CN110300155A - Cognitive Internet of Things spectrum data sharing method based on block chain - Google Patents
Cognitive Internet of Things spectrum data sharing method based on block chain Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
- H04L63/0442—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload wherein the sending and receiving network entities apply asymmetric encryption, i.e. different keys for encryption and decryption
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
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Abstract
The invention discloses a cognitive Internet of things frequency spectrum data sharing method based on a block chain. The method comprises the following steps: firstly, a cognitive Internet of things cloud server issues a spectrum data sharing requirement, and spectrum coins are prestored; then, nodes participating in spectrum data sharing spontaneously form clusters at the edge of the cognitive Internet of things, spectrum data are collected and packaged into pre-added spectrum data sub-blocks, and the pre-added spectrum data sub-blocks are asymmetrically encrypted and uploaded to fog nodes at the edge of a network; secondly, the fog node issues a spectrum data block verification requirement, and the verification node performs consensus verification on the pre-added spectrum data sub-blocks locally; determining clusters for providing new spectrum data sub-blocks among cluster head nodes through distributed consensus; and finally, automatically distributing the spectrum coins in the clusters according to the contribution proportion and the quality of the spectrum data blocks. According to the method, the decentralization, high fault tolerance and non-tampering sharing of the spectrum data in the cognitive Internet of things are realized, and the spectrum data sharing time delay and the data transmission energy consumption are reduced.
Description
Technical field
The present invention relates to cognition internet of things field, especially a kind of cognition Internet of Things frequency spectrum datas based on block chain
Sharing method.
Background technique
Cognition Internet of Things is a kind of new networking paradigms, it assigns " brain " for Internet of Things, it is made to have elaborative faculty.With
Internet of Things car networking, smart home, smart city, intelligence wearing etc. numerous areas obtain application and it is increasingly prominent its to people
The important value of class society, people gradually recognize between object be only connected with each other be it is far from being enough, object should have
Self-teaching, thinking and the ability for understanding physical world and human society are understanding physical world perception information and reasoning
On the basis of, it realizes the intelligence of resource allocation, network operation, service configuration, physical world and human society is combined together.Recognize
Know that Internet of Things has become international forward position and the hot spot of academia and industry close attention, represents the development in Internet of Things future
Trend, concept and raw product are gradually used in the fields such as smart home, wisdom building, monitoring unmanned.Future, Che Lian
The heterogeneous devices such as net, smart home, smart city, intelligent wearable device and network will increasingly move towards to merge, and provide more for the mankind
Add comfortable, convenient and fast life.
Electromagnetic spectrum is to ensure that " the neural train of thought " of cognition Internet of Things operation, merges increasingly in the cognition Internet of Things of isomery,
Increasingly present super-intensive, large scale deployment trend under, high-quality frequency spectrum resource it is in short supply become restrict cognition Internet of Things quickly send out
The bottleneck of exhibition.The running for recognizing Internet of Things depends on high efficiency of transmission, effective integration and the intelligent decision of data, wherein data pass
It is defeated mainly based on public open frequency range or dedicated frequency range.However, as more to show all things on earth mutual for the development of cognition Internet of Things
The trend of connection, hundreds of millions of equipment access cognition Internet of Things, on the one hand, dedicated frequency range can't bear the heavy load already, recognize Internet of Things
Frequent generation is interfered with each other between equipment, the scarcity of high-quality dedicated frequency spectrum resource is difficult to support the sustainable of cognition Internet of Things
Development；On the other hand, the competition use pattern of public open frequency range and random mutual interference characteristic often make it under complex electromagnetic environment
It is difficult for cognition Internet of Things and reliable and stable communication guarantee is provided.It recognizes internet of things equipment and surrounding electromagnetism is grasped by frequency spectrum data
Environment, the single internet of things equipment ability that recognizes is limited, comprehensive standard that the frequency spectrum data of acquisition is not enough to support it to electromagnetic environment
It really grasps, therefore, cognition internet of things equipment needs the mutual frequency spectrum data of networking share.C.-H.Ko et al. (C.-H.Ko,
D.H.Huang,and S.-H.Wu,“Cooperative spectrum sensing in TV White Spaces:When
cognitive radio meets cloud,”in Proc.IEEE INFOCOM Workshop Cloud Comput.,
