CN103957062A - Method for evaluating reputation of cognitive users in distributed cognitive radio network - Google Patents
Method for evaluating reputation of cognitive users in distributed cognitive radio network Download PDFInfo
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Abstract
The invention discloses a method for evaluating the reputation of cognitive users in a distributed cognitive radio network. The method mainly solves the problem of trust evaluation on the condition that the distributed cognitive radio network lacks a central control device. The method includes the steps of conducting initialization, selecting initial reputation evaluation user groups, screening the reputation evaluation user groups, judging whether the number of remaining reputation evaluation user groups is smaller than two, reselecting the reputation evaluation user groups, evaluating cooperation reputation and resource allocation of the cognitive users, evaluating communication reputation of the cognitive users, determining evaluation reputation values of reputation evaluation users and upgrading the reputation values. Through the method, the reputation of network behaviors of the cognitive users in the distributed cognitive radio network can be effectively evaluated, evaluation, calculation and upgrading of the reputation values of the cognitive users are achieved efficiently, the fairness of trust evaluation is ensured, and the network efficiency, the network security and the network robustness are improved.
Description
Technical field
The invention belongs to communication technical field, further relate to the method for assessing cognitive user credit worthiness in the distributed cognition radio network in cognitive radio networks technical field.The present invention can solve in distributed cognition radio network countless according to credit value in fusion center situation calculate, the fusion of perception data and the problem of spectrum allocation may, make that distributed cognition radio network operation is more efficient, fair, safety and stalwartness.
Background technology
In distributed cognition wireless network, lack central control equipment, therefore each cognitive user need to be born the double liability of cognitive user and center type cognition wireless network center base station.Cognitive user need to complete all operations of cognitive circulation, and due to single cognitive user ability limitation, this just needs to have worked in coordination with between cognitive user information fusion and decision-making, thereby cognitive circulation can be carried out smoothly.The disappearance of central control equipment has been brought as Control on Communication and has been disperseed, and is difficult to solve without policymaker's Coordination Decision, and the fairness between node, reliability, lack the trusted third party that carries out credit value calculating, the problem such as the unmanned calculating of credit value in faith mechanism.Therefore,, in order to solve the confidence level of distributed cognition radio network cognitive user, need Trust Management Mechanism reasonable in design.
The patent application " the cognitive radio networks layering cooperation frequency spectrum sensing method based on credit worthiness " (application number CN201310061675.2, publication No. CN103178910A) that Zhejiang University proposes discloses a kind of cognitive radio networks layering cooperation frequency spectrum sensing method based on credit worthiness.Concrete steps are: sensing node is carried out to sub-clustering, and node carries out local perception, and bunch head is entered a judgement based on a bunch interior nodes perception data, and fusion center is entered a judgement according to the court verdict of each bunch of head and credit worthiness, upgrade an each bunch of credit worthiness.This invention is by credit worthiness mechanism and adopt the network hierarchy cooperative sensing of clustering algorithm to combine, the impact bunch on system senses performance that degree of lowering credit is low, cognitive radio networks can significantly be reduced deeply decline user and attacked user the harmful effect that system is caused, can effectively reduce again system communication expense simultaneously.The weak point that the method exists is: although the method has been considered credit worthiness in cognitive radio networks in cooperative spectrum sensing, measures of reputation method is not described in detail, does not form complete credit management method; The frequency spectrum sensing method of the method application is only applicable to adopt the hierarchical network of clustering algorithm, in distributed cognition radio network, cannot be suitable for.In distributed cognition radio network, lack hub facility, the method cannot efficiently complete frequency spectrum perception; In addition, the method is not introduced any supervision mechanism yet, cannot ensure fairness and the robustness of measures of reputation and frequency spectrum perception in the time that network suffers malicious attack.
In the article " Towards Trust Establishment for Spectrum selection in Cognitive Radio Networks " that S.Parvin et al. delivers on 201024th IEEE International Conference on Advanced Information Networking and Applications, the method for evaluating trust based on behavior under a kind of center type cognitive radio networks framework is proposed, direct trust and the relation of indirectly trusting in this model, are considered, can detect easily the bad behavior of cognitive user in cognitive radio networks.Its trust management appraisal procedure is as follows: 1, cognitive user perception idle frequency spectrum information perception information is sent to cognitive user base station; 2, cognitive user base station obtains direct trust value and indirect trust values and integrates and obtains comprehensive trust value; 3, make frequency spectrum decision-making according to trust value.The weak point that the method exists is: first, the credit value of the method calculates, fusion and the spectrum allocation may of perception data all need to complete based on cognitive user base station, inapplicable in distributed cognition radio network; Secondly, the method does not have the fully feature in conjunction with cognition wireless network, and the factor of trust metrics is too single, does not consider the network behavior feature of the cognitive user in the ad hoc network situation in cognitive radio networks; Again, the method has only been considered the trust Generating Problems in trust management, and the concrete problem such as trust metrics and renewal does not relate to, and trust management framework is more rough, does not set forth whole trusting relationship according to the thought of cognition circulation.
Summary of the invention
The present invention is directed to above-mentioned the deficiencies in the prior art, propose to assess in a kind of distributed cognition radio network the method for cognitive user credit worthiness, complete in distributed cognition radio network countless according to fusion center, without in the situation under policymaker, for the cognitive user accurate fair calculating of carrying out credit value, the fusion that completes perception data, final reference trust value carry out fair allocat to frequency spectrum, can ensure fairness, fail safe and the robustness of cognitive radio networks operation.
To achieve these goals, the present invention includes following steps:
(1) initialization:
(1a) all empty the data record in the database of cognitive user, to each cognitive user in radio net, set unique identify label according to natural number order, the identify label of cognitive user is deposited in the network parameter data record of cognitive user;
(1b) initial cooperation credit value and the initial communication credit value of all cognitive user in the record of the database of cognitive user are set to 0.5, and initial assessment credit value is set to 0, and initial total credit value is set to 0.5;
(1c) cognitive user number in radio net is recorded in the network parameter data record of recognizing cognitive user, completes radio net initialization;
(1d) add the new cognitive user of network to carry out initialization to request.
