotation." ALGNAME " is keyword, can not change, and shows that this part will link other algorithm; The name that " XXXXX " is the algorithm that is linked; "=" is used for separating these two parts, is also keyword, can not change;
B) algorithm index list
Its format is as follows: "(# INDEX = XXXXXX?)".Wherein character "? # " shows that this is annotation." INDEX " is keyword, can not change, and shows that this part is the parameter list of algorithm; " XXXXXX " is the list of corresponding input index, uses CSV between index; "=" is used for separating these two parts, is also keyword, can not change;
Attention: index is since 0 open numbering instead of from 1.
C) algorithmic descriptions
Its format is as follows: "(# NOTE = XXXX?)".Where the characters "(? #)" Indicates that this is a comment." NOTE " is keyword, can not change, and shows that the algorithm to linked carries out some explanations by this part; " XXXX " content for explaining; "=" is used for separating these two parts, is also keyword, can not change;
This part content is optional, but for algorithm is elaborated, this part is not ignored in suggestion in writing process.
3. Internet of Things mark recognizer
Generally, recognizer adopts " eliminating " strategy, the concrete identification strings of input is compared from different rules, thereby constantly dwindle comparison range, and finally obtain the identifier type under this concrete identification strings.The concrete false code of algorithm is as follows:
1). access identities rale store module, constructs following data structure:
A) all regular collection: RULE_SET;
B) all set of identifiers: ID_SET;
C) mark-regular mapping table, this data structure is a Hash table, key is mark, is worth the set of the strictly all rules for belonging to certain mark;
D) rule-mark mapping table, this data structure is also a Hash table, key is rule, is worth the set of all marks for meeting this rule.
2). establishing rule set to be got rid of is rmvRuleSet, and its initial value is made as RULE_SET (being all regular collections).If identifier to be got rid of integrates as rmvIDSet, and its initial value is ID_SET (being all set of identifiers).
3) .while (rmvRuleSet is not empty, and rmvIDSet is not empty)
4). according to hereinafter described rule compositor algorithm, the rule in rmvRuleSet is carried out to descending sort according to regular weight;
5). the rule of selecting weight maximum (is designated as rl
i), and it is mated with the identification strings of input;
6) if. the match is successful, and upgrading rmvRuleSet is rmvRuleSet-rl
i, then forward 8 to);
7) if. mate unsuccessfully, also search rl
irule-mark mapping table, i.e. dictionary rl
i(1≤i≤N): { id
i1, id
i2, id
i3..., idi
j... }, and rmvIDSet is updated to: rmvIDSet-{id
i1, id
i2, id
i3..., idi
j... }, then forward 8 to);
8) after .rmvIDSet is updated, search successively the mark that in this set, each identifier is corresponding-regular mapping table, obtain the rule set that each identifier is corresponding, obtain the union of these rule sets, and upgrade rmvRuleSet by this union, and from rmvRuleSet, deduct rl
i, then forward 3 to).
4. rule compositor algorithm
1. the number of " rule " is very large, and rationally the execution sequence of definite different " rule " is significant for the complexity that reduces regular matching times final minimizing algorithm.For one " rule ", definition:
P: in a rule match process, be somebody's turn to do " rule " probability that the match is successful, 0<p<1;
Q: in a rule match process, should " rule " mate unsuccessful probability, 0<q<1; Obviously p+q=1; f
i∈ F={f
1, f
2, f
3..., f
i..., f
m, wherein f
ifor the prior probability of mark i, prior probability can be understood as to the probability that occurs of mark i in all marks, or when being understood as an identification strings and arriving mark input module, it may be the probability of mark i.
The value of 2.p is relevant with two factors:
In all identifiers, be applicable to the shared ratio of identifier of this " rule ";
Being suitable in the identifier of this " rule ", the probability (prior probability) that these identifiers occur.
3.p computational methods
First introduce a binary variable x
i, wherein
,
wherein f
i∈ F={f
1, f
2, f
3..., f
i..., f
m, i.e. f
ifor prior probability.
4. the computational methods of " rule " weight
can regard the matching problem of " rule " as information source problem, two kinds of signals of information source output: 1 (the match is successful) and 0 (mating unsuccessful).Wherein, be that 1 probability is p; Be that 0 probability is q.W is the amount of information of this information source, and the value of w is larger, illustrates that the amount of information that the matching process of this " rule " comprises is larger, should preferentially carry out this " rule ".And in the time of p=q=0.5, w gets maximum.
5. " rule " sort method
Calculate successively the weight of each " rule ", then sort according to this weight, preferential great " rule " of right of execution.
A concrete application example is provided below.
If the length of a kind of mark (calling " ID1 " in the following text) is 3, its length rule can be used [3] to represent, its first byte meets byte rule, and its span is numeral, upper and lower case letter, the byte rule available [1 of its first byte, 255, 255, 255, 255, 255, 255, 255, 252] represent, wherein first byte represents that index is 1, the data structure of 8 bytes next represents the span of this byte, because its span is numeral, upper and lower case letter, so except latter two bit of the 8th byte gets 0, in these 8 bytes, other bit gets 1, so the ASCII character of these 8 bytes is respectively 255, 255, 255, 255, 255, 255, 255, 252, what its 2nd, 3 byte represented is month, obviously, 2, between 3 bytes, exist incidence relation, can not represent by byte rule simply, need this feature be described with functional rule, its Function feature can be described as: (? #ALGNAME=Month) (? #INDEX=2,3) (? the function of #NOTE=function is whether the 2nd, 3 bytes that judge identification strings have month feature).
