CN110516923A - A kind of car networking synthetical information evaluating method - Google Patents
A kind of car networking synthetical information evaluating method Download PDFInfo
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Abstract
The present invention provides a kind of car networking synthetical information evaluating methods, and first all information in current car networking are carried out with unified data characteristics parameter characterization, quantify each parameter attribute weight shared in scaling information value；Estimation calculating is carried out by property parameters and information dimension of the weight to every information, obtains each information based on the information value size under specified services parameter；Then information qualified after processing is worth the big minispread of weight according to it to determine information transmission order.The present invention is based on information value, construct car networking information value comprehensive evaluation model, unified data characteristics parameter characterization is carried out to bulk information, quantify (data) the feature weight shared in scaling information value, and is selected according to information of the threshold value of information value to transmission.
Description
Technical field
The present invention relates to car networking fields, and in particular to one kind can preferentially be passed according to the value of information in car networking
Send the car networking synthetical information evaluating method of high price value information.
Background technique
Application in actual traffic shows that car networking is a kind of special mobile ad hoc network, has high-speed mobility, network
Many parts can be continually divided into.Widely distributed a variety of different types of data informations in car networking, such as: text letter
Breath, image information, audio-frequency information, video information etc., vehicle node is probably because the influence of environmental factor can not be with
Neighbor node communicates and becomes an isolated child node, and the connectivity of network is frequently destroyed, and traditional Routing Protocol is difficult
The quick change in topology of car networking is adapted to, it is lower using rear data transmission efficiency.In addition, its significance level of different data and multiple
Miscellaneous degree is not quite similar.The significance level and complexity of information have codetermined the value of information.In terms of importance angle, letter
Breath is more important, then is worth bigger；In terms of complexity angle, information change is more violent, and emergency event is more, then is worth bigger.
Traditional transparent transmission does not account for the value of information to be transmitted, and the priceless value information of transmission causes system resource
Significant wastage, therefore, how between vehicle and vehicle, efficiently and reliably to be transmitted between vehicle and trackside website be vehicle
Can networking effectively improve the critical issue of traffic safety and traffic administration ability.
Summary of the invention
The purpose invented herein, which is to provide one kind, preferentially to transmit high value according to the value of information in car networking
The car networking synthetical information evaluating method of information.
Specifically, the present invention provides a kind of car networking synthetical information evaluating method, includes the following steps:
Step 100 carries out unified data characteristics parameter characterization to all information in current car networking, and it is special to quantify each parameter
Levy the weight shared in scaling information value；
Step 200 carries out estimation calculating by property parameters and information dimension of the weight to every information, obtains each information
Based on the information value size under specified services parameter；
Step 300, the threshold value for setting filter information value, abandon the information of not up to threshold value, and qualification is believed
Breath, which saves to data to send, to be collected；
Step 400, the information for sending concentration to data are analyzed, and exception information therein is cleaned, meanwhile, it is right
Empty information and missing information carry out information and fill a vacancy operation, and the information that can not be handled is marked；
Step 500, then by information qualified after processing according to its be worth the big minispread of weight with determine information pass
Send sequence.
In an embodiment of the invention, the weight calculation mode in the step 100 is as follows:
Step 111. determines all information with information content from a new perception period；
Step 112. utilizes the potential feature calculation of environmental information and the sensing region of selection most information content；
Step 113. obtains the detected value of each sensor in sensing region and forms set, according to any one sensor
Detected value and corresponding detection accuracy and bulk properties detected value obtain the entropy of the detected value；
Any one information can be obtained according to the errored message degree of sensor and the entropy of corresponding detected value in step 114.
Weight.
In an embodiment of the invention, in the step 111, determine that there is letter in the perception period new from one
The information mode of breath amount is as follows:
Wherein, SnFor the information content after determination, j is perception period, CjFor whole space time unit set, SjWhen to have perceived
Dummy cell set, and haveK is the information content quantity of selection, and Cn is all information content, Ω (Xs∪v；XCn\v) it is space-time
The space time unit Cn of unit S ∪ v mutual information between v.
In an embodiment of the invention, step 113 medium entropy to obtain process as follows:
If x1、x2…...xn, it is the detected value of sensor in sensing region, takes any n detected value composition set, d1,
d2... ... dnFor the precision of respective sensor, the overall attribute value that detects isIf m*n matrix, wherein xj is j-th
Attribute value, the then entropy of any detected value are as follows:
In an embodiment of the invention, the calculation formula of weight is as follows in the step 114:
Its k is constant, k=1/lnm, cjFor errored message degree, and cj=1-Ej, the entropy of detected value
WjFor the weight of j-th of information.
