CN117880917B - Dynamic self-organizing network method, device, equipment and medium - Google Patents
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Abstract
The invention discloses a dynamic self-organizing network method, a device, equipment and a medium, which relate to the technical field of wireless mobile communication and are used for solving the problems that the existing self-organizing network method ignores network connectivity among nodes, and the distance evaluation is inaccurate, so that the organizing efficiency and the searching efficiency of a network are low. The method includes creating a plurality of nodes in a network to form a network topology: for any node in the network topology: calculating the distance between the current node and other nodes according to the hash value of the current node and the direct connectivity between the current node and other nodes in the network topology structure; updating an initial neighbor list of the current node according to the distance between the current node and other nodes to obtain a target neighbor list corresponding to the current node; and updating the initial neighbor list of all the nodes to complete the network construction. The dynamic self-organizing network method provided by the invention is used for improving the network organization efficiency and the searching efficiency by improving the distance evaluation accuracy.
Description
Technical Field
The present invention relates to the field of wireless mobile communications technologies, and in particular, to a method, an apparatus, a device, and a medium for dynamic ad hoc networks.
Background
An ad hoc network is a network combining mobile communication and computer networks, in which user terminals can move at will while maintaining communication. The self-organizing network can utilize the route forwarding function of the mobile terminal to communicate under the condition of no infrastructure, thereby overcoming the defect that the network-free communication infrastructure can be used. The self-organizing network has the characteristics of no centrality, no peer-to-peer property among nodes, self-discovery, automatic configuration, self-organization, self-healing and the like, can rapidly, accurately and efficiently perform forwarding and route maintenance work of data packets, adapts to rapid change of network topology, reduces introduced extra time delay and control information for maintaining routes, and reduces the cost of a routing protocol so as to meet the limitation of the computing capacity, storage space, power supply and the like of the mobile terminal.
However, the conventional ad hoc network method often ignores network connectivity among nodes, that is, the capability of each node in the network to communicate with each other, resulting in inaccurate distance evaluation during the network construction process, thereby affecting the organization efficiency and search efficiency of the network.
Disclosure of Invention
The invention aims to provide a dynamic self-organizing network method, a device, equipment and a medium, which are used for solving the problems that the existing self-organizing network method ignores network connectivity among nodes, and the distance evaluation is inaccurate, so that the organizing efficiency and the searching efficiency of a network are low.
In order to achieve the above object, the present invention provides the following technical solutions:
in a first aspect, the present invention provides a dynamic ad hoc network method, including:
Creating a plurality of nodes in a network to form a network topology: each of the nodes includes a hash value and an initial neighbor list; the initial neighbor list comprises N random nodes; n is greater than 0;
For any one node in the network topology: according to the hash value of the current node and the direct connectivity between the current node and other nodes in the network topology structure, calculating the distance between the current node and other nodes by adopting an optimized distance evaluation function; the direct connectivity indicates that no other node exists between any two adjacent nodes;
Updating an initial neighbor list of the current node according to the distance between the current node and other nodes to obtain a target neighbor list corresponding to the current node; the target neighbor list is a set of nodes with the distance between the target neighbor list and the current node being smaller than a preset threshold range; the target neighbor list is dynamically updated when a new node is added or the node is offline in the network topology structure;
Updating the initial neighbor list of all nodes to complete network construction; each node in the built network communicates with the nearest node in its corresponding target neighbor list.
Compared with the prior art, the dynamic ad hoc network method provided by the invention comprises the following steps: creating a plurality of nodes in a network to form a network topology: for any node in the network topology: according to the hash value of the current node and the direct connectivity between the current node and other nodes in the network topology structure, calculating the distance between the current node and other nodes by adopting an optimized distance evaluation function, and considering the direct connectivity between the nodes when the distance evaluation is carried out, wherein the calculated distance result can more accurately reflect the actual distance between the nodes; updating an initial neighbor list of the current node according to the distance between the current node and other nodes to obtain a target neighbor list corresponding to the current node, and because the initial neighbor list of the node is updated based on the calculated more accurate distance, the neighbor node closest to each node can be determined, and the node organization efficiency is improved; the target neighbor list is dynamically updated when a new node is added or the node is offline in the network topology structure, so that a dynamic node organization strategy can be realized, and the change of the network scale and the dynamic behavior of the node can be dealt with; each node in the built network communicates with the node closest to the corresponding target neighbor list, and when searching the target node to be communicated, the path searched in the node searching process is shorter, the searching is more accurate and the more efficient node searching can be realized in a large-scale network because the searching direction is guided by using the optimized distance evaluation function.
