CN111464371A - PSN (packet switched network) time slicing method based on network change degree - Google Patents
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Abstract
The invention discloses a time slicing method of a PSN (packet Switched network) network based on network change degree, which determines a slice size dereferencing range according to the characteristics of the PSN network, then traverses the slice size in the range according to the sampling precision of a data set, obtains the corresponding network change degree by using a network change degree calculation method, and finally, network snapshot sequences generated at time intervals under different network change degrees represent different dynamic characteristics of the network. The invention fully considers the relation of PSN network whole network topology changing along with time, and expresses the changing degree by adopting the network changing degree and constructs a network changing degree-slice size table, thereby effectively expressing the influence of different slice sizes on PSN network slicing.
Description
Technical Field
The invention relates to the technical field of dynamic networks, in particular to a time slicing method of a PSN (packet switched network) based on network change degree.
Background
The PSN Network is a special Delay Tolerant Network (DTN) that has characteristics of DTN Network and also has characteristics of social Network, wherein the nodes are portable devices (e.g. bluetooth) carried by mobile users, and since these devices are carried by human, the nodes in the Network have social characteristics, such as mobile model. The network initially provides network services to mobile users in order to enable network communications without end-to-end connectivity. Nowadays, with the rapid development of portable devices, PSN networks are widely used, for example: the communication between the rescue team and the survivors is restored by realizing the PSN in the disaster; when the user downloads the application, the downloading speed is increased by nearby mobile user data; and the data can be transmitted to the gateway in a more convenient and faster way, and the coverage range of the network is improved. The collected PSN network data is usually an interactive time sequence, i.e., each piece of data represents a pair of node pairs and a state value, and the whole network is a linked flow arranged in time sequence. Since a group of network snapshot sequences are used in a general dynamic network research analysis, it becomes necessary to convert the data in the form of the link stream into the network snapshot sequence, and it is not easy to find a suitable conversion method. The invention finds a suitable conversion method by studying the relationship between the dynamic network change degree and the slice size in the network time slice.
Existing time slicing studies include correlations between variable and non-variable, overlapping and non-overlapping, length, etc. of the slice window size and the apparent network characteristics. In the related art, the time division positions at the time of slicing are determined by methods such as event occurrence, but the slice sizes obtained by these methods are not equal in length and do not overlap, and therefore, these methods are not suitable for studies of PSN networks such as link prediction.
Disclosure of Invention
The invention aims to provide a time slicing method of a PSN (packet switched network) based on network change degree, so as to more effectively mine the structural characteristics of a dynamic network under the condition of meeting some researches on the PSN such as link prediction and the like.
The original data set of the PSN network is a dynamic network in a link flow form, and the research object in general dynamic network research is a dynamic network of a group of network snapshot sequences, so that the conversion of the dynamic network from the link flow form to a group of network snapshots is very important.
The method comprises the steps of firstly, traversing a given slice size range to slice a PSN network, converting a link flow type network into a network snapshot type, using a three-tuple expression to express a network snapshot in each time slice, then defining a key parameter which reflects the dynamic change degree of the network in a short time, namely the change degree of an adjacent network, according to the characteristic that a dynamic network topological structure changes along with time, calculating the change degree of the adjacent network snapshot by adopting a defined adjacent network change degree formula to form an adjacent network change degree sequence, carrying out averaging processing on the sequence to obtain a network change degree value which represents the dynamic change degree of the network, and finally counting all the slice sizes and the corresponding network change degrees by using the network change degree-slice size table. The specific steps of the whole slicing process are as follows:
and S1, determining the value range and the traversal precision of the slice size according to the characteristics of the PSN network data set and the theory related to the personnel movement.
And S2, taking the value of each slice in the value range, converting the dynamic network in the form of the link flow into a group of network snapshot sequences, and calculating the change degree of the adjacent network to obtain a group of adjacent network change degree sequences.
And S3, analyzing the change trend of each group of adjacent network change degree sequences according to a time sequence analysis method, and selecting the adjacent network change degree sequences with similar change trends according to a given filter.
And S4, obtaining the network change degree of the whole network according to the network change degree calculation method of the whole network for the adjacent network change degree sequence selected by the filter.