(2) select initial credit assessment user group:
(2a) judge whether the data record that credit assessment user organizes is empty, if it is empty, execution step (2b), otherwise, execution step (3);
(2b) in [0.2,0.5] scope an optional arithmetic number as selection percentage;
(2c) cognitive user number and selection percentage in radio net are rounded after multiplying each other, obtain the number of users of credit assessment user group;
(2d) calculate according to the following formula, the selection factor of credit assessment user group:
Wherein, m represents the selection factor of credit assessment user group, and N represents cognitive user number in radio net, and J represents the number of users of credit assessment user group,
represent to round operation downwards;
(2e) from the database of cognitive user, select to meet the cognitive user of following formula identify label condition, the credit assessment user who charges to cognitive user organizes in data record:
I?mod?m＝1
Wherein, I represents the identify label of cognitive user, and m represents the selection factor of credit assessment user group, and mod represents modulo operation;
(2f) the credit assessment user of cognitive user is organized to the cognitive user recording in data record, as credit assessment user, using all credit assessment users as credit assessment user group.
(3) screening credit assessment user group:
(3a) check that successively credit assessment user organizes the credit value of all credit assessment users in data record, if total credit value of credit assessment user is less than 0.5, or credit assessment user's assessment credit value is less than 0, this credit assessment user is organized data record and is deleted from credit assessment user;
(3b) check that successively all credit assessment users that credit assessment user organizes in data record participate in credit assessment number of times continuously, exceed 5 times if credit assessment user participates in credit assessment continuously, this credit assessment user is organized data record and deleted from credit assessment user.
(4) judge whether the residue credit assessment number of users that credit assessment user organizes in data record is less than 2, if be less than 2, execution step (5), otherwise, execution step (6).
(5) reselect credit assessment user group:
(5a) current credit assessment user organizes positive integer of random issue, using this positive integer as the initial application number of cognitive user;
(5b) wish to add the cognitive user of credit assessment user group to send application information;
(5c) check whether the credit value of cognitive user that sends application information meets application condition, taking initial application number as starting point, with 1 for increasing progressively, to qualified cognitive user, set successively an application number, the application number of cognitive user is recorded in the data record of credit assessment user group;
(5d) calculate according to the following formula, the selection factor of credit assessment user group:
Wherein, m represents the selection factor of credit assessment user group, N
1cognitive user number in the data record of expression credit assessment user group, J represents the number of users of the described credit assessment user group of step (2c),
represent to round operation downwards;
(5e), from the data record of credit assessment user group, delete the cognitive user of discontented foot formula application numbers condition:
A?mod?m＝1
Wherein, A represents the application number of cognitive user, and m represents the selection factor of credit assessment user group, and mod represents modulo operation;
(5f) the credit assessment user of cognitive user is organized to the cognitive user recording in data record, as credit assessment user, using all credit assessment users as credit assessment user group.
(6) the cooperation prestige of assessment cognitive user:
(6a) cognitive user is carried out local frequency spectrum perception;
(6b) cognitive user is by local frequency spectrum perception information reporting to credit assessment user group, and the row vector element value of frequency spectrum perception information is 0 and 1, the frequency spectrum number that the number of the element of row vector is perception;
(6c) credit assessment user group is carried out perception information fusion to the frequency spectrum perception information of cognitive user, obtains final frequency spectrum perception information;
(6d) credit assessment user group is by final frequency spectrum perception information broadcasting to the cognitive user in radio net, and cognitive user enters final frequency spectrum perception information recording in the perception information data record of cognitive user;
(6e) credit assessment user to final frequency spectrum perception information whether identical judgement of frequency spectrum perception information with cognitive user, if identical, cognitive user frequency spectrum perception is correct, otherwise, cognitive user frequency spectrum perception mistake;
(6f) credit assessment user assesses the cooperation scoring of cognitive user, if cognitive user reports perception information, and cognitive user frequency spectrum perception is correct, and the cooperation of cognitive user scoring is 1; If cognitive user reports perception information, but cognitive user frequency spectrum perception mistake, the cooperation of cognitive user scoring is 0.5; If cognitive user does not report perception information, the cooperation of cognitive user scoring is 0.
(7) resource is distributed:
(7a) cognitive user is sent the frequency spectrum solicited message that comprises the bid of cognitive user to asked frequency spectrum;
(7b) according to the following formula, credit assessment user batch total is calculated the frequency spectrum competitiveness of the cognitive user of sending frequency spectrum solicited message, the frequency spectrum competitiveness of cognitive user is recorded in the frequency spectrum request msg record of cognitive user:
CP＝T*B
Wherein, CP represents the frequency spectrum competitiveness of cognitive user, and T is the total credit value of cognitive user, B by cognitive user to the bid of request frequency spectrum;
(7c) credit assessment user group by the frequency spectrum competitiveness of cognitive user according to sorting from big to small;
(7d) credit assessment user group is by from the frequency spectrum perception data record of cognitive user, the frequency spectrum that the final frequency spectrum perception information reading is 0, be recorded as idle frequency spectrum list, the frequency spectrum in idle frequency spectrum list is distributed to the descending cognitive user of competitiveness successively;
(7e) credit assessment user organizes and announces spectrum allocation may result.
(8) the communication prestige of assessment cognitive user:
(8a) cognitive user is carried out data communication according to spectrum allocation may result;
(8b) credit assessment user awareness is monitored the communication behavior of each cognitive user, determines the communication scoring to cognitive user according to communication quality judgment criteria.