In a second aspect, the present invention provides a dynamic ad hoc network device comprising:
The node creation module is used for creating a plurality of nodes in the network to form a network topology structure: each of the nodes includes a hash value and an initial neighbor list; the initial neighbor list comprises N random nodes; n is greater than 0;
The inter-node distance calculation module is used for aiming at any node in the network topological structure: according to the hash value of the current node and the direct connectivity between the current node and other nodes in the network topology structure, calculating the distance between the current node and other nodes by adopting an optimized distance evaluation function; the direct connectivity indicates that no other node exists between any two adjacent nodes;
The initial neighbor list updating module is used for updating the initial neighbor list of the current node according to the distance between the current node and other nodes to obtain a target neighbor list corresponding to the current node; the target neighbor list is a set of nodes with the distance between the target neighbor list and the current node being smaller than a preset threshold range; the target neighbor list is dynamically updated when a new node is added or the node is offline in the network topology structure;
The network construction completion module is used for updating the initial neighbor list of all the nodes to complete network construction; each node in the built network communicates with the nearest node in its corresponding target neighbor list.
In a third aspect, the present invention provides a dynamic ad hoc network device comprising:
A communication unit/communication interface for creating a plurality of nodes in a network forming a network topology: each of the nodes includes a hash value and an initial neighbor list; the initial neighbor list comprises N random nodes; n is greater than 0;
A processing unit/processor configured to, for any one node in the network topology: according to the hash value of the current node and the direct connectivity between the current node and other nodes in the network topology structure, calculating the distance between the current node and other nodes by adopting an optimized distance evaluation function; the direct connectivity indicates that no other node exists between any two adjacent nodes;
Updating an initial neighbor list of the current node according to the distance between the current node and other nodes to obtain a target neighbor list corresponding to the current node; the target neighbor list is a set of nodes with the distance between the target neighbor list and the current node being smaller than a preset threshold range; the target neighbor list is dynamically updated when a new node is added or the node is offline in the network topology structure;
Updating the initial neighbor list of all nodes to complete network construction; each node in the built network communicates with the nearest node in its corresponding target neighbor list.
In a fourth aspect, the present invention provides a computer readable storage medium having instructions stored therein that, when executed, implement the dynamic ad hoc network method described above.
Compared with the prior art, the beneficial effects of the device type scheme of the second aspect, the device type scheme of the third aspect and the computer readable storage medium type scheme of the fourth aspect are the same as those of the hybrid block hash encryption method of the above technical solutions, and are not described in detail herein.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
FIG. 1 is a flow chart of a dynamic ad hoc network method provided by the present invention;
Fig. 2 is a schematic structural diagram of a dynamic ad hoc network device according to the present invention;
fig. 3 is a schematic structural diagram of a dynamic ad hoc network device according to the present invention.
Detailed Description
In order to clearly describe the technical solution of the embodiments of the present invention, in the embodiments of the present invention, the words "first", "second", etc. are used to distinguish the same item or similar items having substantially the same function and effect. For example, the first threshold and the second threshold are merely for distinguishing between different thresholds, and are not limited in order. It will be appreciated by those of skill in the art that the words "first," "second," and the like do not limit the amount and order of execution, and that the words "first," "second," and the like do not necessarily differ.
In the present invention, the words "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.
In the present invention, "at least one" means one or more, and "a plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a alone, a and B together, and B alone, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b or c may represent: a, b, c, a and b, a and c, b and c, or a, b and c, wherein a, b, c can be single or multiple.