If the length of the second mark (calling " ID2 " in the following text) is 2, its length rule can be used [2] to represent; Its first byte meets byte rule, and its span be numeral 1,3,5,7,9, b, c, h, k, p, z, A, H, K, R, Y, U, the byte rule of its first byte available [1,170,26,18,2,24,72,32,17] represents; Its 2nd byte also meets byte rule, and its span is alphabetical a～z, and the byte rule of its second byte available [2,0,252,255,255,15,0,0,0] represents.
If the length of the third mark (calling " ID3 " in the following text) is 1, its length rule can be used [1] to represent; Its first byte meets byte rule, and its span be numeral 1,3,5,7,9, b, c, h, k, p, z, A, H, K, R, Y, U, the byte rule of its first byte available [1,170,26,18,2,24,72,32,17] represents.
Now, for these three marks (being ID1, ID2, ID3), the rule extracting is as follows:
ID1: length rule: [3]; Byte rule: [1,255,255,255,255,255,255,255,252]; Functional rule: (? #ALGNAME=Month) (? #INDEX=2,3) (? the function of #NOTE=function is whether the 2nd, 3 bytes that judge identification strings have month feature).
ID2: length rule: [2]; Byte rule: [1,170,26,18,2,24,72,32,17]; [2,0,252,255,255,15,0,0,0].
ID3: length rule: [1]; Byte rule: [1,170,26,18,2,24,72,32,17].
The prior probability of supposing ID1, ID2 and ID3 is respectively 0.3,0.5,0.2, foundation
p,
qand the result of the computational methods of regular weight w shown in can table 1.
The result of calculation of table 1.p, q and regular weight w
Suppose that mark input module receives character string for " 1a ", according to upper table, find the weight maximum of " length rule: [2] ", so first judge to character string whether meet " length rule: [2] ", through coupling, this character string meets this rule; Then find " byte rule: [2,0,252,255,255,15,0,0,0]." weight maximum, through coupling, this character string meets this rule, input character string must belong to ID2.Then,, according to same flow process, by this character string and regular the mating of being left, finally find that this input of character string belongs to ID2 in order.
Above embodiment is only in order to technical scheme of the present invention to be described but not be limited; those of ordinary skill in the art can modify or be equal to replacement technical scheme of the present invention; and not departing from the spirit and scope of the present invention, protection scope of the present invention should be as the criterion with described in claim.
Claims (10)
1. an Internet of Things isomery index identification method, its step comprises:
1) gather the feature that all kinds of Internet of Things identify, use individual character rule, length rule and functional rule to describe identification characteristics, obtain corresponding Rule Information storage, wherein position and the span of byte in individual character rule description mark, the length of length rule description mark, functional rule is described the relation between byte in mark;
2) according to the Rule Information of the Internet of Things identification characteristics of storage, the Internet of Things identification strings of user's typing is carried out to rule match, obtain the affiliated marking type of identification strings of typing, and output identification recognition result.
2. the method for claim 1, is characterized in that: described individual character rule adopts data structure [Index, Bitmap] to describe, and wherein, Index is index, is used to refer to the position of the corresponding byte of individual character rule in mark; Bitmap is the data structure of 8 bytes, is used for describing the span of this byte.
3. method as claimed in claim 2, is characterized in that: the span of described byte comprises numeral, upper and lower case letter.
4. the method for claim 1, is characterized in that, described functional rule by reference other algorithm is described certain relation, and its describing mode comprises three parts: algorithm title, algorithm index list and algorithmic descriptions.
5. method as claimed in claim 4, is characterized in that, the form of described algorithm title is: (? #ALGNAME=XXXXX), wherein character "? # " " ALGNAME " is keyword, can not change, and shows that this part will link other algorithm; The name that " XXXXX " is the algorithm that is linked; "=" is used for separating these two parts, is also keyword, can not change.
6. method as claimed in claim 4, is characterized in that, described algorithm index row tableau format is: (? #INDEX=XXXXXX), wherein character "? # " " INDEX " is keyword, can not change, and shows that this part is the parameter list of algorithm; " XXXXXX " is the list of corresponding input index, uses CSV between index; "=" is used for separating these two parts, is also keyword, can not change.
