CN112383944A - Unmanned aerial vehicle swarm self-adaptive networking method with built-in block chain - Google Patents
Unmanned aerial vehicle swarm self-adaptive networking method with built-in block chain Download PDFInfo
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Abstract
The invention discloses an unmanned aerial vehicle swarm self-adaptive networking method with built-in block chains, which is realized by combining a block chain basic technology, and meanwhile, a global unique identifier is applied to networking transmission. By adopting an equipment identification addressing-based mode, global unique identification is configured for any unmanned aerial vehicle, ground terminal and the like in the swarm network, and any transmission-related operation is closely related to GUID in the whole cluster networking system. In addition, the invention provides an unmanned aerial vehicle swarm ad hoc network mechanism with a built-in block chain, so that the unmanned aerial vehicle network has certain survivability and self-healing functions, topology updating and information sharing of nodes of the whole network can be realized, and the working efficiency and the survival capability of the unmanned aerial vehicle are greatly improved.
Description
Technical Field
The invention relates to the technical field of wireless ad hoc networks and block chains, in particular to an unmanned aerial vehicle swarm adaptive networking method with built-in block chains.
Background
Ad hoc peer-to-peer multihop mobile communication networks, i.e. ad hoc networks, are a special kind of wireless mobile networks. All nodes in the network are equal in position, and any central control node is not required to be arranged. The nodes in the network not only have the functions required by the common mobile terminal, but also have the message forwarding capability. Compared with the common mobile network and fixed network, it has the following characteristics: 1) the Adhoc network has no strict control center, all nodes have equal positions, namely, the Adhoc network is a peer-to-peer network, the nodes can join and leave the network at any time, and the fault of any node does not influence the operation of the whole network and has strong survivability; 2) the arrangement or the expansion of the network does not need to depend on any preset network facility, the nodes coordinate respective behaviors through a layered protocol and a distributed algorithm, and the nodes can quickly and automatically form an independent network after being started; 3) when a node is to communicate with nodes that are out of its coverage, multi-hop forwarding by intermediate nodes is required. Unlike multihop of fixed networks, multihop routing in an Adhoc network is performed by ordinary network nodes, not by dedicated routing devices (e.g., routers); 4) the network topology changes dynamically, and the network node can move anywhere and can be started and shut down at any time. The above characteristics make Ad hoc networks significantly different from ordinary cellular mobile communication networks and fixed communication networks in architecture, network organization, protocol design, and the like.
The unmanned aerial vehicle networking has the characteristics of wide coverage, high node moving speed, limited load capacity, unbalanced load data flow distribution and the like, so that the routing technology used in the ground network cannot be directly applied to the unmanned aerial vehicle networking. Therefore, it is necessary to develop networking technologies suitable for drones.
Disclosure of Invention
The invention aims to provide an unmanned aerial vehicle swarm adaptive networking method with built-in block chains, which is combined with a block chain basic technology to realize unmanned aerial vehicle swarm adaptive networking with built-in block chains and is matched with an unmanned aerial vehicle swarm dynamic networking mechanism according to identifiers to improve the working efficiency of an unmanned aerial vehicle.
The purpose of the invention is realized by the following technical scheme:
an unmanned aerial vehicle swarm adaptive networking method with built-in blockchains comprises the following steps:
marking unmanned aerial vehicle nodes of each built-in block chain by using a global unique identifier GUID;
the method comprises the steps that a plurality of GUIDs are stored in a block chain in advance, when a certain unmanned aerial vehicle node is expected to be accessed to a network, whether the GUID of the unmanned aerial vehicle node expected to be accessed is stored in the block chain is verified, and if yes, the unmanned aerial vehicle node is allowed to be accessed to the network;
each unmanned aerial vehicle node in the network has a corresponding safety attribute value, and is stored in a block chain, the safety attribute value of the unmanned aerial vehicle node is periodically determined according to a block chain consensus algorithm, each unmanned aerial vehicle node periodically sends a route learning packet to surrounding neighbors through a wireless link, each unmanned aerial vehicle node calculates link quality through the route learning packet of the neighboring node and the corresponding safety attribute value, and therefore when data are transmitted, the unmanned aerial vehicle node with higher link quality is selected as a next node, and routing information is updated.