Apr.2011, pp.672-677.) it proposes to utilize large-scale memory and processor, pass through the collaborative spectrum sensing of centralization
Frequency spectrum data cloud is constructed, the current spectrum management network of the frequency spectrum perception device build of centralized management is based on, however
The frequency spectrum perception equipment of profession is limited after all, it is difficult to form effective covering to time-frequency domain-airspace electromagnetic environment；
M.Pan et al. (M.Pan, P.Li, Y.Song, Y.Fang, P.Lin, and S.Glisic, " When spectrum meets
clouds:Optimal session based spectrum trading under spectrum uncertainty,”
IEEE J.Sel.Areas Commun., vol.32, no.3, pp.615-627, Mar.2014.) it proposes to hand over by frequency spectrum data
User's dynamic of not cognitive ability is easily supported to use frequency spectrum resource, this frequency spectrum data transaction can only exist in a point-to-point fashion
Frequency spectrum perception equipment and frequency spectrum are carried out using between equipment；Q.Wu et al. (Q.Wu, G.Ding, Z.Du, Y.Sun, M.JO, and
V.Vasilakos,“A cloud-based architecture for the internet of spectrum devices
over future wireless networks,”IEEE Access,vol.4,no.2016,pp.2854-2862,
Jun.2016. it) proposes to network popular frequency spectrum perception equipment and frequency spectrum using equipment, constitutes centralized frequency spectrum based on cloud and set
Standby network to share frequency spectrum data, but have ignored popular frequency spectrum perception equipment and frequency spectrum using equipment be it is distributed,
Frequency spectrum data can not be shared in centralized manner at all.
Summary of the invention
The purpose of the present invention is to provide a kind of low time delay, low energy consumption, and it is decentralization, highly fault tolerant based on block chain
Internet of Things frequency spectrum data sharing method is recognized, enables to recognize internet of things equipment shared frequency spectrum data in a distributed manner.
The technical solution for realizing the aim of the invention is as follows: a kind of cognition Internet of Things frequency spectrum data based on block chain is shared
Method, comprising the following steps:
Step 1, cognition Internet of Things cloud server publication frequency spectrum data share demand, and prestore frequency spectrum coin；
The shared node of step 2, participation frequency spectrum data is spontaneous to form cluster in cognition Internet of Things network edge, and acquisition frequency spectrum data is simultaneously
It is packaged as the frequency spectrum data sub-block of pre- addition, the mist node of network edge is uploaded to after progress asymmetric encryption；
Step 3, mist node publication frequency spectrum data block verify demand, the frequency spectrum data sub-district that verifying node verification adds in advance
Whether block, which meets frequency spectrum data, is shared demand, is thought if meeting there is no data falsification and wrong data and is entered step 4, if
Be unsatisfactory for, think there are data falsification and wrong data, authentication failed of knowing together, the cluster be not involved in the addition of frequency spectrum data block and
The distribution of frequency spectrum coin；
The source of pre- addition frequency spectrum data sub-block is determined between step 4, leader cluster node by distributed common recognition, it is pre- to add
Frequency spectrum data sub-block be added into frequency spectrum data block chain as formal block；
Step 5, in cluster according to the contribution proportion and quality of frequency spectrum data block, it is automatic to distribute frequency spectrum coin.
Further, the shared node of participation frequency spectrum data described in step 2 is spontaneous forms cluster in cognition Internet of Things network edge,
Acquisition frequency spectrum data and the frequency spectrum data sub-block for being packaged as pre- addition are uploaded to network edge after carrying out asymmetric encryption
Mist node, specific as follows:
The cognition Internet of things node for participating in the shared demand of frequency spectrum data shares geographic area in frequency spectrum data and spontaneously forms cluster,
Each cluster includes that multiple sensing nodes and a leader cluster node, sensing node collect frequency spectrum data under the leader of leader cluster node,
And distributed common recognition is carried out to frequency spectrum data collected, unified frequency spectrum data sub-block is formed, is enabledIndicate cluster i's
J-th of sensing node, sensing nodeAs the following formula by the state of itself by xij(k) it is updated to xij(k+1):
Wherein, xij(k) j-th of sensing node for being cluster iIn the state at k moment, xijIt (k+1) is j-th of cluster i
Sensing nodeIn the state at k+1 moment；
xin(k) frequency spectrum data for being neighbours' sensing node n,For nodeThe collection of neighbours' sensing node
It closes, in which:
Indicate nodeDegree, Ω is the maximal degree for recognizing Internet of Things adjacency matrix G, and xij(0)=Dataij,
Wherein xijIt (0) is the original state of j-th of sensing node of cluster i, DataijThe local collected for j-th of sensing node of cluster i
Frequency spectrum data；
Sensing node forms unified frequency spectrum data sub-block through excessive wheel iteration in cluster, and then leader cluster node downloads distance
Nearest Edge Server public key with the public key encryption frequency spectrum data sub-block, and is uploaded to the Edge Server, edge service
Device is decrypted to obtain frequency spectrum data sub-block with private key.