The existing self-organizing network method generally adopts Euclidean distance and Manhattan distance equidistant evaluation functions to evaluate the distance between nodes, the direct connectivity between the nodes is not considered by the distance evaluation functions, and the calculated distance cannot truly reflect the actual distance between the nodes because the network environment is a complex change process, so that the organizing efficiency and the node searching efficiency of the network are affected.
In order to solve the above problems, the present invention provides a method, apparatus, device and medium for dynamic ad hoc network, in which network connectivity is introduced, an optimized distance evaluation function can more accurately reflect the actual distance between nodes, and then a dynamic node organization policy can cope with the change of network scale and the dynamic behavior of nodes, and finally a search policy based on heuristic function can realize efficient node search in a large-scale network, and the description is given below with reference to the accompanying drawings.
Fig. 1 is a flowchart of a dynamic ad hoc network method provided in the present invention, as shown in fig. 1, the dynamic ad hoc network method includes the following steps:
step 101: creating a plurality of nodes in a network to form a network topology: each of the nodes includes a hash value and an initial neighbor list;
the number of the created nodes is determined according to the requirement, each node is provided with a corresponding unique identifier, and the hash value of the node is obtained by carrying out hash calculation on the unique identifier of the node.
The initial neighbor list includes N random nodes; n is greater than 0; if the number of the created nodes is M, N can be equal to M-1, M-2 and the like, the number of the nodes in the neighbor list is determined according to the requirement, and the neighbor list of the nodes refers to a list of the nodes directly connected with the nodes.
Step 102: for any one node in the network topology: according to the hash value of the current node and the direct connectivity between the current node and other nodes in the network topology structure, calculating the distance between the current node and other nodes by adopting an optimized distance evaluation function;
direct connectivity means that no other node exists between any two adjacent nodes, and the two nodes can directly communicate with each other.
Specifically, the calculating the distance between the current node and the other nodes by using the optimized distance evaluation function includes: performing exclusive-or operation on hash values of two nodes to be calculated to obtain an exclusive-or result;
substituting the exclusive OR result and the direct connectivity of the two nodes to be calculated in the network topology structure into an optimized distance evaluation function formula to obtain the distance between the two nodes to be calculated, wherein the optimized distance evaluation function formula is shown as formula (1):
d(i,j)＝α*H(i,j)+(1-α)*C(i,j)(1)
Wherein d (i, j) represents the distance between two nodes to be calculated, i and j are respectively two nodes to be calculated, H (i, j) is the exclusive OR result corresponding to the two nodes to be calculated, C (i, j) is the direct connectivity of the two nodes to be calculated in the network topology structure, when the direct connectivity between the two nodes is represented by 1, if the direct connectivity is not represented by 0, alpha is a weight parameter, and the value of alpha is greater than 0 and less than 1 and can be dynamically changed.
The optimized distance estimation function is non-negative because both H (i, j) and C (i, j) are non-negative; identity: d (i, i) =0, because H (i, i) =0, c (i, i) =0. Symmetry: d (i, j) =d (j, i) because H (i, j) =h (j, i), C (i, j) =c (j, i). Triangle inequality: for all i, j, k, there is d (i, j) < = d (i, k) +d (k, j).
Step 103: updating an initial neighbor list of the current node according to the distance between the current node and other nodes to obtain a target neighbor list corresponding to the current node;
The step is a process of grouping and organizing the nodes, each node only selects a plurality of nodes closest to the node as neighbors of the node, and the sparsity and the high efficiency of the network can be maintained.
The target neighbor list is a set of N nodes with the distance between the target neighbor list and the current node being smaller than a preset threshold range; the number of the nodes in the target neighbor list can be customized according to the requirement, and the preset threshold range is determined according to the distance between the current node and all other nodes; the target neighbor list is dynamically updated when new nodes join or nodes go offline in the network topology.