The technical scheme provided by the invention can be seen that the self-adaptive networking of the unmanned aerial vehicle swarm with the built-in block chain is realized by combining the basic technology of the block chain, and meanwhile, the Globally Unique Identifier (GUID) is applied to networking transmission. By adopting an equipment identification addressing-based mode, Global Unique Identification (GUID) is configured for any unmanned aerial vehicle, ground terminal and the like in the swarm network, and any transmission-related operation is closely related to the GUID in the whole cluster networking system. In addition, the invention provides an unmanned aerial vehicle swarm ad hoc network mechanism with a built-in block chain, so that the unmanned aerial vehicle network has certain survivability and self-healing functions, topology updating and information sharing of nodes of the whole network can be realized, and the working efficiency and the survival capability of the unmanned aerial vehicle are greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a flowchart of an unmanned aerial vehicle swarm adaptive networking method with built-in blockchains according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an unmanned aerial vehicle ad hoc network system model provided by an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
A Globally Unique Identifier (GUID) is a numeric Identifier of 128 bits in binary length generated by an algorithm. GUIDs are used primarily in networks or systems having multiple nodes, multiple computers. Ideally, no computer or cluster of computers will generate two identical GUIDs. The total number of GUIDs reaches 2^128(3.4 x 10^38), so the probability of randomly generating two identical GUIDs is very small, but not 0. Therefore, the algorithm used to generate the GUID typically adds a non-random parameter (e.g., time) to ensure that such duplication does not occur. Due to the high dynamics of the drone swarm, the traditional addressing approach based on IP addresses can cause high latency, while reducing quality of service. And a device identification addressing-based mode (any transmission-related operation in the whole cluster networking system is closely related to the GUID) is adopted, and a globally unique identifier is configured for each unmanned aerial vehicle node, so that the method can be well adapted to a dynamic environment.
In addition, the block chain is a chain data structure formed by combining data blocks in a sequential connection mode according to a time sequence, a distributed decentralized digital account book which is not falsifiable and counterfeitable is ensured in a cryptographic mode, and data which are in a sequential relation and can be verified in a system can be safely stored. The block chain verifies and stores data by using a block chain type data structure, generates and updates blocks by using a distributed node consensus algorithm, and programs and operates the data by using an intelligent contract.
In the embodiment of the present invention, an unmanned aerial vehicle swarm adaptive networking with built-in blockchains is implemented by combining with a blockchain basic technology, as shown in fig. 1, the method mainly includes:
1. and marking the unmanned aerial vehicle nodes of each built-in block chain by adopting a globally unique identifier GUID.
In the embodiment of the invention, a Globally Unique Identifier (GUID) is introduced as identity information of the unmanned aerial vehicle nodes, and different unmanned aerial vehicle nodes are marked.
As shown in table 1, the GUID includes five fields: manufacturer, delivery time, type, number, and public key. The manufacturer and the delivery time are used for managing and maintaining the unmanned aerial vehicle nodes, the type represents the type of the unmanned aerial vehicle node, and the number is a unique number and is used for identifying each unmanned aerial vehicle node; the unmanned aerial vehicle node obtains a key pair through an encryption algorithm, wherein one key pair is public to the outside and is called a public key, the other key pair is reserved by the unmanned aerial vehicle node and is called a private key, and the key pair obtained through the encryption algorithm is unique worldwide. When using this key pair, if one of the keys is used to encrypt a piece of data, the other key must be used to decrypt the piece of data. If the data is encrypted by the public key, the data must be decrypted by the private key, and if the data is encrypted by the private key, the data must also be decrypted by the public key (namely, a digital signature), otherwise the decryption will not be successful.
| Manufacturer(s) | Time of delivery | Type (B) | Numbering | Public key |
TABLE 1 GUID Format
2. The method comprises the steps that a plurality of GUIDs are stored in a block chain in advance, when a certain unmanned aerial vehicle node is expected to be accessed to a network, whether the GUID of the unmanned aerial vehicle node expected to be accessed is stored in the block chain is verified, and if yes, the network is allowed to be accessed.
In the embodiment of the invention, the access authentication of the unmanned aerial vehicle node is realized based on the GUID, and the GUID is mainly used for verifying the identity information of the unmanned aerial vehicle node newly accessed to the swarm. The block chain stores the GUID of each drone node. Unmanned aerial vehicles with different functions all have their GUIDs as identifiers of the unmanned aerial vehicle swarm ad hoc network. The GUID has the self-certification capability, namely, the verification node does not need external authority, and whether the node belongs to the swarm in advance can be verified through the GUID of the new node, so that the authentication and the safety of the network are ensured. For example, when a new drone node wants to access a stable drone blockchain network, the new drone node first broadcasts its GUID information, and at this time, the drone swarm will check the key and model information of the new drone node trying to access, and compare the GUIDs in the blockchain to check whether it can join the drone swarm. A new drone node can be allowed to join the cluster if and only if it holds the correct GUID information.