Further, the publication of mist node described in step 3 frequency spectrum data block verifies demand, and verifying node verification adds in advance
Frequency spectrum data sub-block whether meet frequency spectrum data share demand, it is specific as follows:
Leader cluster node gives verifying node by the mist nodes sharing of network edge by asymmetric encryption, by frequency spectrum data,
It verifies node and obtains frequency spectrum data, the adjacency matrix and correspondence of position, cluster including sensing node using the private key decryption of oneself
Frequency spectrum data, then verify node and common recognition verifying carried out to the frequency spectrum data of pre- addition frequency spectrum data sub-block, according to frequency spectrum
Whether the information that data provide checks in frequency spectrum data in the distributed common recognition locally simulated containing malicious user injection
Data are verified data after the completion of common recognition verifyingWith the confidence interval [Δ under 1- α confidence levelmin,Δmax], ifData falsification and wrong data is then not present, frequency spectrum data passes through common recognition verifying；Otherwise, frequency spectrum data is total to
Know authentication failed.
Further, pre- addition frequency spectrum data sub-district is determined by distributed common recognition between leader cluster node described in step 4
The source of block, the frequency spectrum data sub-block added in advance, which is added into frequency spectrum data block chain, becomes formal block, specific as follows:
Each cluster leader cluster node obtains common recognition result Q by distributed common recognition*, by Q*With original signal spectrum number provided by each cluster
According to comparing, the smallest frequency spectrum data of difference is then the supplier of new frequency spectrum data block, obtains the reward of frequency spectrum coin.
Further, the contribution proportion and quality described in step 5 in cluster according to frequency spectrum data block, automatic distribution frequency
Coin is composed, specific as follows:
After new frequency spectrum data block is added into block chain as formal block, the frequency spectrum coin coin quilt of cloud storage
To the cluster of the block is provided, frequency spectrum coin is allocated automatically according to the contribution proportion and quality of frequency spectrum data block for release.
Further, the distribution verified in step 3 in the local common recognition verifying and step 4 of node between leader cluster node is total
Know, the mist node by recognizing Internet of Things network edge carries out.
Compared with prior art, the present invention its remarkable advantage is: (1) block chain technology being applied to distributed deployment
Recognize Internet of Things, realize the decentralization of frequency spectrum data in cognition Internet of Things, it is high it is fault-tolerant, can not distort it is shared；(2) it combines
The advantage of mobile edge calculations carries out the acquisition of frequency spectrum data, verifying and the shared cognition Internet of Things network edge that is arranged in, drop
Low frequency spectrum data sharing time delay and data transmit energy consumption；(3) the distributed fusion of frequency spectrum data, verifying and frequency spectrum coin are realized
Distribution, can resist and distort to the malice of frequency spectrum data.
Detailed description of the invention
Fig. 1 is to recognize the shared network architecture schematic diagram of Internet of Things frequency spectrum data.
Fig. 2 is the flow diagram of the cognition Internet of Things frequency spectrum data sharing method the present invention is based on block chain.
Fig. 3 is the result figure verified node in the embodiment of the present invention and carry out common recognition verifying.
Fig. 4 is the common recognition process schematic that leader cluster node determines block ownership in the embodiment of the present invention.
Fig. 5 is the structure of frequency spectrum data block and organizational form schematic diagram in the embodiment of the present invention.
Fig. 6 is that three layers in the embodiment of the present invention of cognition Internet of Things frequency spectrum data shares network architecture schematic diagram.