As an optional manner, updating the initial neighbor list of the current node according to the distance between the current node and other nodes, and obtaining the target neighbor list of the current node specifically includes:
the distances between the current node and other nodes are ordered in the order from small to large, and an ordered distance set is obtained;
and determining the nodes corresponding to the distances which are concentrated and arranged in the first N distances as nodes in the target neighbor list of the current node. And setting the distance of the row at the Nth as L, and setting the preset threshold range to be smaller than or equal to L.
Step 104: updating the initial neighbor list of all nodes to complete network construction; each node in the built network communicates with the nearest node in its corresponding target neighbor list.
The self-organizing network established is based on a search strategy of a heuristic function, the strategy guides a node search direction by utilizing an optimized distance evaluation function, and specifically, the process of searching for a target communication node for communication through the node after the network establishment is completed comprises the following steps:
determining a first node closest to the initial node according to a target neighbor list of the initial node;
determining a second node closest to the first node according to the target neighbor list of the first node;
And determining the next node closest to the second node according to the target neighbor list of the second node until the target communication node is found, and realizing communication between the starting node and the target communication node.
According to the dynamic ad hoc network method provided by the invention, the distance between the current node and other nodes is calculated by adopting the optimized distance evaluation function, the direct connectivity between the nodes is considered when the distance evaluation is carried out, and the calculated distance result can more accurately reflect the actual distance between the nodes; updating an initial neighbor list of the current node according to the distance between the current node and other nodes to obtain a target neighbor list corresponding to the current node, and because the initial neighbor list of the node is updated based on the calculated more accurate distance, the neighbor node closest to each node can be determined, and the node organization efficiency is improved; the target neighbor list is dynamically updated when a new node is added or the node is offline in the network topology structure, so that a dynamic node organization strategy can be realized, and the change of the network scale and the dynamic behavior of the node can be dealt with; each node in the built network communicates with the node closest to the corresponding target neighbor list, and when searching the target node to be communicated, the optimized distance evaluation function is utilized to guide the searching direction, so that the path searched in the node searching process is shorter, the searching is more accurate, and the more efficient node searching can be realized in the large-scale network.
The network constructed by the scheme has a dynamic processing function, when a new node is added or a node is offline or the weight parameter alpha is changed, the system automatically updates the neighbor list of the related node and carries out node organization again; as an alternative, when a new node is added to the established network, the target neighbor list is dynamically updated including:
Calculating a target distance set between the new node and other nodes in the network topology structure after the new node is added;
And updating the target neighbor list of each node according to the target distance set and the distance between each node in the network topology structure before the new node is added.
As an alternative, when there is an offline node in the built network, the target neighbor list dynamic update includes:
determining a target node containing the offline node in the target neighbor list;
Judging whether the offline node is a node communicating with the target node, if so, deleting the offline node from a target neighbor list of the target node, determining a second node in the target neighbor list as a node closest to the target node, and if not, judging the next target node; the second node is the node closest to the target node in addition to the offline node.
In practice, it is assumed that the network is made up of five nodes: a, B, C, D, E. Each node has a corresponding unique identifier and obtains a unique hash value through a hash operation. In the initial state, the neighbor list of each node is set to be a random group of nodes. Next, the distance between the nodes is evaluated with an optimized distance evaluation function, here set to α to 0.5. And grouping and organizing the nodes based on the optimized distance evaluation function. For example, node a may select two nodes closest and next closest to each other as its new neighbors, such as B and D. When a new node F joins the network, the network automatically updates the neighbor list of the relevant node and reorganizes the nodes. Finally, a search strategy based on a heuristic function is adopted, and the strategy guides the search direction by utilizing the optimized distance evaluation function. For example, the node closest to the node a is searched, and the search range is gradually enlarged until the target node is found after the search is started from the neighboring node of a.
In this scenario, assuming that d (i, j) is a qualified distance function, we can further analyze the efficiency of node organization using d (i, j). This may require designing an algorithm or strategy that can efficiently organize the nodes based on the value of d (i, j). To demonstrate the efficiency of such an organization strategy, we need to define a suitable efficiency index, such as the diameter of the network (the maximum distance between any two nodes). We then need to construct the worst case of the network, calculate the diameter in this case, and prove its relationship to the N nodes.