And S5, generating a network change degree-slice size table according to the calculated slice size and the corresponding network change degree.
The relevant theories of the characteristics of the PSN network data set and the movement of the person in step S1 are specifically as follows:
(1) all nodes in the PSN network form an integral network, and parameters of wireless transmission equipment carried by personnel in each node are the same, and the transmission radius and the discovery capability are the same.
(2) The nodes in the PSN network are wireless nodes carried by people, and therefore include the characteristics of periodicity of people movement, slow movement speed and the like.
The key parameter, which represents the degree of network change in a short time defined in step S2, that is, the degree of network change in the vicinity, specifically is:
the change degree of the adjacent network reflects the change condition of the whole network topology in a short time, and the formula is as follows:
wherein, αiIndicating the ith neighbor network variation value,
showing two adjacent networks GjAnd Gj+1The number of edges in one of the networks, i.e. the edges only exist in GjIn or only in Gj+1Performing the following steps; i Gj∪Gj+1I represents two adjacent networks GjAnd Gj+1The number of all edges present in (i.e. the edge is present at G)jOr in Gj6+1Performing the following steps; m represents the number of adjacent network snapshots.
The filter for screening the adjacent network variation degree sequences with similar variation trends defined in step S3 specifically includes:
the filter is to select the variation degree sequence with the variation characteristics of the variation degree sequence of the same type of adjacent network, so that the accuracy of evaluation is improved while the finally generated evaluation table entries are reduced, and the specific characteristics include variance, stability and the like.
In step S4, the network change degree, which is a key parameter for characterizing the network change degree in the entire data set time range, is specifically:
an index value is needed to evaluate the dynamic change degree of the network in the whole data set, and the calculation formula is as follows:
wherein α represents the corresponding network change degree of the whole network at the time interval, and n represents the number of the adjacent network change degrees in the adjacent network change degree sequence.
The slice evaluation table obtained in step S5 specifically includes:
and generating a slice evaluation table at different time intervals and corresponding network change degrees, wherein each row of the table has the same slice size as the network change degree, the table entries have different slice sizes, and the number of the table entry elements in each row is different. The PSN network in each data set may obtain a table of network variation-slice size, and the result of the table is used as a support for selecting an appropriate slice size to perform a slicing operation on the network.
Compared with the prior art, the method provided by the invention can properly convert the PSN network in the form of the link flow into a group of network snapshot sequences, so that other network research methods taking the network snapshot sequences as research objects have a better research basis, the dynamic characterization effect of the network after slicing under different time intervals is evaluated through the network change degree, and a network change degree-slice size table is constructed, thereby providing support for the subsequent network research analysis.
The method is suitable for the dynamic network related researches such as PSN network visual modeling and link prediction data processing, most of existing network analysis and processing technologies cannot be applied to the PSN network in a link flow form, the PSN network needs to be converted into a network snapshot sequence, the process is also called slicing the network to obtain a time slice sequence, and aiming at the problem, a method for representing the network change degree by adopting the network change degree is provided by mining the change relation between network topologies in adjacent time slices, and the network can be sliced more effectively.
The method comprises the steps of firstly, traversing a given time slice size range to slice a PSN network, converting a link flow type network into a network snapshot type, using a three-tuple expression method to express a network snapshot in each time slice, then defining a key parameter which reflects the dynamic change degree of the network in a short time, namely the change degree of an adjacent network, according to the characteristic that a dynamic network topological structure changes along with time, calculating the change degree of the adjacent network snapshot by adopting a defined adjacent network change degree formula to form an adjacent network change degree sequence, carrying out averaging processing on the sequence which passes through filter inspection to obtain a network change degree value representing the dynamic change degree of the network, and finally counting all time slice sizes and corresponding network change degrees by using a network change degree-slice size table. The invention fully considers the relation of PSN network whole network topology changing along with time, and expresses the changing degree by adopting the network changing degree and constructs a network changing degree-slice size table, thereby effectively expressing the influence of different slice sizes on PSN network slicing.
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The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a diagram of dynamic network link changes in the form of a link flow;
fig. 2 is a schematic representation of slice evaluation.