Specific embodiment
The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
The steady frequency spectrum data share framework of cognition Internet of Things is a kind of cloud computing and what mobile edge calculations combined goes
The heterogeneous distributed network of centralization.Firstly, car networking, smart home, smart city, the intelligence of cognition Internet of Things fusion are dressed and are set
Equipment and the mutual isomery of network such as standby；Secondly, car networking, smart home, smart city, intelligent wearable device distributed portion
Administration, there is no generate center control nodes after fusion；Third, the side that cognition Internet of Things is combined by cloud computing with edge calculations
Formula reduces frequency spectrum data propagation delay time, saves data transmissions consumption, and network architecture schematic diagram is as shown in Figure 1.
As shown in Fig. 2, the present invention is based on the cognition Internet of Things frequency spectrum data sharing methods of block chain, comprising the following steps:
Step 1, cognition Internet of Things cloud server issue frequency spectrum data automatically and share demand, and prestore frequency spectrum coin
coinspec, it is specific as follows:
It includes data time, band limits and geographic area that frequency spectrum data, which shares demand, and the demand is in cognition Internet of Things
Servers-all and node are visible；The autonomous response spectrum data sharing demand of the cognition internet of things equipment of distributed deployment；Meanwhile
Server prestores the return that frequency spectrum coin is shared as frequency spectrum data to cognition Internet of Things beyond the clouds.Frequency spectrum coin is a kind of encryption currency,
It generates and propagates in cognition Internet of Things, can be used for buying the frequency spectrum right to use, flow and bandwidth.
The shared node of step 2, participation frequency spectrum data is spontaneous to form cluster in cognition Internet of Things network edge, and acquisition frequency spectrum data is simultaneously
It is packaged as the frequency spectrum data sub-block of pre- addition, the mist node of network edge is uploaded to after progress asymmetric encryption, specifically such as
Under:
The cognition Internet of things node for participating in the shared demand of frequency spectrum data shares the spontaneous shape of geographical vicinity in frequency spectrum data
At N number of cluster, cluster i includes a leader cluster nodeWith several sensing nodes, sensing nodeIndicate cluster
J-th of sensing node of i,For the quantity of sensing node in cluster i.Sensing node is in leader cluster nodeLeader under collect
Frequency spectrum data, and distributed common recognition is carried out to frequency spectrum data collected, unified frequency spectrum data sub-block is formed, method is such as
Under:
Sensing nodeFrequency spectrum data is acquired first, and the frequency spectrum of neighbours' sensing node n is received further according to adjacency matrix G
Data xin(k), as the following formula by the state of itself by xij(k) it is updated to xij(k+1):
Wherein, xij(k) j-th of sensing node for being cluster iIn the state at k moment, xijIt (k+1) is j-th of cluster i
Sensing nodeIn the state at k+1 moment；
xin(k) frequency spectrum data for being neighbours' sensing node n,For nodeThe collection of neighbours' sensing node
It closes, in which:
Indicate nodeDegree, Ω is the maximal degree for recognizing Internet of Things adjacency matrix G, and xij(0)=Dataij,
Wherein xijIt (0) is the original state of j-th of sensing node of cluster i, DataijThe local collected for j-th of sensing node of cluster i
Frequency spectrum data；
Common recognition iterative process can also be write as following matrix form
X (k+1)=Px (k) (3)
Wherein P=I- η L, I are unit matrix, and L is the Laplace transform of adjacency matrix G, and common recognition process iteration carries out straight
The state of sensing node converges to unified frequency spectrum data in cluster.
Sensing node forms unified frequency spectrum data sub-block through excessive wheel iteration in cluster, and then leader cluster node downloads distance
Nearest Edge Server public keyThe encrypted signature frequency spectrum data Data generated with the public keyiObtain frequency spectrum data
Block Blocki, and it is uploaded to Edge Server edgei
Edge Server edgeiReceive frequency spectrum data sub-block BlockiAfterwards, with the private key of oneselfThe signature of generation
Decryption obtains frequency spectrum data DataiSub-block:
Asymmetric encryption and decryption are carried out using RSA Algorithm.Each cognition internet of things equipment is owned by a pair of secret keys, i.e., public
Key keypubicWith private key keyprivate, public key discloses on cognition Internet of Things, and any node can be downloaded and for encrypting, private key
Equipment end is retained in for decrypting.