(9) determine credit assessment user's assessment credit value:
(9a) credit assessment user by step (6f) Suo Shu to cognitive user cooperation scoring with step (8b) Suo Shu to cognitive user communicate by letter scoring two scorings carry out signature operation;
(9b) credit assessment user intercourses the scoring of the cooperation to cognitive user and the scoring of communicating by letter after signature;
(9c) according to scoring fusion method, respectively credit assessment user is merged with the scoring of communicating by letter the cooperation scoring of cognitive user, obtain the cooperation general comment and the general comment of communicating by letter of cognitive user;
(9d) credit assessment user's scoring is adjudicated, if credit assessment user is all less than 0.1 with the cooperation general comment of cognitive user and the difference of the general comment of communicating by letter to the cooperation scoring of cognitive user respectively with the scoring of communicating by letter, credit assessment user's assessment justice, otherwise, credit assessment user's assessment unfairness;
(9e), according to assessment credit value evaluation method, determine credit assessment user's assessment credit value.
(10) credit value upgrades:
(10a) credit assessment user group, according to credit value update method, obtains the reputation data after upgrading, and the trust data after renewal comprises cooperation credit value, communication credit value and total credit value of cognitive user;
(10b) credit assessment user group, by the reputation data after upgrading, is broadcast to all cognitive user of cognitive radio;
(10c) cognitive user, by the reputation data after upgrading, is recorded in the trust data record of cognitive user.
The present invention compared with prior art has the following advantages:
First, because the present invention adopts credit assessment user group, distributed cognition radio network is carried out to trust management, overcome the inabundant feature in conjunction with distributed cognition wireless network in prior art, need to rely on cognitive user base station to carry out the deficiency of measures of reputation, make the present invention not need to rely on trusted third party, just can solve more efficiently assessment, calculating and the renewal of the credit value to cognitive user, judge the prestige state of cognitive user.
Second, because the present invention adopts assessment cooperation credit value prestige, assessment communication credit value and determines assessment credit value, refinement the method that the trust metrics stage is changed real-time prestige, overcome the deficiency of not considering trust initialization, in real time trust evaluation and trust update in prior art, made the present invention improve the feasibility of cognitive radio networks trust evaluation.
The 3rd, because the present invention adopts trust metrics assessment and two aspects of supervision in conjunction with carrying out trust metrics, overcome the deficiency that cannot ensure correctly to carry out measures of reputation and frequency spectrum perception in prior art in the time that network suffers malicious attack, made the present invention improve fail safe and the robustness of trust evaluation.
The 4th, because the present invention adopts cooperation credit value prestige, communication credit value and the multiple trust evaluation measure coefficients of assessment credit value, measure coefficient variation, has overcome the single deficiency of the trust metrics factor in prior art, makes the present invention improve the fairness of trust evaluation.
The 5th, because the present invention adopts complete credit assessment user group selection scheme and the Evaluation and calculation method of cognitive user credit value, form a rounded system flow process, overcome in prior art the not deficiency of complete method for evaluating trust, made the present invention more intuitively and embody accurately the prestige state of a cognitive user.
Brief description of the drawings
Fig. 1 is flow chart of the present invention.
Concrete implementing measure
Below in conjunction with accompanying drawing 1, concrete steps of the present invention are described further.
Step 1, initialization.
When radio net initialization, data record in the database of cognitive user is all emptied, comprise the network parameter data record of cognitive user, the trust data record of cognitive user, perception data record, the frequency spectrum request msg record of cognitive user and five kinds of data record of data record of credit assessment user group of cognitive user.
Each cognitive user in radio net is set to unique identify label, the identify label of cognitive user is deposited in the network parameter data record of cognitive user.
In the trust data record of cognitive user, initial cooperation credit value and the initial communication credit value of all cognitive user are set to 0.5, and initial assessment credit value is set to 0, and initial total credit value is set to 0.5.Cognitive user number in radio net is recorded in the network parameter data record of cognitive user, completes radio net initialization.
In the time having new cognitive user request to add cognitive radio networks, new cognitive user is carried out to initialization: credit assessment user group is by the new cognitive user of credit value information notification of other users in current wireless electric network.Empty the data in the trust data storehouse of new cognitive user, the credit value information of other cognitive user in current wireless electric network and cognitive user number are stored into database.
Cognitive user number in radio net in the network parameter data record of institute's cognitive user is added to 1.In the trust data storehouse of all cognitive user, for new cognitive user creates a prestige record.
By the behavior credit value of new cognitive user, cooperation credit value and total credit value, be all set to the mean value of all users in current wireless electric network, assessment credit value is set to 0, completes new cognitive user initialization.
Step 2, selects initial credit assessment user group.
If the data record of credit assessment user group is empty, carry out following steps; Otherwise, go to step 3 execution.
An optional arithmetic number is as selection percentage in [0.2,0.5] scope, and selection percentage can dynamic setting, and cognitive user number and selection percentage in radio net are rounded after multiplying each other, and obtains the number of users that credit assessment user organizes.
According to the following formula, calculate the selection factor of assessment user group:
Wherein, m represents the selection factor of credit assessment user group, and N represents cognitive user number in radio net, and J represents the number of users of credit assessment user group,
represent to round operation downwards.
From the database of cognitive user, the credit assessment user that the cognitive user of selecting to meet following formula identify label condition is charged to cognitive user organizes in data record:
I?mod?m＝1
Wherein, I represents the identify label of cognitive user, and m represents the selection factor of credit assessment user group, and mod represents modulo operation.
The credit assessment user of cognitive user is organized to the cognitive user recording in data record, as credit assessment user, using all credit assessment users as credit assessment user group.
Step 3, screening credit assessment user group.
Check that successively credit assessment user organizes the credit value of all credit assessment users in data record, if total credit value of credit assessment user is less than 0.5, or credit assessment user's assessment credit value is less than 0, for ensureing the fail safe of trust evaluation, this cognitive user has no longer met the condition of credit assessment user group, and this credit assessment user is organized data record and deleted from credit assessment user.