In an embodiment of the invention, in the step 200, the process for obtaining information value size is as follows:
Total number of events in step 211, a cycle determining first, using the probability that wherein everything part occurs as the thing
The characteristic parameter value of part, determines the information content of everything part；
Step 212, the variation probability that current event is determined according to the variation speed of information content, recycle the weight of event i.e.
The information value calculation formula of current information can be obtained.
In an embodiment of the invention, in the step 211, the mode for obtaining the information content is as follows:
The event space for defining information source first is S={ S1,...Si,...,SM, wherein the total number of event is M, Si=
{xi,x2,...xiIndicate an event, xi,x2,...xiThe value of each characteristic parameter is respectively indicated, then event SiInformation content is；
Ii=-logpi
Wherein, piThe probability occurred for event i.
In an embodiment of the invention, change the formula of probability in the step 212 are as follows:
pij=Γ (pi,t)
If information matrix is ∏, then γ is ΠiCharacteristic value (γ1, γ2... γn) constitute diagonal matrix, t be perception
Period.
In an embodiment of the invention, the calculation formula of the information value H in the step 212 are as follows:
Wherein, pijFor the probability of event change, wiFor the significance level weight of event, M is the total number of event.
In an embodiment of the invention, in the step 500, the value weight size calculation formula of data information
It is as follows:
wi=f (αi,βi)
Wherein, the threshold value of information value size isIt is information value weight ΩiWith event SiFeature ginseng
Amount, if information matrix is Πi, γ is ΠiCharacteristic value (γ1, γ2... γn) constitute diagonal matrix, η is each characteristic value pair
Feature vector (the η answered1, η2... ηn) composition matrix, target is to SiDesirability βiIt indicates,It chooses
Corresponding feature vector (the η of preceding i characteristic value1, η2... ηn) composition characteristic matrix αi, and f indicates wiIt is about αiAnd βiLetter
Number.
The present invention constructs car networking information value comprehensive evaluation model based on information value, to bulk information into
The unified data characteristics parameter characterization of row, quantization (data) the feature weight shared in scaling information value, and foundation
The threshold value of information value selects the information of transmission, at (the meeting business demand) information for reaching threshold value
Reason, and the information of not up to threshold value (not meeting business demand) is then abandoned, and using the data transmission mechanism of communication for coordination, is mentioned
The utilization rate of high-transmission resource has been finally reached the purpose for promoting network overall transfer performance.
Detailed description of the invention
Fig. 1 is the evaluation method flow diagram of one embodiment of the present invention；
Fig. 2 is the information value self-adaptive estimation process of one embodiment of the present invention.
Specific embodiment
The present invention for network environment in car networking dynamic is changeable, complicated variety of physical environment and data transmission sea
The features such as amount property and real-time, constructs the car networking synthetical information evaluating model based on information value, makes all kinds of letters in car networking
Breath value reaches balanced with transmission, plays important supporting role to promote traffic efficiency, safety etc..In addition, car networking network
State changes at random, in network entity have real-time dynamic reorganization characteristic, cause it is very high to networked-induced delay requirement, because
This, makes full use of limited resources, is task first to meet the preferential transmission of high price value information.
As shown in Figure 1, in an embodiment of the invention, a kind of car networking synthetical information evaluating method is provided, with
Preferential transmission is worth higher information within the limited time, and steps are as follows for execution:
Step 100 carries out unified data characteristics parameter characterization to all information in current car networking, and it is special to quantify each parameter
Levy the weight shared in scaling information value；
Information therein includes OBD data, nearby vehicle information, voice data and the video counts that car-mounted terminal acquires in real time
Traffic information etc. is set according to, road.
As shown in Fig. 2, the obtaining step of weight is as follows:
Step 111. determines all information with information content from a new perception period；
Method of determination is as follows:
Wherein, SnFor the information content after determination, j is perception period, CjFor whole space time unit set, SjWhen to have perceived
Dummy cell set, and haveK is the information content quantity of selection, and Cn is all information content, Ω (Xs∪v；XCn\v) it is space-time
The space time unit Cn of unit S ∪ v mutual information between v.
Step 112. utilizes the potential feature calculation of environmental data and the sensing region of selection most information content；
Step 113. obtains the detected value of each sensor in sensing region and forms set, according to any one sensor
Detected value and corresponding detection accuracy and bulk properties detected value obtain the entropy of the detected value；
Its medium entropy to obtain process as follows:
If x1、x2…...xn, it is the detected value of sensor in sensing region, takes any n detected value composition set, influence
The principal element of the data precision is sensor accuracy and error, and sensor accuracy is only related with sensor itself, and value is solid
Fixed, error is generally caused by environment and other equipment, main to consider history deviation and overall equal deviation.d1, d2... ... dnFor
The precision of respective sensor, the overall attribute value that detects areAssuming that m*n matrix, wherein xjFor j-th of attribute value, then
The entropy of any detected value are as follows:
Any one information can be obtained according to the errored message degree of sensor and the entropy of corresponding detected value in step 114.