Step 3, mist node publication frequency spectrum data block verify demand, the frequency spectrum data sub-district that verifying node verification adds in advance
Whether block, which meets frequency spectrum data, is shared demand, is thought if meeting there is no data falsification and wrong data and is entered step 4, if
Be unsatisfactory for, think there are data falsification and wrong data, authentication failed of knowing together, the cluster be not involved in the addition of frequency spectrum data block and
The distribution of frequency spectrum coin, specific as follows:
Leader cluster node is returned in network edge server storage frequency spectrum coin as data verification, and Edge Server issues frequency spectrum
Data block validation task, other cognition autonomous response verification tasks of Internet of things node near Edge Server, becomes verifying
Node.Whether the frequency spectrum data block that verifying node verification adds in advance, which meets frequency spectrum data, is shared demand, the method is as follows:
Leader cluster node gives verifying node by the mist nodes sharing of network edge by asymmetric encryption, by frequency spectrum data,
It verifies node and obtains frequency spectrum data, the adjacency matrix and correspondence of position, cluster including sensing node using the private key decryption of oneself
Frequency spectrum data, then verify node and common recognition verifying carried out to the frequency spectrum data of pre- addition frequency spectrum data sub-block, according to frequency spectrum
Whether the information that data provide checks in frequency spectrum data in the distributed common recognition locally simulated containing malicious user injection
Data are verified data after the completion of common recognition verifyingWith the confidence interval [Δ under 1- α confidence levelmin,Δmax], ifData falsification and wrong data is then not present, frequency spectrum data passes through common recognition verifying；Otherwise, frequency spectrum data is total to
Know authentication failed.Fig. 3 is the common recognition verification result to frequency spectrum data, verify dataFall into confidence interval [Δmin,Δmax], therefore
Think there is no data falsification or wrong data in frequency spectrum data, common recognition is verified.
The source of pre- addition frequency spectrum data sub-block is determined between step 4, leader cluster node by distributed common recognition, it is pre- to add
Frequency spectrum data sub-block be added into frequency spectrum data block chain as formal block, it is specific as follows:
The source of pre- addition frequency spectrum data block is determined between leader cluster node by distributed common recognition.Due to the frequency added in advance
There are errors between the frequency spectrum data block that modal data block and each leader cluster node upload, so leader cluster node passes through distribution
It knows together and the frequency spectrum data block with minimal error is determined as optimal spectrum block, and be added to frequency spectrum data block chain to become
Formal block, the method is as follows:
Each cluster leader cluster node obtains common recognition result Q by distributed common recognition*, by Q*With original signal spectrum number provided by each cluster
According to comparing, the smallest frequency spectrum data of difference is then the supplier of new frequency spectrum data block, obtains the reward of frequency spectrum coin.Due to spectrum number
It according to record of the block in frequency spectrum data block chain is certainty and permanent, so network edge mist node only need to be by the frequency
The allocation index upload server for composing block, without frequency spectrum data block is uploaded to cognition Internet of Things cloud, to reduce number
According to transimission and storage expense, the frequency spectrum data block address index that he recognizes Internet of things node foundation cloud can correctly be shared should
Frequency spectrum data.Fig. 4 gives the result of distributed common recognition between leader cluster node in certain emulation, it is seen that Q*The original provided with cluster 2
Beginning frequency spectrum data difference is minimum, therefore cluster 2 is considered as the supplier of new frequency spectrum data block, obtains the reward of frequency spectrum coin.
Step 5, in cluster according to the contribution proportion and quality of frequency spectrum data block, it is automatic to distribute frequency spectrum coin, it is specific as follows:
Inside frequency spectrum data block, sub-block carries out tissue with Merkle tree construction, as shown in figure 5, each spectrum number
It is linked to previous frequency spectrum data block by encryption pointers according to block, it is (original until being linked to first frequency spectrum data block
Block), frequency spectrum data block joins end to end as frequency spectrum data block chain.When new frequency spectrum data block is added into block chain
After formal block, the frequency spectrum coin of cloud storage, which is released into, provides the cluster of the block, and frequency spectrum coin is according to frequency spectrum data block
Contribution proportion and quality be allocated automatically.In step 3, the verifying node of network edge is total to frequency spectrum data
Know verifying, the frequency spectrum data containing data falsification has been removed, and the quality of frequency spectrum data gets a promotion；In step 4, each cluster
Leader cluster node determines the supplier of new frequency spectrum data block by distributed know together, the frequency spectrum data block quilt with minimal error
It is added to frequency spectrum data block chain, by taking Fig. 5 as an example, it is assumed that cluster 2 provides frequency spectrum data sub-block Block112, then cluster 2 is according to institute
Frequency spectrum data sub-block Block is provided112Account for frequency spectrum data block Block1Ratio obtainFrequency spectrum coin, with this
Analogize.
