CN112671493B - Time transmission quality evaluation method in complex network environment - Google Patents
Time transmission quality evaluation method in complex network environment Download PDFInfo
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Abstract
The invention relates to the field of network time transfer, and discloses a time transfer quality evaluation method in a complex network environment. Firstly, analyzing a network system, calculating average shortest path, degree distribution and betweenness of each node of the network system, and constructing an original data matrix of each node; then calculating the weight of each characteristic quantity, and calculating the weight matrix of the whole weighted network system based on the original data matrix; and finally, constructing a weighted network system, and quantitatively evaluating the quality of time transmission in the network environment. The method can realize accurate evaluation of time transmission quality in a complex network environment, and overcomes the defect that the time synchronization precision of the NTP and the PTP is too coarse by only using microsecond level and sub microsecond level to evaluate respectively.
Description
Technical Field
The invention relates to the field of network time transmission, in particular to a method for evaluating time transmission quality in a complex network environment.
Background
By network, it is meant in practice a collection of nodes and edges, and if the nodes are edge-connected according to a determined rule, the resulting network is referred to as a "rule network". If nodes are connected in a completely random manner, the obtained network is a random network, and if the nodes are connected in a certain (self) organization principle, the nodes evolve into various different networks, namely a complex network.
The importance of network time synchronization is self-evident in the current state of development of networks. NTP and PTP both belong to network time synchronization protocols, and have similarities and differences.
To accommodate the Internet hierarchy, NTP (Network Time Protocol) employs a hierarchical temporal distribution model. The method is suitable for running on a computer and a client/server program and a protocol, and under the basic condition, an NTP client sends out a time request, exchanges time with a time server, and then the client calculates time delay and adjusts time synchronization with the server. In addition to client/server synchronization, NTP also supports broadcast synchronization for peer computers. The NTP time service precision is related to the network condition between the NTP server and the user, the redundant server and different network paths are used for guaranteeing the reliability precision, and the network delay of the wide area network is generally between 10ms and 500 ms; network latency for local area networks is typically less than 1ms with timing operating system kernel processing delays.
Synchronization between master and slave clocks of PTP (Precision Time Protocol ) is accomplished by periodic message exchanges. The slave clock can exchange messages in each period to obtain four time stamps, and the clock deviation and path delay between the master clock and the slave clock can be calculated through the four time stamps. The PTP is different from NTP in that a physical layer chip supporting hardware time stamping is used, meanwhile, an IEEE1588 protocol of an application layer is realized on a control chip such as ARM, and the synchronous precision can reach submicron level.
The network environment is very complex, and is shown in the following steps: the number of network nodes is variable, and can be hundreds of thousands; the dynamic behavior of each node is complex; coupling of network connections; the network connection structure is complex; the space-time evolution of the network is complex. In the present day of the rapid development of network technology and the development of various intelligent tools and methods, the research on complex network environments is set aside to talk about network time synchronization, and only microsecond and submicrosecond are used for respectively evaluating that the time synchronization precision of NTP and PTP is too coarse, so that the method is far from sufficient in the actual network environment time synchronization.
Disclosure of Invention
The invention aims to provide a method for evaluating time transmission quality in a complex network environment.
In order to achieve the above object, the present invention provides the following technical solutions:
the invention provides a time transmission quality evaluation method in a complex network environment, which comprises the following steps:
calculating average shortest path, degree distribution and betweenness of each node of the network system, and constructing an original data matrix of each node;
calculating the weight of each characteristic quantity, and calculating the weight matrix of the whole weighted network system based on the original data matrix;
and constructing a weighted network system, and quantitatively evaluating the quality of time transfer in the network environment.
As an implementation manner, the average path length is an average value of distances between all node pairs in the network, and the calculation manner is that:
where N is the number of network nodes, l ij Is the distance between any two nodes i and j.