Detailed Description
The invention provides a method for time slicing of a PSN network based on network change degree. The method is not simple to properly convert the dynamic network from a link flow form into a network snapshot sequence form, and the dynamic change characteristics of the network can be relatively accurately represented by adopting the network change degree to evaluate the conversion result under different slice sizes. The following further description is made with reference to the drawings and the detailed description.
As shown in fig. 1, G ═ G<N,E,T>A network is defined in the form of a link flow, where N is a set of nodes, E is a set of edges, T is a start time and an end time for each edge to exist, and the set DG ═ { G ═ G1.G2,…，GtDefined as a set of network snapshot sequences. In the invention, a proper time interval size is found out through the network change degree to be used as the slice size to convert the network, and the specific steps are as follows:
s1, network slicing processing: the initial parameter setting in the network slicing needs to be set through the characteristics of the PSN network data set and the characteristics of personnel movement, and in practical application, due to the high dynamic property of the PSN network and the periodicity of the personnel movement, the slicing time range can be selected from days, weeks and the like, and the slicing precision can be selected from seconds or minutes.
S2, calculating the change degree of the adjacent network: the calculation of the adjacent network change degree reflects the change situation of the whole network topology in a short time, and the link flow network is divided by the slice size given in the step S1 to obtain a network snapshot sequence, wherein the ith network snapshot of the sequence is GiThen, a neighboring network change degree formula is applied to obtain a neighboring network change degree sequence, wherein the formula is as follows:
wherein, αiIndicating the ith neighbor network variation value,
showing two adjacent networks GjAnd Gj+1Number of edges in only one of the networksAmount, i.e. edge only present at GjIn or only in Gj+1Performing the following steps; i Gj∪Gj+1I represents two adjacent networks GjAnd Gj+1The number of all edges present in (i.e. the edge is present at G)jOr in Gj+1Performing the following steps; m represents the number of selected neighboring network snapshots and may take a value greater than or equal to 2.
S3, selecting the adjacent network variation degree sequence of the same variation characteristics by using a filter: the filter is to select a variation sequence of variation features having the same neighboring network variation, so as to reduce the finally generated evaluation table entries and improve the accuracy of the evaluation, for example: a variance filter which can select a partial sequence with relatively stable adjacent change degree sequence change; the stationarity filter can adopt a unit root inspection method in the field of time sequence analysis to inspect whether a change degree sequence of an adjacent network is stable or not.
S4, calculating the network change degree of the whole network: for a given network, it is necessary to use a value to evaluate its dynamic variation, which is calculated as follows:
wherein α represents the corresponding network change degree of the whole network at the time interval, and n represents the number of the adjacent network change degrees in the adjacent network change degree sequence.
S5, generating a network variation degree-slice size table: as shown in fig. 2, a network variation-slice size table is generated with different slice sizes and corresponding network variations, where each row of the table has a slice size equal to the network variation, the entries have different slice sizes, and the number of entry elements in each row is different. And then, the influence on network evolution analysis under different network change degrees is found out by adopting the conventional link prediction method, and the network evolution of the PSN network can be further researched by using the generated network change degree-slice size table after a result is obtained.
The method can properly convert the PSN network in the form of the link flow into a group of network snapshot sequences, so that other network research methods taking the network snapshot sequences as research objects have better research foundation, the dynamic characterization effect of the network after slicing under different slice sizes is evaluated through the network change degree, and a network change degree-slice size table is constructed, thereby providing support for the subsequent network research analysis.
The method is suitable for the dynamic network related researches such as PSN network visual modeling and link prediction data processing, most of existing network analysis and processing technologies cannot be applied to the PSN network in a link flow form, the PSN network needs to be converted into a network snapshot sequence, the process is also called slicing the network to obtain a time slice sequence, and aiming at the problem, a method for representing the network change degree by adopting the network change degree is provided by mining the change relation between network topologies in adjacent time slices, and the network can be sliced more effectively.