Distributed common recognition mechanism between leader cluster node encourages sensing node to improve frequency spectrum data quality, because being best suitable for frequency
The frequency spectrum block that modal data shares demand can be added into block chain, its supplier is made to obtain frequency spectrum coin.If without spectrum number
According to block by verifying, then the shared failure of frequency spectrum data, frequency spectrum coin, which is retracted into, recognizes Internet of Things cloud server.
It recognizes Internet of Things and frequency spectrum data, i.e. Cloud Server is shared by the three-layer network framework based on mobile edge calculations
Layer, network edge mist node layer and cognition Internet of things node layer, as shown in Figure 6.First, cognition Internet of things node completes frequency first
The pretreatment of modal data, so that the data volume uploaded be made to greatly reduce；Second, the mist server of cognition Internet of Things network edge exists
Network edge carries out the adding procedure of the common recognition verifying and frequency spectrum data block of frequency spectrum data；Third, when new frequency spectrum data area
After block is added to frequency spectrum data block chain, the index of frequency spectrum block is uploaded to cloud, including frequency spectrum data by mist server
The description of block, mist server address, the physical address and public key for recognizing internet of things equipment for participating in common recognition verifying.
Since frequency spectrum data has a localisation features, most of frequency spectrum data it is locally generated, in local use, it is few
The frequency spectrum data use demand of cross-region.Under normal circumstances, cognition Internet of things node is locally using frequency spectrum data, passes through local
Mist server is inquired and downloads required frequency spectrum data；In special circumstances, cognition Internet of things node need to use the spectrum number in strange land
According to filing an application and prestore frequency spectrum coin to cloud server, Cloud Server is according to index matching network apart from nearest verifying section
Point, and frequency spectrum data index is sent to cognition Internet of things node, cognition Internet of things node downloads the public key of the verifying node, verifying
Frequency spectrum data block needed for node cooperation cognition Internet of things node downloading, cognition Internet of things node are completed to download and confirm, be tested
It demonstrate,proves node and obtains the reward of frequency spectrum coin.
Claims (6)
1. a kind of cognition Internet of Things frequency spectrum data sharing method based on block chain, which comprises the following steps:
Step 1, cognition Internet of Things cloud server publication frequency spectrum data share demand, and prestore frequency spectrum coin；
The shared node of step 2, participation frequency spectrum data is spontaneous to form cluster in cognition Internet of Things network edge, acquires frequency spectrum data and is simultaneously packaged
As the frequency spectrum data sub-block added in advance, the mist node of network edge is uploaded to after progress asymmetric encryption；
Step 3, mist node publication frequency spectrum data block verify demand, and the frequency spectrum data sub-block that verifying node verification adds in advance is
The no frequency spectrum data that meets shares demand, is thought if meeting there is no data falsification and wrong data and enters step 4, if discontented
It is sufficient then think that there are data falsification and wrong data, authentication failed of knowing together, the cluster is not involved in the addition of frequency spectrum data block and frequency spectrum
Coin distribution；
The source of pre- addition frequency spectrum data sub-block, the frequency added in advance are determined between step 4, leader cluster node by distributed common recognition
Modal data sub-block is added into frequency spectrum data block chain as formal block；
Step 5, in cluster according to the contribution proportion and quality of frequency spectrum data block, it is automatic to distribute frequency spectrum coin.