Check that successively all credit assessment users that credit assessment user organizes in data record participate in credit assessment number of times continuously, if participating in credit assessment continuously, credit assessment user exceedes 5 times, for ensureing the fairness of trust evaluation, this user can not continue continuously, as credit assessment user, this credit assessment user to be organized data record and to be deleted from credit assessment user.
Step 4, judges whether the residue credit assessment number of users that credit assessment user organizes in data record is less than 2, if residue credit assessment number of users is less than 2, execution step 5, reselects credit assessment user group, otherwise, execution step 6.
Step 5, reselects credit assessment user group.
Current credit assessment user organizes positive integer of random issue, using this positive integer as the initial application number of cognitive user.Wish to add the cognitive user of credit assessment user group to send application information.
Credit assessment user organizes and checks whether the credit value of the cognitive user of sending application information meets application condition, application condition comprises that the credit value of cognitive user need to be greater than 0.5, cognitive user at least participated in frequency spectrum perception or data communication behavior, and the dump energy of cognitive user has been greater than the required energy of trust evaluation at least one times.Then, taking initial application number as starting point, for increasing progressively, to qualified cognitive user, set successively an application number with 1, the application number of cognitive user is recorded in the data record of credit assessment user group.
According to the following formula, calculate the selection factor of credit assessment user group:
Wherein, m represents the selection factor of credit assessment user group, N
1cognitive user number in the data record of expression credit assessment user group, J represents the number of users of the described credit assessment user group of step (2c),
represent to round operation downwards.
From the data record of credit assessment user group, select to meet the cognitive user of following formula application numbers condition, the user who does not satisfy condition is deleted:
A?mod?m＝1
Wherein, A represents the application number of cognitive user, and m represents the selection factor of credit assessment user group, and mod represents modulo operation.
The credit assessment user of cognitive user is organized to the cognitive user recording in data record, as credit assessment user, using all credit assessment users as credit assessment user group.Select credit assessment user can ensure the fairness of selecting in order to upper method.
Step 6, the cooperation prestige of assessment cognitive user.
Cognitive user is carried out local signal detection, and by local frequency spectrum perception information reporting, to credit assessment user group, the row vector element value of frequency spectrum perception information is 0 and 1, the frequency spectrum number that the number of the element of row vector is perception.
Credit assessment user group receives after the frequency spectrum perception information that cognitive user reports, and the row vector of frequency spectrum perception information is arranged in order from top to bottom, obtains a line number and equal the matrix of the cognitive user number that reports frequency spectrum perception information.Credit assessment user organizes the number of times that in each column vector of comparator matrix, vector element 0 and 1 occurs, by transversely arranged successively the vector element that occurrence number in each column vector is many, obtains a row vector, using this row vector as final frequency spectrum perception information.
Credit assessment user group is by final frequency spectrum perception information broadcasting to the cognitive user in radio net, and cognitive user enters final frequency spectrum perception information recording the perception information data record of cognitive user.
Credit assessment user adjudicates the frequency spectrum perception information of cognitive user: if final frequency spectrum perception information is identical with the frequency spectrum perception information of cognitive user, cognitive user frequency spectrum perception is correct, otherwise, cognitive user frequency spectrum perception mistake.
Credit assessment user determines the cooperation scoring to cognitive user: if cognitive user reports perception information, and frequency spectrum perception is correct, and the cooperation of cognitive user scoring is 1; If cognitive user reports perception information, but frequency spectrum perception mistake, the cooperation of cognitive user scoring is 0.5; If cognitive user does not report perception information, the cooperation of cognitive user scoring is 0.
Step 7, resource is distributed.
The cognitive user that need to carry out frequency spectrum use thinks that credit assessment user group sends frequency spectrum solicited message, and solicited message comprises the bid of cognitive user to asked frequency spectrum.Credit assessment user group receives after the solicited message of cognitive user, according to the following formula, calculates the frequency spectrum competitiveness of the cognitive user of sending frequency spectrum solicited message, the frequency spectrum competitiveness of cognitive user is recorded in the frequency spectrum request msg record of cognitive user:
CP＝T*B
Wherein, CP represents the frequency spectrum competitiveness of cognitive user, and T is the total credit value of cognitive user, and B is the bid of cognitive user to frequency spectrum.
Credit assessment user group is by from the frequency spectrum perception data record of cognitive user, the frequency spectrum that the final frequency spectrum perception information reading is 0, be recorded as idle frequency spectrum list, the frequency spectrum competitiveness of cognitive user is sorted from big to small, the frequency spectrum in idle frequency spectrum list is distributed to the descending cognitive user of competitiveness successively.
After spectrum allocation may completes, credit assessment user organizes and announces spectrum allocation may result.
Step 8, the communication prestige of assessment cognitive user.
Be assigned to the cognitive user of frequency spectrum at the enterprising row data communication of assigned frequency spectrum, cognitive user is carried out in the process of data communication, credit assessment user awareness is monitored the communication behavior of each cognitive user, the communication scoring of assessment to cognitive user: if the behavior of frequency spectrum or interfere with primary users communication does not appear taking by force in cognitive user, the communication of cognitive user scoring is 1; If the behavior of interfere with primary users appears in cognitive user, the communication of cognitive user scoring is 0.5; If the behavior of frequency spectrum appears taking by force in cognitive user, the communication of cognitive user scoring is 0.
Step 9, determines credit assessment user's assessment credit value.
Credit assessment user will carry out after signature operation with two scorings of scoring that cognitive user is communicated by letter cognitive user cooperation scoring, intercourse the scoring of the cooperation to cognitive user and the scoring of communicating by letter after signature, signature has ensured the non-repudiation of the scoring of credit assessment user to cognitive user.