Weight.
The calculation formula of weight is as follows:
Its k is constant, k=1/lnm, cjFor errored message degree, and cj=1-Ej, the entropy of detected value
WjFor the weight of j-th of information.
Step 200 carries out estimation calculating by property parameters and information dimension of the weight to every information, obtains each information
Based on the information value size under specified services parameter；
Wherein, the process for obtaining information value size is as follows:
Total number of events in step 211, a cycle determining first, using the probability that wherein everything part occurs as the thing
The characteristic parameter value of part, determines the information content of everything part；
The mode for obtaining information content is as follows:
The event space for defining information source first is S={ S1,...Si,...,SM, wherein the total number of event is M, Si=
{xi,x2,...xiIndicate an event, xi,x2,...xiThe value of each characteristic parameter is respectively indicated, then event SiInformation content is；
Ii=-log pi
Wherein, piThe probability occurred for event i.
Step 212, the variation probability that current event is determined according to the variation speed of information content, recycle the weight of event i.e.
The information value calculation formula of current information can be obtained.
Because the value of information is related with the significance level of information and complexity, complexity is again fast with the variation of information
It is slow related, so the formula of variation probability are as follows:
pij=Γ (pi,t)
If information matrix is Π, then γ is ΠiCharacteristic value (γ1, γ2... γn) constitute diagonal matrix, t be perception
Period.
The calculation formula of information value H are as follows:
Wherein, pijFor the probability of event change, wiFor the significance level weight of event, M is the total number of event.
In addition, it can include the step of being screened to the information after determining information value:
Characteristic parameter matrix and target first by everything part after probability extracts obtain the desirability of the event
To the weight expression formula for indicating information importance level；
Weight expression formula is substituted into value formula by information source again and obtains the initial information value of event, then output is extremely believed
Place, adjustment self-demand degree feeds back to information source again after initial information value is analyzed in the stay of two nights, and information source is based on the feedback signal
Optimize weight expression formula and be then forwarded to the stay of two nights after recalculating, the stay of two nights feeds back new desirability to information source, weight again after receiving
Multiple process, until obtaining the information value standard for meeting pre-provisioning request.
Step 300, the threshold value for setting filter information value, abandon the information of not up to threshold value, and qualification is believed
Breath, which saves to data to send, to be collected；
In this step, it is all to save all qualified data informations to data transmission collection, just jumps to
Step 400, preservation processing is not influenced on abandoning for the data information for not meeting threshold value during processing.
Step 400, the information for sending concentration to data are analyzed, and exception information therein is cleaned, meanwhile, it is right
Empty information and missing information carry out information and fill a vacancy operation, and the information that can not be handled is marked；
Here cleaning refers to that individual information deviates most of data, then is tentatively judged as it and obtains adopting for bias data
It is abnormal to collect node, which is excluded.
Step 500, then by information qualified after processing according to its be worth the big minispread of weight with determine information pass
Send sequence.
As shown in Fig. 2, the value weight size calculation formula of information is as follows:
wi=f (αi,βi)
Wherein, the threshold value of information value size isIt is information value weight ΩiWith event SiFeature ginseng
Amount, if information matrix is Πi, γ is ΠiCharacteristic value (γ1, γ2... γn) constitute diagonal matrix, η is each characteristic value pair
Feature vector (the η answered1, η2... ηn) composition matrix, target is to SiDesirability βiIt indicates,It chooses
Corresponding feature vector (the η of preceding i characteristic value1, η2... ηn) composition characteristic matrix αi, and f indicates wiIt is about αiAnd βiLetter
Number.
Present embodiment based on information value, constructs car networking information value overall merit mould by this upper step
Type can be realized effective transmission of emergency message.Unified data characteristics parameter characterization is carried out to bulk information, is quantified (data)
The feature weight shared in scaling information value, and selected according to information of the threshold value of information value to transmission
It selects, (the meeting business demand) information for reaching threshold value is handled, and not up to threshold value (not meeting business demand)
Information is then abandoned, and using the data transmission mechanism of communication for coordination, is improved the utilization rate of transfer resource, has been finally reached promotion net
The purpose of network overall transfer performance.
So far, although those skilled in the art will appreciate that present invention has been shown and described in detail herein multiple shows
Example property embodiment still without departing from the spirit and scope of the present invention, still can according to the present disclosure directly
Determine or deduce out many other variations or modifications consistent with the principles of the invention.Therefore, the scope of the present invention is understood that and recognizes
It is set to and covers all such other variations or modifications.