In the embodiment of the invention, the GUID is also used for data transmission, when an unmanned aerial vehicle node A1 in the network transmits a message, the message is signed by using a private key of the unmanned aerial vehicle node A1, other unmanned aerial vehicle nodes verify the message by retrieving the public key of the unmanned aerial vehicle node A1 in a block chain, and whether the message is sent by the unmanned aerial vehicle node in the network is verified; the GUID is also used for block verification, when a block is generated by the drone node a2 in the network, the block needs to be signed and broadcast by a private key of the drone node a2, and other drone nodes can link a new block into the local block chain only after verifying the validity of the block by retrieving the public key of the drone node a2 in the block chain.
By introducing the block chain, identity information of each node in the unmanned aerial vehicle swarm can be guaranteed to be not falsifiable or counterfeitable; by introducing the GUID, safe joining of the unmanned aerial vehicle swarm nodes can be realized, and self-adaptive dynamic updating of the swarm is completed.
3. Each unmanned aerial vehicle node in the network has a corresponding safety attribute value, and is stored in a block chain, the safety attribute value of the unmanned aerial vehicle node is periodically determined according to a block chain consensus algorithm, each unmanned aerial vehicle node periodically sends a route learning packet to surrounding neighbors through a wireless link, each unmanned aerial vehicle node calculates link quality through the route learning packet of the neighboring node and the corresponding safety attribute value, and therefore when data are transmitted, the unmanned aerial vehicle node with higher link quality is selected as the next node.
Since the Ad hoc network is a distributed multi-hop wireless network, and nodes can enter and exit the network at any time due to the mobile characteristics of the Ad hoc network, the characteristics are very suitable for the current unmanned plane swarm. The novel mobile wireless network formed by the unmanned aerial vehicle nodes is called an unmanned aerial vehicle Ad hoc network. Generally, there are dozens to dozens of unmanned aerial vehicle nodes in an Ad hoc network of unmanned aerial vehicles, and these unmanned aerial vehicles all have a relay communication function, so each unmanned aerial vehicle is equivalent to a router and has its own wireless transceiver. In addition, the existing unmanned aerial vehicle has high processing capacity, and the unmanned aerial vehicles can share information and make quick response to the information through an Ad hoc network of the unmanned aerial vehicle. The Ad hoc network of the unmanned aerial vehicle formed after networking has the fighting capacity incomparable with that of a single unmanned aerial vehicle.
Unmanned aerial vehicle node in the network has router and two kinds of functions in the terminal concurrently, can remove wantonly according to the demand, freely joins in or leaves the network through GUID. In view of the specific working environment, the communication capacity of the drone nodes in the network is limited, so that communication between nodes at a longer distance needs to be forwarded by means of other drone nodes. Through built-in block chain, the unmanned aerial vehicle ad hoc network system can save important networking information in the block chain, and avoid being tampered or destroyed by malicious unmanned aerial vehicle. And due to the distributed characteristic of the block chain, the unmanned aerial vehicle swarm network can realize convenient information sharing. In addition, the damage of few unmanned aerial vehicle nodes in the bee colony can not influence the whole network, and other normal unmanned aerial vehicle nodes still keep complete block chains. Therefore, the multi-hop self-organizing network with the built-in block chains has certain survivability and self-healing functions, topology updating and information sharing of nodes of the whole network can be achieved, and the working efficiency and the survival capacity of the unmanned aerial vehicle are greatly improved.
In the embodiment of the present invention, a security attribute evaluation mechanism and a dynamic route learning mechanism are set in a network, and mainly described as follows:
1) a security attribute evaluation mechanism.
Every node all has a security attribute value in the unmanned aerial vehicle bee colony, and this value has characterized the degree of safety of node, and the security attribute value is higher, and the degree of safety is higher. In the embodiment of the invention, each unmanned aerial vehicle node locally maintains a block chain, the longest legal chain in the block chains is the longest legal chain of the whole unmanned aerial vehicle cluster, the local block chain of each unmanned aerial vehicle node can be updated towards the longest legal chain of the unmanned aerial vehicle cluster, and the longest legal chain has the security attribute values of all the unmanned aerial vehicle nodes.