According to the following formula, calculate the weight factor of the scoring of credit assessment user to cognitive user, weight factor is relevant to credit assessment user's assessment credit value:
Wherein, ω
jthe weight factor of the scoring of the credit assessment user that expression identify label is j to cognitive user,
the assessment credit value that represents the credit assessment user that identify label is j, j represents credit assessment user's identify label, and J represents the credit assessment user's of credit assessment user group identify label collection, and Σ represents sum operation.
According to the following formula, merge the cooperation scoring of cognitive user, obtain the cooperation general comment of cognitive user:
Wherein, Q
1represent the cooperation general comment of cognitive user, j represents credit assessment user's identify label, and J represents the assessment user's of credit assessment user group identify label collection,
represent that the credit assessment user that identify label is j marks to the cooperation of cognitive user, ω
jthe weight factor of the scoring of the credit assessment user that expression identify label is j to cognitive user.
According to the following formula, merge the communication scoring of cognitive user, obtain the communication general comment of cognitive user:
Wherein, Q
2represent the communication general comment of cognitive user, j represents the identify label of cognitive user, and J represents the credit assessment user's of credit assessment user group identify label collection,
represent that the credit assessment user that identify label is j marks to the communication of cognitive user, ω represents the weight factor of the scoring of credit assessment user to cognitive user, ω
jthe weight factor of the scoring of the credit assessment user that expression identify label is j to cognitive user.
The cooperation general comment that obtains cognitive user with communicate by letter after general comment, credit assessment user group is adjudicated credit assessment user's scoring: if credit assessment user is all less than 0.1 with the cooperation general comment of cognitive user and the difference of the general comment of communicating by letter to the cooperation scoring of cognitive user respectively with the scoring of communicating by letter, credit assessment user's assessment justice, otherwise, credit assessment user's assessment unfairness.
Pass judgment on situation according to credit assessment user's scoring, determine credit assessment user's assessment credit value.If credit assessment user completes credit assessment and assessment is fair, credit assessment user's assessment credit value improves 0.1; The assessment unfairness if credit assessment user completes credit assessment, credit assessment user's assessment credit value reduces by 0.2; If credit assessment user does not complete credit assessment, credit assessment user's assessment credit value reduces by 0.1.
Because assessment credit value is for being not less than 0, be not more than 1 real number, need to credit assessment user's assessment credit value be adjudicated and be revised.If credit assessment user's assessment credit value is less than 0, credit assessment user's assessment credit value is modified to 0; If credit assessment user's assessment credit value is greater than 1, credit assessment user's assessment credit value is modified to 1.
Step 10, credit value upgrades.
According to the following formula, the cooperation credit value after the renewal of calculating cognitive user:
T
1＝H
1×γ+Q
1×(1-γ)
Wherein, T
1cooperation credit value after the renewal of expression cognitive user, H
1for the cooperation credit value before the renewal of cognitive user, γ represents that the time trusts modifying factor, and its value is between being real number between 0 and 1, Q
1represent the cooperation general comment of cognitive user.
According to the following formula, the communication credit value after the renewal of calculating cognitive user:
T
2＝H
2×γ+Q
2×(1-γ)
Wherein, T
2communication credit value after the renewal of expression cognitive user, H
2for the communication credit value before the renewal of cognitive user, γ represents that the time trusts modifying factor, and its value is between being real number between 0 and 1, Q
2represent the communication general comment of cognitive user.
According to the following formula, the total credit value after the renewal of calculating cognitive user:
T＝T
1×α+T
2×β+T
3×(1-α-β)
Wherein, T represents the total credit value after the renewal of cognitive user, T
1cooperation credit value after the renewal of expression cognitive user, T
2communication credit value after the renewal of expression cognitive user, T
3represent the assessment credit value of cognitive user, α and β represent the trust weight factor, and the value of α and β is between being real number between 0 and 1, and meets alpha+beta < 1.
Trust data after renewal comprises cooperation credit value, communication credit value and total credit value of cognitive user.Obtain after the reputation data after upgrading, credit assessment user group is broadcast to the reputation data after upgrading all cognitive user of cognitive radio, cognitive user is recorded into the reputation data after upgrading the trust data record of cognitive user, complete credit value and upgrade, complete the assessment to cognitive user credit value in distributed cognition radio network.