Further optionally, when the network belongs to a BA scaleless network, the average path length is:
as an implementation manner, the number of edges connected to a point in the network is called the degree of the point, and let P (k) denote the probability that the degree of any point is k, then { P (k) } is called the degree distribution of the network, and the function of the degree distribution is:
further optionally, for a scaleless network BA model, the network initially has m 0 The nodes are connected in pairs. After which a new node is added every time unit. The new node selects m nodes from the current network to be connected with the new node, and after t time units, the network contains m 0 +mt nodes, m 0 (m 0 -1)/2+mt edges, when t is sufficiently large, the degree distribution calculation method is:
as an implementation manner, the node bets are calculated in the following manner:
in B of i The number g of the node i is the number g mn G is the shortest path number between node m and node n min Is the shortest path number between node m and node n through node i.
As an embodiment, the weight of each feature is calculated by a probabilistic method.
As an implementation manner, the calculation manner of the weight of each feature quantity is as follows:
wherein omega i As the weight of each feature quantity,for the average value of the corresponding evaluation factors, σ i The standard deviation of the corresponding evaluation factors is S i 。
As an implementation manner, the weight matrix of the whole weighted network system is as follows:
wherein Q is a weight matrix of the whole weighted network system, W is a weight matrix, Y n And normalizing the matrix of the original data.
As an implementation manner, the quality of time transfer in the network environment is evaluated by the following formula:
wherein Z is i As target index, q i Is the corresponding weight.
The invention provides a time transmission quality evaluation method in a complex network environment, which comprises the steps of firstly analyzing a network system, calculating average shortest path, degree distribution and node betweenness of the network system, and constructing an original data matrix of each node; then calculating the weight of each characteristic quantity, and calculating the weight matrix of the whole weighted network system based on the original data matrix; and finally, constructing a weighted network system, and quantitatively evaluating the quality of time transmission in the network environment. The method can realize accurate evaluation of time transmission quality in a complex network environment, and overcomes the defect that the time synchronization precision of the NTP and the PTP is too coarse by only using microsecond level and sub microsecond level to evaluate respectively.
Drawings
FIG. 1 is a schematic diagram of a network architecture; wherein (a) a normal network, (b) a weighted network.
Fig. 2 is a flow chart of time transfer quality evaluation in a complex network environment.
Detailed Description
In order to make the technical problems, technical schemes and beneficial effects to be solved more clear, the invention is further described in detail below. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Basic feature quantities describing a complex network are: average path length, cluster coefficients, degree distribution, mesopores, etc. And factors influencing time synchronization in a complex network system are as follows: average shortest distance, maximum degree value of degree distribution and maximum point medium value. As shown in fig. 2, in order to improve network time transfer accuracy, the present invention provides a method for evaluating time transfer quality in a complex network environment, including:
calculating average shortest path, degree distribution and betweenness of each node of the network system, and constructing an original data matrix of each node;
calculating the weight of each characteristic quantity, and calculating the weight matrix of the whole weighted network system based on the original data matrix;
and constructing a weighted network system, and quantitatively evaluating the quality of time transfer in the network environment.
Firstly, the invention calculates the average shortest path, the degree distribution and the betweenness of each node of the network system to construct the original data matrix of each node.
The average shortest path, also called characteristic path length, can have many different definitions of the distance between two nodes, the simplest and most common of which is the number of shortest edges between them. The average path length L of the network is the average of the distances between all pairs of nodes in the network.
Where N is the number of network nodes, l ij Is the distance between any two nodes i and j.
The network we say here belongs to the BA scaleless network, and a large number of demonstration studies indicate that the degree distribution functions are all in the form of power law distribution, and the average path length is:
the degree of a node in a network refers to the number of connection edges that the node has. And respectively counting the number of nodes with the same degree to obtain a distribution diagram with one degree. The distribution of nodes in a network is generally described by a degree distribution function P (k). The degree distribution function P (k) represents the probability that a node is arbitrarily chosen in the network, whose degree is exactly k.
Generally, the greater the degree of a node, the more "important" that node belongs to a critical node in the network.
The degree distribution calculation method of the BA scaleless network comprises the following steps:
this shows that its degree distribution can be approximated by a power law function with a power exponent of 3.
The betweenness of a node is the number of nodes that pass through in all the shortest paths in the network.