7. the method for claim 1, is characterized in that: step 2) carry out rule match, the method that obtains the marking type under the identification strings of typing is:
2.1) construct following data structure according to the Rule Information of the Internet of Things identification characteristics of storage:
All regular collection: RULE_SET; All set of identifiers: ID_SET;
Mark-regular mapping table, is a Hash table, and key is mark, is worth the set of the strictly all rules for belonging to certain mark;
Rule-mark mapping table, is a Hash table, and key is rule, is worth the set of all marks for meeting this rule;
2.2) establishing rule set to be got rid of is rmvRuleSet, and its initial value is made as RULE_SET, i.e. all regular collections; If identifier to be got rid of integrates as rmvIDSet, and its initial value is ID_SET, i.e. all set of identifiers;
2.3) while (rmvRuleSet is not empty, and rmvIDSet is not empty)
2.4) rule in rmvRuleSet is carried out to descending sort according to regular weight;
2.5) select the rule of weight maximum, be designated as rl
i, and it is mated with the identification strings of input;
2.6), if the match is successful, upgrading rmvRuleSet is rmvRuleSet-rl
i, then forward step 2.8 to);
2.7) if mate unsuccessfully, also search rl
irule-mark mapping table, i.e. dictionary rl
i(1≤i≤N): { id
i1, id
i2, id
i3..., idi
j... }, and rmvIDSet is updated to: rmvIDSet-{id
i1, id
i2, id
i3..., idi
j... }, then forward step 2.8 to);
2.8) after rmvIDSet is updated, search successively the mark that in this set, each identifier is corresponding-regular mapping table, obtain the rule set that each identifier is corresponding, obtain the union of these rule sets, and upgrade rmvRuleSet by this union, and from rmvRuleSet, deduct rl
i, then forward step 2.3 to).
8. method as claimed in claim 7, is characterized in that step 2.4) adopt and carry out with the following method rule compositor:
2.4a) for a rule, definition:
P: in a rule match process, be somebody's turn to do " rule " probability that the match is successful, 0<p<1;
Q: in a rule match process, should " rule " mate unsuccessful probability, 0<q<1; Obviously p+q=1; f
s∈ F={f
1, f
2, f
3..., f
i..., f
m, wherein f
ifor the prior probability of mark i;
2.4b) value of p is relevant with two factors: in all identifiers, be applicable to the shared ratio of this regular identifier; Being suitable in this regular identifier, the probability that these identifiers occur, i.e. prior probability; The computational methods of p are as follows:
First introduce a binary variable x
i, wherein
,
wherein f
i∈ F={f
1, f
2, f
3..., f
i..., f
m, i.e. f
ifor prior probability;
2.4c) adopt following formula computation rule weight:
Regard information source problem as by regular matching problem, two kinds of signals of information source output: 1, for the match is successful; 0, unsuccessful for mating); Wherein, be that 1 probability is p, be 0 probability is q, w is the amount of information of this information source, and the value of w is larger, and the amount of information that this regular matching process comprises is larger, should preferentially carry out this rule;
2.4d) calculate successively each regular weight, then sort according to this weight, the preferential great rule of right of execution.
9. the method for claim 1, is characterized in that, user adopts one or more typing Internet of Things marks in following manner: the input of Web interface, smart mobile phone APP typing, Quick Response Code scanning record, one dimension code scanning record, RFID scanning record.
10. an Internet of Things isomery mark recognition system that adopts method described in claim 1, is characterized in that, comprising:
Rule Extraction module, for using individual character rule, length rule and functional rule to describe the feature of Internet of Things mark, obtains corresponding Rule Information;
Mark rule memory module, connects described Rule Extraction module, for storing the Rule Information of identification characteristics of acquisition;
Mark input module, for typing Internet of Things identification strings to be identified;
Mark recognizer module, connect described mark rule memory module and described mark input module, for according to the Rule Information of the Internet of Things identification characteristics of storage, the Internet of Things identification strings of user's typing is carried out to rule match, obtain the affiliated marking type of identification strings of typing;
Mark recognition result output module, connects described mark recognizer module, for output identification recognition result.
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| 敬洁: "支持多标准的物联网编码解析系统的研究", 《中国优秀硕士学位论文电子期刊》 * |
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| CN105184734A (en) * | 2015-10-15 | 2015-12-23 | 中国科学院计算机网络信息中心 | IOT (Internet of Things) heterogeneous identification generation method based on technology of digital signal processing |
| CN105184734B (en) * | 2015-10-15 | 2018-08-21 | 中国科学院计算机网络信息中心 | Internet of Things isomery mark generating method based on Digital Signal Processing |
| CN105654112A (en) * | 2015-12-22 | 2016-06-08 | 中国互联网络信息中心 | High-efficiency internet of things identifier code division method |
| CN105654112B (en) * | 2015-12-22 | 2019-03-22 | 中国互联网络信息中心 | A kind of efficient Internet of Things identification code division methods |
| CN107592306A (en) * | 2017-09-08 | 2018-01-16 | 四川省绵阳太古软件有限公司 | Information security monitoring management method and system based on environment of internet of things big data |
| WO2020140937A1 (en) * | 2019-01-02 | 2020-07-09 | 中国移动通信有限公司研究院 | Internet of things recognition identifier method and apparatus, and terminal device |
| CN112260872A (en) * | 2020-10-22 | 2021-01-22 | 北京理工大学 | Identification heterogeneous recognition method and system based on character string matching |
| CN112260872B (en) * | 2020-10-22 | 2022-03-04 | 北京理工大学 | Identification heterogeneous recognition method and system based on character string matching |
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