Claims (8)
1. a method of assessing cognitive user credit worthiness in distributed cognition radio network, comprises the steps:
(1) initialization:
(1a) all empty the data record in the database of cognitive user, to each cognitive user in radio net, set unique identify label according to natural number order, the identify label of cognitive user is deposited in the network parameter data record of cognitive user;
(1b) initial cooperation credit value and the initial communication credit value of all cognitive user in the trust data of cognitive user record are set to 0.5, and initial assessment credit value is set to 0, and initial total credit value is set to 0.5;
(1c) cognitive user number in radio net is recorded in the network parameter data record of recognizing cognitive user, completes radio net initialization;
(1d) add the new cognitive user of network to carry out initialization to request;
(2) select initial credit assessment user group:
(2a) judge whether the data record that credit assessment user organizes is empty, if it is empty, execution step (2b), otherwise, execution step (3);
(2b) in [0.2,0.5] scope an optional arithmetic number as selection percentage;
(2c) cognitive user number and selection percentage in radio net are rounded after multiplying each other, obtain the number of users of credit assessment user group;
(2d) calculate according to the following formula, the selection factor of credit assessment user group:
Wherein, m represents the selection factor of credit assessment user group, and N represents cognitive user number in radio net, and J represents the number of users of credit assessment user group,
represent to round operation downwards;
(2e) from the database of cognitive user, select to meet the cognitive user of following formula identify label condition, the credit assessment user who charges to cognitive user organizes in data record:
I?mod?m＝1
Wherein, I represents the identify label of cognitive user, and m represents the selection factor of credit assessment user group, and mod represents modulo operation;
(2f) the credit assessment user of cognitive user is organized to the cognitive user recording in data record, as credit assessment user, using all credit assessment users as credit assessment user group;
(3) screening credit assessment user group:
(3a) check that successively credit assessment user organizes the credit value of all credit assessment users in data record, if total credit value of credit assessment user is less than 0.5, or credit assessment user's assessment credit value is less than 0, this credit assessment user is organized data record and is deleted from credit assessment user;
(3b) check that successively all credit assessment users that credit assessment user organizes in data record participate in credit assessment number of times continuously, exceed 5 times if credit assessment user participates in credit assessment continuously, this credit assessment user is organized data record and deleted from credit assessment user;
(4) judge whether the residue credit assessment number of users that credit assessment user organizes in data record is less than 2, if be less than 2, execution step (5), otherwise, execution step (6);
(5) reselect credit assessment user group:
(5a) current credit assessment user organizes positive integer of random issue, using this positive integer as the initial application number of cognitive user;
(5b) wish to add the cognitive user of credit assessment user group to send application information;
(5c) check whether the credit value of cognitive user that sends application information meets application condition, taking initial application number as starting point, with 1 for increasing progressively, to qualified cognitive user, set successively an application number, the application number of cognitive user is recorded in the data record of credit assessment user group;
(5d) calculate according to the following formula, the selection factor of credit assessment user group:
Wherein, m represents the selection factor of credit assessment user group, N
1cognitive user number in the data record of expression credit assessment user group, J represents the number of users of the described credit assessment user group of step (2c),
represent to round operation downwards;
(5e), from the data record of credit assessment user group, delete the cognitive user of discontented foot formula application numbers condition:
A?mod?m＝1
Wherein, A represents the application number of cognitive user, and m represents the selection factor of credit assessment user group, and mod represents modulo operation;
(5f) the credit assessment user of cognitive user is organized to the cognitive user recording in data record, as credit assessment user, using all credit assessment users as credit assessment user group;
(6) the cooperation prestige of assessment cognitive user:
(6a) cognitive user is carried out local frequency spectrum perception;
(6b) cognitive user is by local frequency spectrum perception information reporting to credit assessment user group, and the row vector element value of frequency spectrum perception information is 0 and 1, the frequency spectrum number that the number of the element of row vector is perception;
(6c) credit assessment user group is carried out perception information fusion to the frequency spectrum perception information of cognitive user, obtains final frequency spectrum perception information;
(6d) credit assessment user group is by final frequency spectrum perception information broadcasting to the cognitive user in radio net, and cognitive user enters final frequency spectrum perception information recording in the perception information data record of cognitive user;
(6e) credit assessment user to final frequency spectrum perception information whether identical judgement of frequency spectrum perception information with cognitive user, if identical, cognitive user frequency spectrum perception is correct, otherwise, cognitive user frequency spectrum perception mistake;
(6f) credit assessment user assesses the cooperation scoring of cognitive user, if cognitive user reports perception information, and cognitive user frequency spectrum perception is correct, and the cooperation of cognitive user scoring is 1; If cognitive user reports perception information, but cognitive user frequency spectrum perception mistake, the cooperation of cognitive user scoring is 0.5; If cognitive user does not report perception information, the cooperation of cognitive user scoring is 0;
(7) resource is distributed:
(7a) cognitive user is sent the frequency spectrum solicited message that comprises the bid of cognitive user to asked frequency spectrum;
(7b) according to the following formula, credit assessment user batch total is calculated the frequency spectrum competitiveness of the cognitive user of sending frequency spectrum solicited message, the frequency spectrum competitiveness of cognitive user is recorded in the frequency spectrum request msg record of cognitive user:
CP＝T*B
Wherein, CP represents the frequency spectrum competitiveness of cognitive user, and T is the total credit value of cognitive user, B by cognitive user to the bid of request frequency spectrum;
(7c) credit assessment user group by the frequency spectrum competitiveness of cognitive user according to sorting from big to small;
(7d) credit assessment user group is by from the frequency spectrum perception data record of cognitive user, the frequency spectrum that the final frequency spectrum perception information reading is 0, be recorded as idle frequency spectrum list, the frequency spectrum in idle frequency spectrum list is distributed to the descending cognitive user of competitiveness successively;
(7e) credit assessment user organizes and announces spectrum allocation may result;
(8) the communication prestige of assessment cognitive user:
(8a) cognitive user is carried out data communication according to spectrum allocation may result;
(8b) credit assessment user awareness is monitored the communication behavior of each cognitive user, determines the communication scoring to cognitive user according to communication quality judgment criteria;
(9) determine credit assessment user's assessment credit value:
(9a) credit assessment user by step (6f) Suo Shu to cognitive user cooperation scoring with step (8b) Suo Shu to cognitive user communicate by letter scoring two scorings carry out signature operation;
(9b) credit assessment user intercourses the scoring of the cooperation to cognitive user and the scoring of communicating by letter after signature;
(9c) according to scoring fusion method, respectively credit assessment user is merged with the scoring of communicating by letter the cooperation scoring of cognitive user, obtain the cooperation general comment and the general comment of communicating by letter of cognitive user;
(9d) credit assessment user's scoring is adjudicated, if credit assessment user is all less than 0.1 with the cooperation general comment of cognitive user and the difference of the general comment of communicating by letter to the cooperation scoring of cognitive user respectively with the scoring of communicating by letter, credit assessment user's assessment justice, otherwise, credit assessment user's assessment unfairness;
(9e), according to assessment credit value evaluation method, determine credit assessment user's assessment credit value;
(10) credit value upgrades:
(10a) credit assessment user group, according to credit value update method, obtains the reputation data after upgrading, and the trust data after renewal comprises cooperation credit value, communication credit value and total credit value of cognitive user;
(10b) credit assessment user group, by the reputation data after upgrading, is broadcast to all cognitive user of cognitive radio;
(10c) cognitive user, by the reputation data after upgrading, is recorded in the trust data record of cognitive user.