Claims (10)
1. a kind of car networking synthetical information evaluating method, which comprises the steps of:
Step 100 carries out unified data characteristics parameter characterization to all information in current car networking, quantifies each parameter attribute and exists
Shared weight when scaling information value；
Step 200 carries out estimation calculating by property parameters and information dimension of the weight to every information, show that each information is based on
Information value size under specified services parameter；
Step 300, the threshold value for setting filter information value, abandon the information of not up to threshold value, qualified information are protected
It deposits to data to send and collect；
Step 400, the information for sending concentration to data are analyzed, and exception information therein is cleaned, meanwhile, sky is believed
Breath and missing information carry out information and fill a vacancy operation, and the information that can not be handled is marked；
Step 500, then by information qualified after processing according to its be worth the big minispread of weight with determine information transmission it is suitable
Sequence.
2. car networking synthetical information evaluating method according to claim 1, which is characterized in that the power in the step 100
Re-computation mode is as follows:
Step 111. determines all information with information content from a new perception period；
Step 112. utilizes the potential feature calculation of environmental information and the sensing region of selection most information content；
Step 113. obtains the detected value of each sensor in sensing region and forms set, according to the detection of any one sensor
Value and corresponding detection accuracy and bulk properties detected value obtain the entropy of the detected value；
The weight of any one information can be obtained according to the errored message degree of sensor and the entropy of corresponding detected value for step 114..
3. car networking synthetical information evaluating method according to claim 2, which is characterized in that
In the step 111, determine have the information mode of information content as follows in the perception period new from one:
Wherein, SnFor the information content after determination, j is perception period, CjFor whole space time unit set, SjTo have perceived space-time list
Member set, and haveK is the information content quantity of selection, and Cn is all information content, Ω (Xs∪v；XCn\v) it is space-time unit
The space time unit Cn of S ∪ v mutual information between v.
4. car networking synthetical information evaluating method according to claim 3, which is characterized in that
Step 113 medium entropy to obtain process as follows:
If x1、x2…...xn, it is the detected value of sensor in sensing region, takes any n detected value composition set, d1,
d2... ... dnFor the precision of respective sensor, the overall attribute value that detects isIf m*n matrix, wherein xj is j-th
Attribute value, the then entropy of any detected value are as follows:
5. car networking synthetical information evaluating method according to claim 4, which is characterized in that
The calculation formula of weight is as follows in the step 114:
Its k is constant, k=1/lnm, cjFor errored message degree, and cj=1-Ej, the entropy of detected valueWjFor
The weight of j-th of information.
6. car networking synthetical information evaluating method according to claim 5, which is characterized in that
In the step 200, the process for obtaining information value size is as follows:
Total number of events in step 211, a cycle determining first, using the probability that wherein everything part occurs as the event
Characteristic parameter value determines the information content of everything part；
Step 212, the variation probability that current event is determined according to the variation speed of information content, recycle the weight of event that can obtain
To the information value calculation formula of current information.
7. car networking synthetical information evaluating method according to claim 6, which is characterized in that
In the step 211, the mode for obtaining the information content is as follows:
The event space for defining information source first is S={ S1,...Si,...,SM, wherein the total number of event is M, Si={ xi,
x2,...xiIndicate an event, xi,x2,...xiThe value of each characteristic parameter is respectively indicated, then event SiInformation content is；
Ii=-log pi
Wherein, piThe probability occurred for event i.
8. car networking synthetical information evaluating method according to claim 7, which is characterized in that
Change the formula of probability in the step 212 are as follows:
pij=Γ (pi,t)
If information matrix is Π, then Υ is ΠiCharacteristic value (Υ1, Υ2... Υn) constitute diagonal matrix, t be perception the period.
9. car networking synthetical information evaluating method according to claim 8, which is characterized in that
The calculation formula of information value H in the step 212 are as follows:
Wherein, pijFor the probability of event change, wiFor the significance level weight of event, M is the total number of event.
10. car networking synthetical information evaluating method according to claim 9, which is characterized in that
In the step 500, the value weight size calculation formula of data information is as follows:
wi=f (αi,βi)
Wherein, the threshold value of information value size isIt is information value weight ΩiWith event SiCharacteristic parameter, if
Information matrix is Πi, γ is ΠiCharacteristic value (Υ1, Υ2... Υn) constitute diagonal matrix, η is that each characteristic value is corresponding
Feature vector (η1, η2... ηn) composition matrix, target is to SiDesirability βiIt indicates,I before choosing
Corresponding feature vector (the η of characteristic value1, η2... ηn) composition characteristic matrix αi, and f indicates wiIt is about αiAnd βiFunction.
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