At the initial moment, the security attribute values of each unmanned aerial vehicle node in the network are consistent, the security attribute values are updated once after each block update period, and when the PoW is adopted as a block chain consensus algorithm, the security attribute update rule is as follows: if the unmanned aerial vehicle node successfully generates a block, the safety attribute is increased; if the unmanned aerial vehicle node does not generate the block, the security attribute is unchanged.
The drone node that generates the tile, because it is willing to consume its own resources, tends to believe it is a secure node, thereby increasing its security attributes. The updated security attributes will be stored in the blockchain for subsequent dynamic route learning.
2) A dynamic route learning mechanism.
The unmanned aerial vehicle cluster moves at a high speed, and the link state and the network topology change rapidly. Meanwhile, extra security guarantee is needed for unmanned aerial vehicle cluster data transmission, so that the traditional route learning mechanism is no longer suitable for unmanned aerial vehicle swarm, and dynamic route learning is needed. The invention adopts each unmanned aerial vehicle node to independently send the route learning packet to assist in realizing the rapid dynamic networking, including the link state acquisition and the route information updating.
Each drone node in the drone swarm network periodically Sends Route Learning (SRLM) packets to surrounding neighbors over wireless links. And when the unmanned aerial vehicle node receives the SRLM learning packet through the wireless link, counting and evaluating the quality of each link according to the link information in the learning packet. The link quality is determined by the packet loss rate of the node, and the formula for calculating the link quality by the current unmanned aerial vehicle node is as follows:
TQ＝(1-α)×SECURITY_B
wherein α represents a packet loss rate between the current unmanned aerial vehicle node and the unmanned aerial vehicle node B, and is determined by a received route learning packet of the unmanned aerial vehicle node B; SECURITY _ B represents the SECURITY attribute value of drone node B, stored in the local block chain with the current drone node.
The current unmanned aerial vehicle node determines the next hop node of the current unmanned aerial vehicle node by comparing the TQ values of other unmanned aerial vehicle nodes, and then updates the routing information of the current unmanned aerial vehicle node. Through the mechanism, the unmanned aerial vehicle node selects a link with low packet loss rate and high next hop node safety attribute, so that the reliability and safety of data transmission are ensured.
Through the mechanism, the unmanned aerial vehicle bee colony can realize safe and reliable's self-adaptation network deployment, and built-in block chain makes the bee colony system have the advantage that data sharing is more convenient, data transmission is more reliable, data information is safer.
As shown in fig. 2, an unmanned aerial vehicle ad hoc network system model is provided; the packet delivery rate and SECURITY value between the nodes of each drone are shown in table 2.
TABLE 2 packet delivery rates and SECURITY values between unmanned aerial vehicle nodes
If the unmanned aerial vehicle node v1 wants to communicate with the unmanned aerial vehicle node v8, the optimal next hop in the transmission link is sequentially found according to the dynamic routing update rule, so that a complete transmission link is obtained. The main process comprises the following steps:
1) the unmanned plane node v1 sends learning packets to three adjacent nodes, and three TQ values are calculated to be TQ respectively12＝8.1,TQ13＝7.2,TQ14Obtaining an optimal next hop of the unmanned plane node v1 as an unmanned plane node v 2; the optimal next hop for drone node v2 is drone node v 5.
2) The unmanned plane node v5 sends learning packets to two adjacent nodes, and two TQ values are calculated and are TQ respectively54＝5.6,TQ57Obtaining an optimal next hop of the unmanned plane node v5 as an unmanned plane node v 7; the optimal next hop for drone node v7 is drone node v 8.
3) The optimal path of the unmanned aerial vehicle nodes v1-v8 obtained according to the process is v1-v2-v5-v7-v 8.
If the node unmanned aerial vehicle node v2 breaks down in unmanned aerial vehicle networking at a certain moment, so that the data packet delivery rate between the unmanned aerial vehicle nodes v1-v2 is reduced to 0, at the moment, the dynamic routing updating rule can automatically update the communication links between the unmanned aerial vehicle nodes v1-v8, and the communication links are automatically switched to the paths v1-v3-v6-v8, so that normal communication between the nodes is ensured.