2. in distributed cognition radio network according to claim 1, assess the method for cognitive user credit worthiness, it is characterized in that, data record in the database of the described cognitive user of step (1a), comprises the network parameter data record of cognitive user, the trust data record of cognitive user, perception data record, the frequency spectrum request msg record of cognitive user and five kinds of data record of data record of credit assessment user group of cognitive user.
3. the method for assessing cognitive user credit worthiness in distributed cognition radio network according to claim 1, is characterized in that, the new cognitive user initialization that step (1d) is described is carried out as follows:
The first step, credit assessment user group, by the new cognitive user of credit value information notification of other users in current wireless electric network;
Second step, empties the data in the trust data storehouse of new cognitive user, the credit value information of other cognitive user in current wireless electric network and cognitive user number is deposited in to the database of cognitive user;
The 3rd step, in the database of all cognitive user, adds 1 by cognitive user number in the radio net in the network parameter data record of cognitive user;
The 4th step, in the trust data record of all cognitive user, for new cognitive user creates a prestige record;
The 5th step, by the behavior credit value of new cognitive user, cooperation credit value and total credit value, the mean value that is all set to the credit value of every other cognitive user in radio net, the assessment credit value of new cognitive user is set to 0, completes new cognitive user initialization.
4. the method for assessing cognitive user credit worthiness in distributed cognition radio network according to claim 1, is characterized in that, the described perception information of step (6c) merges, and carries out as follows:
The first step, credit assessment user group receives after the frequency spectrum perception information that cognitive user reports, and the row vector of frequency spectrum perception information is arranged in order from top to bottom, obtains a line number and equal the matrix of the cognitive user number that reports frequency spectrum perception information;
Second step, credit assessment user organizes the number of times that in each column vector of comparator matrix, vector element 0 and 1 occurs, records the many vector elements of occurrence number in each column vector;
The 3rd step, credit assessment user group is by each column vector, and the vector element that occurrence number is many is transversely arranged successively, obtains a row vector, using this row vector as final frequency spectrum perception information.
5. in distributed cognition radio network according to claim 1, assess the method for cognitive user credit worthiness, it is characterized in that, the described communication quality judgment criteria of step (8b) is: if the behavior of frequency spectrum or interfere with primary users communication does not appear taking by force in cognitive user, the communication of cognitive user scoring is 1; If the behavior of interfere with primary users appears in cognitive user, the communication of cognitive user scoring is 0.5; If the behavior of frequency spectrum appears taking by force in cognitive user, the communication of cognitive user scoring is 0.
6. the method for assessing cognitive user credit worthiness in distributed cognition radio network according to claim 1, is characterized in that, the scoring fusion method that step (9c) is described is carried out as follows:
The first step, according to the following formula, calculate the weight factor of the scoring of credit assessment user to cognitive user:
Wherein, ω
jthe weight factor of the scoring of the credit assessment user that expression identify label is j to cognitive user,
the assessment credit value that represents the credit assessment user that identify label is j, j represents credit assessment user's identify label, and J represents the credit assessment user's of credit assessment user group identify label collection, and Σ represents sum operation;
Second step, according to the following formula, merges the cooperation scoring of cognitive user, obtains the cooperation general comment of cognitive user:
Wherein, Q
1represent the cooperation general comment of cognitive user, j represents credit assessment user's identify label, and J represents the assessment user's of credit assessment user group identify label collection,
represent that the credit assessment user that identify label is j marks to the cooperation of cognitive user, ω
jthe weight factor of the scoring of the credit assessment user that expression identify label is j to cognitive user;
The 3rd step, according to the following formula, merges the communication scoring of cognitive user, obtains the communication general comment of cognitive user:
Wherein, Q
2represent the communication general comment of cognitive user, j represents the identify label of cognitive user, and J represents the credit assessment user's of credit assessment user group identify label collection,
represent that the credit assessment user that identify label is j marks to the communication of cognitive user, ω represents the weight factor of the scoring of credit assessment user to cognitive user, ω
jthe weight factor of the scoring of the credit assessment user that expression identify label is j to cognitive user.
7. the method for assessing cognitive user credit worthiness in distributed cognition radio network according to claim 1, is characterized in that, the assessment credit value evaluation method that step (9e) is described carries out according to following rule:
The first step, if credit assessment user completes credit assessment and assessment is fair, credit assessment user's assessment credit value improves 0.1; The assessment unfairness if credit assessment user completes credit assessment, credit assessment user's assessment credit value reduces by 0.2; If credit assessment user does not complete credit assessment, credit assessment user's assessment credit value reduces by 0.1;
Second step, adjudicates and revises credit assessment user's assessment credit value: if credit assessment user's assessment credit value is less than 0, credit assessment user's assessment credit value is modified to 0; If credit assessment user's assessment credit value is greater than 1, credit assessment user's assessment credit value is modified to 1.