The method comprises the steps of firstly, traversing a given slice size range to slice a PSN network, converting a link flow type network into a network snapshot type, using a three-tuple expression to express a network snapshot in each time slice, then defining a key parameter which reflects the dynamic change degree of the network in a short time, namely the change degree of an adjacent network, according to the characteristic that a dynamic network topological structure changes along with time, calculating the change degree of the adjacent network snapshot by adopting a defined adjacent network change degree formula to form an adjacent network change degree sequence, carrying out averaging processing on the sequence which passes through filter inspection to obtain a network change degree value which represents the dynamic change degree of the network, and finally counting all time slice sizes and corresponding network change degrees by using a network change degree-slice size table. The invention fully considers the relation of PSN network whole network topology changing along with time, and expresses the changing degree by adopting the network changing degree and constructs a network changing degree-slice size table, thereby effectively expressing the influence of different time slice sizes on PSN network slicing, and further selecting proper slice size according to the changing degree, thereby improving the accuracy of PSN network link prediction and providing certain support for PSN network routing decision.
The above-mentioned embodiments only express one or several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (6)
1. A time slicing method of PSN network based on network change degree is characterized in that a value range of slice size is determined according to the characteristics of PSN network, then the slice size in the range is traversed according to the sampling precision of a data set, the corresponding network change degree size is obtained by using a network change degree calculation method, finally, network snapshot sequences generated by the slice sizes under different network change degrees represent different dynamic characteristics of the network, and the whole slicing process specifically comprises the following steps:
s1, determining the value range and the traversal precision of the slice size according to the characteristics of the PSN network data set and the characteristics of personnel movement;
s2, traversing the slice sizes in the value range, taking the value of each slice size, converting the dynamic network in the form of the link flow into a group of network snapshot sequences, and calculating the change degree of the adjacent network to obtain a group of adjacent network change degree sequences;
s3, analyzing the change trend of each group of adjacent network change degree sequences according to a time sequence analysis method, and selecting network change degree sequences with similar change trends according to a defined filter;
s4, obtaining the network change degree of the whole network according to the whole network change degree calculation method for the network change degree sequence selected by the filter;
and S5, generating a network change degree-slice size table according to the calculated slice size and the corresponding network change degree.
2. The method for time slicing of PSN network based on network variation as claimed in claim 1, wherein in step S1, determining the slice size span and traversal accuracy according to the characteristics of PSN network dataset and the characteristics of personnel movement specifically comprises:
(1) all nodes in the PSN form an integral network, and parameters of wireless transmission equipment carried by personnel in each node are the same, and the transmission radius and the discovery capability are the same;
(2) nodes in the PSN network are wireless nodes carried by people and include the characteristics of periodicity of movement and slow movement speed of people.
3. The method for time-slicing the PSN network based on the network variation degree according to claim 1, wherein in step S2, the neighboring network variation degree represents a key parameter of the network variation degree in a short time, specifically:
the adjacent network change degree represents the change condition of the whole network topology in a short time, and the formula is as follows:
wherein, αiRepresents the ith neighbor network variation value, | Gj⊕Gj+1I represents two adjacent networks GjAnd Gj+1The number of edges in one of the networks, i.e. the edges only exist in GjIn or only in Gj+1Performing the following steps; i Gj∪Gj+1I represents two adjacent networks GjAnd Gj+1The number of all edges present in (i.e. the edge is present at G)jOr in Gj+1Performing the following steps; m represents the number of adjacent network snapshots.
4. The method for time-slicing PSN network based on network variation as claimed in claim 1, wherein in step S3, a filter for screening neighboring network variation sequences with similar variation trends is defined, the filter selects variation sequences with variation characteristics of the same neighboring network variation, and the accuracy of evaluation is improved while reducing the last generated evaluation table entries.
5. The method for time-slicing PSN network based on network variation as claimed in claim 1, wherein in step S4, the network variation characterizes key parameters of the network variation degree in the whole data set time range, specifically:
and evaluating the dynamic change degree of the network in the whole data set by using an index value, wherein the calculation formula is as follows:
wherein α represents the corresponding network change degree of the whole network at the time interval, and n represents the number of the adjacent network change degrees in the adjacent network change degree sequence.
6. The method for time-slicing the PSN network based on the network variation degree of claim 1, wherein the step S5 specifically comprises:
generating a network variation-slice size table by using different time intervals and corresponding network variations, wherein each line of the table is the time interval with the same network variation, the table entries are different time interval sizes, the number of table entry elements in each line is different, the PSN network in each data set obtains a network variation-slice size table, and the result of the table is used as a support for selecting a proper slice size to slice the network.
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