Efficiency of search strategy in this scheme: assuming we use an algorithm for node searching, we need to demonstrate that its temporal complexity is O (N log N) and spatial complexity is O (N). First, we need to describe the working principle of the algorithm in detail, including its heuristic functions, expansion strategies, etc. Then we need to analyze the time and space consumption of the algorithm in the worst case, resulting in their relationship to the N nodes.
The embodiment of the present invention may perform the division of the functional modules according to the above method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated in one processing unit. The integrated modules may be implemented in hardware or in software functional modules. It should be noted that, in the embodiment of the present invention, the division of the modules is schematic, which is merely a logic function division, and other division manners may be implemented in actual implementation.
Fig. 2 shows a schematic structural diagram of a dynamic ad hoc network device provided in the present invention in the case of dividing each functional module by corresponding each function. As shown in fig. 2, the apparatus includes:
A node creation module 201, configured to create a plurality of nodes in a network to form a network topology: each of the nodes includes a hash value and an initial neighbor list; the initial neighbor list comprises N random nodes; n is greater than 0;
An inter-node distance calculation module 202 of any node, configured to, for any node in the network topology: according to the hash value of the current node and the direct connectivity between the current node and other nodes in the network topology structure, calculating the distance between the current node and other nodes by adopting an optimized distance evaluation function; the direct connectivity indicates that no other node exists between any two adjacent nodes;
An initial neighbor list updating module 203 of any node, configured to update an initial neighbor list of the current node according to a distance between the current node and other nodes, so as to obtain a target neighbor list corresponding to the current node; the target neighbor list is a set of nodes with the distance between the target neighbor list and the current node being smaller than a preset threshold range; the target neighbor list is dynamically updated when a new node is added or the node is offline in the network topology structure;
The initial neighbor list sequential updating module 204 is configured to update the initial neighbor lists of all nodes, and complete network construction; each node in the built network communicates with the nearest node in its corresponding target neighbor list.
Optionally, the inter-node distance calculation module of any node includes:
The hash value calculation unit is used for carrying out exclusive-or operation on the hash values of the two nodes to be calculated to obtain an exclusive-or result;
The distance calculation unit is used for substituting the exclusive or result and the direct connectivity of the two nodes to be calculated in the network topology structure into the following optimized distance evaluation function formula to obtain the distance between the two nodes to be calculated:
d(i,j)＝α*H(i,j)+(1-α)*C(i,j)
wherein d (i, j) represents the distance between two nodes to be calculated, i and j are respectively the two nodes to be calculated, H (i, j) is the exclusive OR result corresponding to the two nodes to be calculated, C (i, j) is the direct connectivity of the two nodes to be calculated in the network topology structure, alpha is a weight parameter, and alpha is more than 0 and less than 1.
Optionally, when a new node is added to the network after the completion of the construction, the dynamic updating of the target neighbor list includes:
Calculating a target distance set between the new node and other nodes in the network topology structure after the new node is added;
And updating the target neighbor list of each node according to the target distance set and the distance between each node in the network topology structure before the new node is added.
Optionally, when an offline node exists in the network after the completion of the construction, the dynamic updating of the target neighbor list includes:
determining a target node containing the offline node in the target neighbor list;
Judging whether the offline node is a node communicating with the target node, if so, deleting the offline node from a target neighbor list of the target node, determining a second node in the target neighbor list as a node closest to the target node, and if not, judging the next target node; the second node is the node closest to the target node in addition to the offline node.
Optionally, the initial neighbor list updating module 203 of the arbitrary node includes:
the sorting unit is used for sorting the distances between the current node and other nodes in order from small to large to obtain a sorted distance set;
And the target neighbor list determining unit is used for determining the nodes corresponding to the distances which are arranged in the sorted distance set in the first N distances as the nodes in the target neighbor list of the current node.
Optionally, the hash value of the node is obtained by performing hash calculation on the unique identifier of the node.