8. the method for assessing cognitive user credit worthiness in distributed cognition radio network according to claim 1, is characterized in that, the credit value update method that step (10a) is described is carried out according to following rule:
The first step, according to following formula, the cooperation credit value after the renewal of calculating cognitive user:
T
1＝H
1×γ+Q
1×(1-γ)
Wherein, T
1cooperation credit value after the renewal of expression cognitive user, H
1for the cooperation credit value before the renewal of cognitive user, γ represents time trust modifying factor, and its value is the real number between 0 and 1, Q
1represent the cooperation general comment of cognitive user;
Second step, according to the following formula, the communication credit value after the renewal of calculating cognitive user:
T
2＝H
2×γ+Q
2×(1-γ)
Wherein, T
2communication credit value after the renewal of expression cognitive user, H
2for the communication credit value before the renewal of cognitive user, γ represents time trust modifying factor, and its value is the real number between 0 and 1, Q
2represent the communication general comment of cognitive user;
The 3rd step, according to the following formula, the total credit value after the renewal of calculating cognitive user:
T＝T
1×α+T
2×β+T
3×(1-α-β)
Wherein, T represents the total credit value after the renewal of cognitive user, T
1cooperation credit value after the renewal of expression cognitive user, T
2communication credit value after the renewal of expression cognitive user, T
3represent the assessment credit value of cognitive user, α and β represent the trust weight factor, and the value of α and β is between being real number between 0 and 1, and meets alpha+beta < 1.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104202106A (en) * | 2014-09-26 | 2014-12-10 | 哈尔滨工业大学 | Collaborative spectrum perception method based on credibility in mobile scene |
| CN104618909A (en) * | 2015-01-08 | 2015-05-13 | 沈阳航空航天大学 | Credibility-based aeronautical radio cooperative spectrum sensing method |
| CN105187140A (en) * | 2015-07-14 | 2015-12-23 | 福建师范大学 | Distributed credible spectrum cooperative sensing method in cognitive radio network |
| CN107623554A (en) * | 2017-08-24 | 2018-01-23 | 西安电子科技大学 | A kind of cooperative frequency spectrum sensing method based on trust value, cognition wireless network |
| CN107808324A (en) * | 2017-10-20 | 2018-03-16 | 西安电子科技大学 | A kind of prestige value calculating method, network trading platform, the computer of online commodity |
| CN109327911A (en) * | 2018-11-30 | 2019-02-12 | 重庆邮电大学 | Recognize the frequency spectrum switching method based on credit system in heterogeneous wireless network |
| CN114614923A (en) * | 2022-02-25 | 2022-06-10 | 中国人民解放军陆军工程大学 | Spectrum use order strengthening method and system based on abnormal frequency behavior detection |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100238868A1 (en) * | 2005-08-04 | 2010-09-23 | Stmicroelectronics S.R.L. | Method and system for dynamic spectrum allocation, and computer program product therefor |
| CN102724678A (en) * | 2012-07-04 | 2012-10-10 | 西安电子科技大学 | Reputation-based resource allocation method in central-type cognition wireless network |
| CN103178910A (en) * | 2013-02-27 | 2013-06-26 | 浙江大学 | Credibility based cognitive radio network stratified cooperative spectrum sensing method |
-
2014
- 2014-03-31 CN CN201410125545.5A patent/CN103957062B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100238868A1 (en) * | 2005-08-04 | 2010-09-23 | Stmicroelectronics S.R.L. | Method and system for dynamic spectrum allocation, and computer program product therefor |
| CN102724678A (en) * | 2012-07-04 | 2012-10-10 | 西安电子科技大学 | Reputation-based resource allocation method in central-type cognition wireless network |
| CN103178910A (en) * | 2013-02-27 | 2013-06-26 | 浙江大学 | Credibility based cognitive radio network stratified cooperative spectrum sensing method |
Non-Patent Citations (2)
| Title |
|---|
| DONGMEI SHU: "A trust-based method for cooperative spectrum sensing in cognitive radio networks", 《IEEE》, 22 November 2013 (2013-11-22) * |
| PARVIN,S.: "Towards Trust Establishment for Spectrum Selection in Cognitive Radio Networks", 《IEEE》, 23 April 2010 (2010-04-23) * |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104202106B (en) * | 2014-09-26 | 2016-04-20 | 哈尔滨工业大学 | Based on the cooperative frequency spectrum sensing method of degree of belief in mobile context |
| CN104202106A (en) * | 2014-09-26 | 2014-12-10 | 哈尔滨工业大学 | Collaborative spectrum perception method based on credibility in mobile scene |
| CN104618909A (en) * | 2015-01-08 | 2015-05-13 | 沈阳航空航天大学 | Credibility-based aeronautical radio cooperative spectrum sensing method |
| CN104618909B (en) * | 2015-01-08 | 2017-12-01 | 沈阳航空航天大学 | A kind of aviation radio cooperative frequency spectrum sensing method based on credit worthiness |
| CN105187140B (en) * | 2015-07-14 | 2018-05-04 | 福建师范大学 | Distributed credible frequency spectrum collaborative sensing method in cognition wireless network |
| CN105187140A (en) * | 2015-07-14 | 2015-12-23 | 福建师范大学 | Distributed credible spectrum cooperative sensing method in cognitive radio network |
| CN107623554A (en) * | 2017-08-24 | 2018-01-23 | 西安电子科技大学 | A kind of cooperative frequency spectrum sensing method based on trust value, cognition wireless network |
| CN107808324A (en) * | 2017-10-20 | 2018-03-16 | 西安电子科技大学 | A kind of prestige value calculating method, network trading platform, the computer of online commodity |
| CN107808324B (en) * | 2017-10-20 | 2021-05-28 | 西安电子科技大学 | Online commodity credit value calculation method, network transaction platform and computer |
| CN109327911A (en) * | 2018-11-30 | 2019-02-12 | 重庆邮电大学 | Recognize the frequency spectrum switching method based on credit system in heterogeneous wireless network |
| CN109327911B (en) * | 2018-11-30 | 2022-05-03 | 重庆邮电大学 | Reputation system-based spectrum switching method in cognitive heterogeneous wireless network |
| CN114614923A (en) * | 2022-02-25 | 2022-06-10 | 中国人民解放军陆军工程大学 | Spectrum use order strengthening method and system based on abnormal frequency behavior detection |
| CN114614923B (en) * | 2022-02-25 | 2023-08-29 | 中国人民解放军陆军工程大学 | Spectrum use order strengthening method and system based on abnormal frequency behavior detection |
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