Through the above description of the embodiments, it is clear to those skilled in the art that the above embodiments can be implemented by software, and can also be implemented by software plus a necessary general hardware platform. With this understanding, the technical solutions of the embodiments can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.), and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods according to the embodiments of the present invention.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (5)
1. An unmanned aerial vehicle swarm adaptive networking method with built-in block chains is characterized by comprising the following steps:
marking unmanned aerial vehicle nodes of each built-in block chain by using a global unique identifier GUID;
the method comprises the steps that a plurality of GUIDs are stored in a block chain in advance, when a certain unmanned aerial vehicle node is expected to be accessed to a network, whether the GUID of the unmanned aerial vehicle node expected to be accessed is stored in the block chain is verified, and if yes, the unmanned aerial vehicle node is allowed to be accessed to the network;
each unmanned aerial vehicle node in the network has a corresponding safety attribute value, and is stored in a block chain, the safety attribute value of the unmanned aerial vehicle node is periodically determined according to a block chain consensus algorithm, each unmanned aerial vehicle node periodically sends a route learning packet to surrounding neighbors through a wireless link, each unmanned aerial vehicle node calculates link quality through the route learning packet of the neighboring node and the corresponding safety attribute value, and therefore when data are transmitted, the unmanned aerial vehicle node with higher link quality is selected as a next node, and routing information is updated.
2. The method of claim 1, wherein the GUID comprises five fields: manufacturer, delivery time, type, number and public key; the manufacturer and the delivery time are used for managing and maintaining the unmanned aerial vehicle nodes, the type represents the type of the unmanned aerial vehicle node, and the number is a unique number and is used for identifying each unmanned aerial vehicle node; the unmanned aerial vehicle node obtains a key pair through an encryption algorithm, wherein one key pair is public to the outside and is called a public key, and the other key pair is reserved and is called a private key.
3. The drone swarm adaptive networking method of the built-in blockchain of claim 1, wherein the GUID is also used for data transmission, when a drone node a1 in the network transmits a message, the message is signed by its own private key, and other drone nodes verify the message by retrieving the public key of the drone node a1 in the blockchain, verifying whether the message is sent by the drone node in the network; the GUID is also used for block verification, when a block is generated by the drone node a2 in the network, the block needs to be signed and broadcast by a private key of the drone node a2, and other drone nodes can link a new block into the local block chain only after verifying the validity of the block by retrieving the public key of the drone node a2 in the block chain.
4. The adaptive swarm networking method for unmanned aerial vehicles with built-in blockchains according to claim 1, wherein at an initial time, the security attribute value of each unmanned aerial vehicle node in the network is consistent, and thereafter, the security attribute value is updated once every blockchain update period, and when PoW is used as the blockchain consensus algorithm, the security attribute update rule is as follows: if the unmanned aerial vehicle node successfully generates a block, the safety attribute is increased; if the unmanned aerial vehicle node does not generate the block, the security attribute is unchanged.
5. The drone swarm adaptive networking method of the built-in blockchain according to claim 1, wherein the formula for the current drone node to calculate the link quality is:
TQ＝(1-α)×SECURITY_B
wherein α represents a packet loss rate between the current unmanned aerial vehicle node and the unmanned aerial vehicle node B, and is determined by a received route learning packet of the unmanned aerial vehicle node B; SECURITY _ B represents the SECURITY attribute value of drone node B, stored in the local block chain with the current drone node.
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| Bhosle et al. | Applying security to data using symmetric encryption in MANET | |
| Qabajeh et al. | A more secure and scalable routing protocol for mobile ad hoc networks | |
| Walid et al. | Trust security mechanism for maritime wireless sensor networks | |
| Panday et al. | A Review on security Issues of AODV routing protocol for MANETs | |
| Lakhlef et al. | A Secure permutation routing protocol in multi-hop wireless sensor networks | |
| Araghi et al. | A survey for prevention of black hole attacks in wireless mobile adhoc networks using cryptographic techniques | |
| Malik et al. | Security Feature in MANETs–A Review | |
| Lalli et al. | Intrusion detection for MANET to detect unknown attacks using genetic algorithm | |
| Alsafwani et al. | Evaluation of the Mobile Ad Hoc Network (MANET) for Wormhole Attacks using Qualnet Simulator | |
| Dureja et al. | Comparative Study Of Collaborative Attacks & Security Mechanisms In Manet | |
| Kumar et al. | Efficient and secure trust based Ad Hoc routing in MANET | |
| Khanna et al. | Security Concerns and Remedial Measures in MANETs Using Intrusion Detection | |
| Mulugeta et al. | Secures geographic forwarding in wireless multimedia sensor Networks | |
| Dinesh Ram Kumar et al. | Exploiting Multiple Paths in Multi-hop Co-operative Ad-Hoc Networks for Providing Security without Trusted Third Party | |
| Raja et al. | Secured Routing Authentication with Node Isolation in Mobile Adhoc Network | |
| Komninos et al. | Security for ad hoc networks |
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