Optionally, the device further includes a node searching module, which may specifically include:
a first node determining unit, configured to determine a first node closest to the starting node according to a target neighbor list of the starting node;
a second node determining unit, configured to determine a second node closest to the first node according to a target neighbor list of the first node;
and the next node determining unit is used for determining the next node closest to the second node according to the target neighbor list of the second node until the target communication node is found, and realizing communication between the starting node and the target communication node.
The above description has been presented mainly in terms of interaction between the modules, and the solution provided by the embodiment of the present invention is described. It is to be understood that, in order to achieve the above-described functions, they comprise corresponding hardware structures and/or software modules that perform the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the case of adopting the corresponding integrated units, fig. 3 shows a schematic structural diagram of a dynamic ad hoc network device provided by the present invention. As shown in fig. 3, the apparatus includes:
A communication unit/communication interface for creating a plurality of nodes in a network forming a network topology: each of the nodes includes a hash value and an initial neighbor list; the initial neighbor list comprises N random nodes; n is greater than 0;
A processing unit/processor configured to, for any one node in the network topology: according to the hash value of the current node and the direct connectivity between the current node and other nodes in the network topology structure, calculating the distance between the current node and other nodes by adopting an optimized distance evaluation function; the direct connectivity indicates that no other node exists between any two adjacent nodes;
Updating an initial neighbor list of the current node according to the distance between the current node and other nodes to obtain a target neighbor list corresponding to the current node; the target neighbor list is a set of nodes with the distance between the target neighbor list and the current node being smaller than a preset threshold range; the target neighbor list is dynamically updated when a new node is added or the node is offline in the network topology structure;
Updating the initial neighbor list of all nodes to complete network construction; each node in the built network communicates with the nearest node in its corresponding target neighbor list.
The processing unit may be a Processor or controller, such as a central processing unit (Central Processing Unit, CPU), general purpose Processor, digital signal Processor (DIGITAL SIGNAL Processor, DSP), application-specific integrated Circuit (ASIC), field programmable gate array (Field Programmable GATE ARRAY, FPGA) or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules and circuits described in connection with this disclosure. The processor may also be a combination that performs the function of a computation, e.g., a combination comprising one or more microprocessors, a combination of a DSP and a microprocessor, and the like. The communication module may be a transceiver, a transceiver circuit, a communication interface, or the like. The memory module may be a memory.
As shown in FIG. 3, the processor may be a general purpose central processing unit (central processing unit, CPU), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the program of the present invention. The communication interface may be one or more. The communication interface may use any transceiver-like device for communicating with other devices or communication networks.
As shown in fig. 3, the terminal device may further include a communication line. The communication line may include a pathway to communicate information between the aforementioned components.
Optionally, as shown in fig. 3, the terminal device may further comprise a memory. The memory is used for storing computer-executable instructions for executing the scheme of the invention, and the processor is used for controlling the execution. The processor is configured to execute computer-executable instructions stored in the memory, thereby implementing the method provided by the embodiment of the invention.
As shown in fig. 3, the memory may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (random access memory, RAM) or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (ELECTRICALLY ERASABLE PROGRAMMABLE READ-only memory, EEPROM), a compact disc read-only memory (compact disc read-only memory) or other optical disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to this. The memory may be stand alone and be coupled to the processor via a communication line. The memory may also be integrated with the processor.
Alternatively, the computer-executable instructions in the embodiments of the present invention may be referred to as application program codes, which are not particularly limited in the embodiments of the present invention.
In a specific implementation, as one embodiment, as shown in FIG. 3, the processor may include one or more CPUs, such as CPU0 and CPU 1in FIG. 3.
In a specific implementation, as an embodiment, as shown in fig. 3, the terminal device may include a plurality of processors, such as the processors in fig. 3. Each of these processors may be a single-core processor or a multi-core processor.