In B of i The number g of the node i is the number g mn G is the shortest path number between node m and node n min Is the shortest path number between node m and node n through node i. The bets of a node reflect the impact of that node in the network.
Collecting the original data of the target index, and carrying out standardization processing on the original data to obtain a matrix:
the invention assigns corresponding weight to each link in the network. As an optional implementation manner, the invention calculates the weight of each feature quantity by using a probability method, wherein the probability method formula is as follows:
wherein omega i As the weight of each feature quantity,for the average value of the corresponding evaluation factors, σ i The standard deviation of the corresponding evaluation factors is S i 。
Calculating the average shortest path L, degree distribution P and weight omega of each node betweenness B by the above method L 、ω P Omega, omega B Obtaining a weight matrix W:
and (3) carrying out standardization processing on the original data in the first collecting step, and calculating a weight matrix Q of the whole weighting network system through the following formula.
The invention evaluates the quality of time transfer in the network environment. The normal network (fig. 1 (a)) is weighted to construct a weighted network (fig. 1 (b)). By the formula
And evaluating the quality of time transfer in the network environment. Wherein Z is i As target index, q i Is the corresponding weight.
The method can realize accurate evaluation of time transmission quality in a complex network environment, and overcomes the defect that the time synchronization precision of the NTP and the PTP is too coarse by only using microsecond level and sub microsecond level to evaluate respectively.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within 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 (7)
1. The time transmission quality evaluation method in the complex network environment is characterized by comprising the following steps:
calculating an average shortest path L, a degree distribution P and a node betweenness B of a network system, and constructing an original data matrix of each node;
calculating the weight of each characteristic quantity, and calculating the weight matrix of the whole weighted network system based on the original data matrix;
constructing a weighted network system, and quantitatively evaluating the quality of time transmission in the network environment;
the calculation mode of each characteristic weight value is as follows:
wherein omega i As the weight of each feature quantity,for the average value of the corresponding evaluation factors, σ i The standard deviation of the corresponding evaluation factors is S i ；
The weight matrix of the whole weighted network system is as follows:
wherein Q is a weight matrix of the whole weighted network system, Y N A matrix standardized by the original data is obtained, and W is a weight matrix;
the quality of time transfer in the network environment is evaluated by the following formula:
wherein Z is i As target index, q i Is the corresponding weight.
2. The method for evaluating time transfer quality in a complex network environment according to claim 1, wherein the average shortest path is an average value of distances between all node pairs in the network, and the calculation method is as follows:
where N is the number of network nodes, l ij Is the distance between any two nodes i and j.
3. The method for evaluating time transfer quality in a complex network environment according to claim 1 or 2, wherein when the network belongs to a BA scaleless network, the average shortest path is:
4. the method for evaluating time transfer quality in a complex network environment according to claim 1, wherein the function of the degree distribution is:
where P (k) represents the probability that the degree of any point is k.
5. The method for evaluating time transfer quality in a complex network environment according to claim 1, wherein when the network belongs to a BA scaleless network, the degree distribution calculating method is:
p (k) represents the probability that the degree of any point is k, and N is the number of network nodes.
6. The method for evaluating time transfer quality in a complex network environment according to claim 1, wherein the node betweenness is calculated by:
in B of i The number g of the node i is the number g mn G is the shortest path number between node m and node n min Is the shortest path number between node m and node n through node i.
7. The method for evaluating the quality of time transfer in a complex network environment according to claim 1, wherein the weight of each feature is calculated by a probability method.
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| CN104392094A (en) * | 2014-10-17 | 2015-03-04 | 北京航空航天大学 | Reliability evaluation method of urban road network based on data of floating vehicles |
| CN110046838A (en) * | 2019-05-29 | 2019-07-23 | 西南交通大学 | A kind of rail traffic industrial chain configuration method based on multilayer complex network |
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| CN104392094A (en) * | 2014-10-17 | 2015-03-04 | 北京航空航天大学 | Reliability evaluation method of urban road network based on data of floating vehicles |
| CN110046838A (en) * | 2019-05-29 | 2019-07-23 | 西南交通大学 | A kind of rail traffic industrial chain configuration method based on multilayer complex network |
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