2. the cognition Internet of Things frequency spectrum data sharing method according to claim 1 based on block chain, which is characterized in that step
The shared node of participation frequency spectrum data described in rapid 2 is spontaneous to form cluster in cognition Internet of Things network edge, acquires frequency spectrum data and is packaged
As the frequency spectrum data sub-block added in advance, the mist node of network edge is uploaded to after progress asymmetric encryption, specific as follows:
The cognition Internet of things node for participating in the shared demand of frequency spectrum data shares geographic area in frequency spectrum data and spontaneously forms cluster, each
Cluster collects frequency spectrum data comprising multiple sensing nodes and a leader cluster node, sensing node under the leader of leader cluster node, and right
Frequency spectrum data collected carries out distributed common recognition, forms unified frequency spectrum data sub-block, enablesIndicate j-th of cluster i
Sensing node, sensing nodeAs the following formula by the state of itself by xij(k) it is updated to xij(k+1):
Wherein, xij(k) j-th of sensing node for being cluster iIn the state at k moment, xijIt (k+1) is j-th of perception of cluster i
NodeIn the state at k+1 moment；
xin(k) frequency spectrum data for being neighbours' sensing node n, For nodeThe set of neighbours' sensing node,
In:
Indicate nodeDegree, Ω is the maximal degree for recognizing Internet of Things adjacency matrix G, and xij(0)=Dataij, wherein
xijIt (0) is the original state of j-th of sensing node of cluster i, DataijThe local frequency spectrum collected for j-th of sensing node of cluster i
Data；
Sensing node forms unified frequency spectrum data sub-block through excessive wheel iteration in cluster, and then leader cluster node downloading is apart from recently
Edge Server public key, with the public key encryption frequency spectrum data sub-block, and be uploaded to the Edge Server, Edge Server is used
Private key is decrypted to obtain frequency spectrum data sub-block.
3. the cognition Internet of Things frequency spectrum data sharing method according to claim 1 based on block chain, which is characterized in that step
Mist node described in rapid 3 issues frequency spectrum data block and verifies demand, and the frequency spectrum data sub-block that verifying node verification adds in advance is
The no frequency spectrum data that meets shares demand, specific as follows:
Leader cluster node gives verifying node, verifying by the mist nodes sharing of network edge by asymmetric encryption, by frequency spectrum data
Node obtains frequency spectrum data, the adjacency matrix and corresponding frequency of position, cluster including sensing node using the private key decryption of oneself
Then modal data verifies node and carries out common recognition verifying to the frequency spectrum data of pre- addition frequency spectrum data sub-block, according to frequency spectrum data
The information of offer checks the number whether injected containing malicious user in frequency spectrum data in the distributed common recognition locally simulated
According to common recognition verifying is verified data after the completionWith the confidence interval [Δ under 1- α confidence levelmin,Δmax], ifData falsification and wrong data is then not present, frequency spectrum data passes through common recognition verifying；Otherwise, frequency spectrum data is total to
Know authentication failed.
4. the cognition Internet of Things frequency spectrum data sharing method according to claim 1 based on block chain, which is characterized in that step
The source of pre- addition frequency spectrum data sub-block, the frequency added in advance are determined between leader cluster node described in rapid 4 by distributed common recognition
Modal data sub-block, which is added into frequency spectrum data block chain, becomes formal block, specific as follows:
Each cluster leader cluster node obtains common recognition result Q by distributed common recognition*, by Q*With raw spectroscopy data phase provided by each cluster
Than the smallest frequency spectrum data of difference is then the supplier of new frequency spectrum data block, obtains the reward of frequency spectrum coin.
5. the cognition Internet of Things frequency spectrum data sharing method according to claim 1 based on block chain, which is characterized in that step
Contribution proportion and quality described in rapid 5 in cluster according to frequency spectrum data block, automatic distribution frequency spectrum coin are specific as follows:
After new frequency spectrum data block is added into block chain as formal block, the frequency spectrum coin coin of cloud storage is released
To the cluster of the block is provided, frequency spectrum coin is allocated automatically according to the contribution proportion and quality of frequency spectrum data block.
6. the cognition Internet of Things frequency spectrum data sharing method according to claim 1 based on block chain, which is characterized in that step
The distributed common recognition in the local common recognition verifying and step 4 of node between leader cluster node is verified in rapid 3, by recognizing Internet of Things net
The mist node at network edge carries out.
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| CN112422526A (en) * | 2020-11-03 | 2021-02-26 | 山西特信环宇信息技术有限公司 | Cone block chain consensus system, method and network |
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| CN110601780A (en) * | 2019-10-17 | 2019-12-20 | 电子科技大学 | Dynamic spectrum access method based on block chain |
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