In one aspect, a computer readable storage medium is provided, in which instructions are stored, which when executed, implement a dynamic ad hoc network method as described above.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are performed in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, a terminal, a user equipment, or other programmable apparatus. The computer program or instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer program or instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired or wireless means. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that integrates one or more available media. The usable medium may be a magnetic medium, e.g., floppy disk, hard disk, tape; but also optical media such as digital video discs (digital video disc, DVD); but also semiconductor media such as Solid State Drives (SSDs) STATE DRIVE.
Although the invention is described herein in connection with various embodiments, other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.
Although the invention has been described in connection with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made without departing from the spirit and scope of the invention. Accordingly, the specification and drawings are merely exemplary illustrations of the present invention as defined in the appended claims and are considered to cover any and all modifications, variations, combinations, or equivalents that fall within the scope of the invention. It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. A method of dynamic ad hoc networking comprising:
Creating a plurality of nodes in a network to form a network topology: each of the nodes includes a hash value and an initial neighbor list; the initial neighbor list comprises N random nodes; n is greater than 0;
For any one node in the network topology: according to the hash value of the current node and the direct connectivity between the current node and other nodes in the network topology structure, calculating the distance between the current node and other nodes by adopting an optimized distance evaluation function; the direct connectivity indicates that no other node exists between any two adjacent nodes;
the calculating the distance between the current node and other nodes by adopting the optimized distance evaluation function comprises the following steps: performing exclusive-or operation on hash values of two nodes to be calculated to obtain an exclusive-or result; substituting the exclusive or result and the direct connectivity of the two nodes to be calculated in the network topology structure into the following optimized distance evaluation function formula to obtain the distance between the two nodes to be calculated:
d(i,j)=α*H(i,j)+(1-α)*C(i,j)
Wherein d (i, j) represents the distance between two nodes to be calculated, i and j are respectively two nodes to be calculated, H (i, j) is the exclusive OR result corresponding to the two nodes to be calculated, C (i, j) is the direct connectivity of the two nodes to be calculated in the network topology structure, when the direct connectivity between the two nodes is represented by 1, when the direct connectivity between the two nodes is not represented by 0, alpha is a weight parameter, and alpha is more than 0 and less than 1;
Updating an initial neighbor list of the current node according to the distance between the current node and other nodes to obtain a target neighbor list corresponding to the current node; the target neighbor list is a set of nodes with the distance between the target neighbor list and the current node being smaller than a preset threshold range; the target neighbor list is dynamically updated when a new node is added or the node is offline in the network topology structure;
Updating the initial neighbor list of all nodes to complete network construction; each node in the built network communicates with the nearest node in its corresponding target neighbor list.
2. The method of dynamic ad hoc network according to claim 1, wherein when a new node is added to the built network, the dynamic updating of the target neighbor list comprises:
Calculating a target distance set between the new node and other nodes in the network topology structure after the new node is added;
And updating the target neighbor list of each node according to the target distance set and the distance between each node in the network topology structure before the new node is added.
3. The method of dynamic ad hoc network according to claim 1, wherein when there is an offline node in the built network, the dynamic updating of the target neighbor list comprises:
determining a target node containing the offline node in the target neighbor list;
Judging whether the offline node is a node communicating with the target node, if so, deleting the offline node from a target neighbor list of the target node, determining a second node in the target neighbor list as a node closest to the target node, and if not, judging the next target node; the second node is the node closest to the target node in addition to the offline node.
4. The method of claim 1, wherein updating the initial neighbor list of the current node according to the distance between the current node and the other nodes to obtain the target neighbor list of the current node comprises:
the distances between the current node and other nodes are ordered in the order from small to large, and an ordered distance set is obtained;
and determining the nodes corresponding to the distances which are concentrated and arranged in the first N distances as nodes in the target neighbor list of the current node.
5. The dynamic ad hoc network method of claim 1, wherein said node's hash value is obtained by hashing a unique identifier of the node.
6. The method of dynamic ad hoc network according to claim 1, further comprising, after said completing network construction:
determining a first node closest to the initial node according to a target neighbor list of the initial node;
determining a second node closest to the first node according to the target neighbor list of the first node;
And determining the next node closest to the second node according to the target neighbor list of the second node until the target communication node is found, and realizing communication between the starting node and the target communication node.
7. A dynamic ad hoc network device, comprising:
The node creation module is used for creating a plurality of nodes in the network to form a network topology structure: each of the nodes includes a hash value and an initial neighbor list; the initial neighbor list comprises N random nodes; n is greater than 0;
The inter-node distance calculation module of any node is used for aiming at any node in the network topological structure: according to the hash value of the current node and the direct connectivity between the current node and other nodes in the network topology structure, calculating the distance between the current node and other nodes by adopting an optimized distance evaluation function; the direct connectivity indicates that no other node exists between any two adjacent nodes; the calculating the distance between the current node and other nodes by adopting the optimized distance evaluation function comprises the following steps: performing exclusive-or operation on hash values of two nodes to be calculated to obtain an exclusive-or result; substituting the exclusive or result and the direct connectivity of the two nodes to be calculated in the network topology structure into the following optimized distance evaluation function formula to obtain the distance between the two nodes to be calculated:
d(i,j)=α*H(i,j)+(1-α)*C(i,j)
Wherein d (i, j) represents the distance between two nodes to be calculated, i and j are respectively two nodes to be calculated, H (i, j) is the exclusive OR result corresponding to the two nodes to be calculated, C (i, j) is the direct connectivity of the two nodes to be calculated in the network topology structure, when the direct connectivity between the two nodes is represented by 1, when the direct connectivity between the two nodes is not represented by 0, alpha is a weight parameter, and alpha is more than 0 and less than 1;
The initial neighbor list updating module of any node is used for updating the initial neighbor list of the current node according to the distance between the current node and other nodes to obtain a target neighbor list corresponding to the current node; the target neighbor list is a set of nodes with the distance between the target neighbor list and the current node being smaller than a preset threshold range; the target neighbor list is dynamically updated when a new node is added or the node is offline in the network topology structure;
The initial neighbor list sequential updating module is used for updating the initial neighbor list of all nodes to complete network construction; each node in the built network communicates with the nearest node in its corresponding target neighbor list.
8. A dynamic ad hoc network device, comprising:
A communication unit/communication interface for creating a plurality of nodes in a network forming a network topology: each of the nodes includes a hash value and an initial neighbor list; the initial neighbor list comprises N random nodes; n is greater than 0;
a processing unit/processor configured to, for any one node in the network topology: according to the hash value of the current node and the direct connectivity between the current node and other nodes in the network topology structure, calculating the distance between the current node and other nodes by adopting an optimized distance evaluation function; the direct connectivity indicates that no other node exists between any two adjacent nodes; the calculating the distance between the current node and other nodes by adopting the optimized distance evaluation function comprises the following steps: performing exclusive-or operation on hash values of two nodes to be calculated to obtain an exclusive-or result; substituting the exclusive or result and the direct connectivity of the two nodes to be calculated in the network topology structure into the following optimized distance evaluation function formula to obtain the distance between the two nodes to be calculated:
d(i,j)=α*H(i,j)+(1-α)*C(i,j)
Wherein d (i, j) represents the distance between two nodes to be calculated, i and j are respectively two nodes to be calculated, H (i, j) is the exclusive OR result corresponding to the two nodes to be calculated, C (i, j) is the direct connectivity of the two nodes to be calculated in the network topology structure, when the direct connectivity between the two nodes is represented by 1, when the direct connectivity between the two nodes is not represented by 0, alpha is a weight parameter, and alpha is more than 0 and less than 1;
Updating an initial neighbor list of the current node according to the distance between the current node and other nodes to obtain a target neighbor list corresponding to the current node; the target neighbor list is a set of nodes with the distance between the target neighbor list and the current node being smaller than a preset threshold range; the target neighbor list is dynamically updated when a new node is added or the node is offline in the network topology structure;
Updating the initial neighbor list of all nodes to complete network construction; each node in the built network communicates with the nearest node in its corresponding target neighbor list.
9. A computer readable storage medium having instructions stored therein which, when executed, implement the dynamic ad hoc network method of any one of claims 1-6.
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