CN112819048B - Distributed community detection method for inter-satellite dynamic network - Google Patents
Distributed community detection method for inter-satellite dynamic network Download PDFInfo
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Abstract
The invention relates to a distributed community detection method for an inter-satellite dynamic network, which comprises the following steps: a. setting all the spacecrafts as a single-node community, and setting the similarity between corresponding nodes of all the spacecrafts as 0; b. calculating the similarity between corresponding nodes of each spacecraft, and setting a judging threshold according to the maximum value of the similarity; c. and comparing the similarity with a judgment threshold value, and updating the community according to a comparison result. The method for calculating the similarity between the spacecraft and other spacecrafts in a distributed manner has small calculation amount, can effectively solve the problem of rapid topology change of the spacecraft communication network, and can rapidly and accurately detect communities.
Description
Technical Field
The invention relates to a distributed community detection method for an inter-satellite dynamic network.
Background
With the increasing maturity of spacecraft launching technology, a large number of spacecrafts are deployed, and related scholars begin to study the autonomous generation of information, task allocation and execution through the spacecrafts, so as to realize the intellectualization of the space-based system. While the ability to share information among all spacecraft is a precondition for achieving system optimization.
In a space network consisting of spacecraft, the geometric topology between nodes is in dynamic change due to the constraint of orbital motion. Therefore, when the routing between the spatial network nodes is performed, the routing table cannot be directly established for performing the end-to-end information transmission like the conventional communication mode. The characteristics of the space network lead to complex routing and high communication cost. It is found that the routing algorithm can be designed based on the prior knowledge of the network structure to effectively solve the problem. The method comprises a routing algorithm based on a network community structure, wherein the algorithm is based on the characteristics of the network between communities and in communities, and different routing algorithms are respectively adopted, so that a better routing result is achieved.
In the prior art, most community detection algorithms are applied to community detection in a static network or community detection with less variation of core members in a dynamic community. Related community detection generally requires a large amount of computation, once community detection is completed, the whole community is not changed greatly, and connectivity in the same community is based on time change and cannot be always used as a static diagram to design a route. Moreover, the traditional community detection method mainly depends on a centralized algorithm, and cannot be applied to a rapidly-changing inter-satellite network.
Disclosure of Invention
The invention aims to provide a distributed community detection method for an inter-satellite dynamic network.
In order to achieve the above object, the present invention provides a distributed community detection method for an inter-satellite dynamic network, comprising the steps of:
a. setting all the spacecrafts as a single-node community, and setting the similarity between corresponding nodes of all the spacecrafts as 0;
b. calculating the similarity between corresponding nodes of each spacecraft, and setting a judging threshold according to the maximum value of the similarity;
c. and comparing the similarity with a judgment threshold value, and updating the community according to a comparison result.
According to one aspect of the present invention, in the step (b), if the similarity attenuation coefficient is set to ω, the similarity f between the node i and the node j at the time t i，j (t) is:
wherein the similarity attenuation coefficient ω satisfies: 0< omega < 1.
According to one aspect of the invention, if node i and node j remain connected all the time, then the similarity f of both i，j (t) is:
f i，j (t)＝1+f i，j (t-1)·ω；
maximum value max f of similarity i，j (t)]The method comprises the following steps:
max[f i，j (t)]＝1+ω+ω 2 +ω 3 ……；
maximum value max f of similarity i，j (t)]Always smaller thanNamely:
according to one aspect of the invention, if node i and node j are not connected at time t, then the similarity f of the two i，j (t) is:
f i，j (t)＝f i，j (t-1)·ω；
as a result of:
therefore:
according to one aspect of the present invention, setting the determination threshold λ is:
according to one aspect of the invention, when t=kt (k=1, 2, 3.), a community update is performed with an update policy of:
f i，j (t) is more than or equal to lambda, and the node i and the node j are classified into the same community;
f i，j (t) < lambda, then nodes i and j are classified into different communities;
wherein T is the community update period, and k is the kth update time.
According to one aspect of the invention, when node i is in the same community as node j, node j is in the same community as node p, node i is classified as the same community as node p.
According to one aspect of the invention, the similarity decay coefficient ω satisfies: omega > 0.8.
According to one aspect of the invention, in said step (c), each community determines a community ID based on the largest or smallest spacecraft number therein.
According to one aspect of the present invention, in the step (c), after all communities are updated, the step (b) is returned to perform similarity calculation again.
According to the conception of the invention, the respective similarity calculation is carried out on the spacecraft, and then the similarity judgment threshold value is determined according to the maximum value of the similarity calculation result. And comparing all calculated similarities with a judgment threshold, and merging the communities into the same community when the calculated similarities are higher than the judgment threshold, otherwise, dividing the communities into different communities. In this way, autonomous community detection is realized through distributed computation similarity of corresponding nodes of each spacecraft. So that the calculation amount is small and the method can be suitable for the inter-satellite network with rapid change.
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FIG. 1 schematically shows a flow chart of a distributed community detection method for an inter-satellite dynamic network according to one embodiment of the invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
The present invention will be described in detail below with reference to the drawings and the specific embodiments, which are not described in detail herein, but the embodiments of the present invention are not limited to the following embodiments.
Referring to fig. 1, the distributed community detection method for the inter-satellite dynamic network is applicable to communication of a distributed heterogeneous space-based system, and aims to provide a reliable network community structure for a routing algorithm. According to the conception of the invention, firstly, the spacecraft calculates the similarity between the spacecraft and all other spacecrafts by using a distributed method. And, the maximum value of these similarities is calculated, and the determination threshold is set using the maximum value of the similarities. Whenever a community update time is reached, the spacecraft synchronously performs a community update according to the comparison result of the calculated similarity and the decision threshold, and updates the community ID accordingly (synchronously with the community update). Therefore, the invention realizes smaller calculated amount in a distributed mode, can effectively solve the problem of rapid topology change of the spacecraft communication network, and rapidly and accurately detects communities.
Specifically, the method firstly initializes the spacecrafts, and sets all the spacecrafts as a single-node community, namely, only a single node exists in the community. And the similarity between the spacecraft (corresponding nodes) is set to 0. In addition, the period of community update may be set to be T, and the decision threshold λ is set to be:
where ω is the similarity decay coefficient.
Taking a node i and a node j corresponding to two spacecrafts as examples, the similarity (evaluation value) f of the two at time t i，j (t) may be calculated by the following distributed algorithm:
wherein the similarity attenuation coefficient ω satisfies: 0< omega < 1.
Equation (1) characterizes node i as connected to node j at time t, and equation (2) characterizes node i as not connected to node j at time t.
The above-mentioned decision threshold lambda is set based on the fact that the above-mentioned concept according to the present invention shows that the similarity decision threshold is determined based on the maximum value of the similarity. Thus, the maximum value of the similarity can be expressed as max [ f i，j (t)]. If node i and node j remain connected all the time, the similarity f of the two i，j (t) is:
f i，j (t)＝1+f i，j (t-1)·ω；
maximum value max f of similarity i，j (t)]The method comprises the following steps:
max[f i，j (t)]＝1+ω+ω 2 +ω 3 ......；
from this, it can be seen from the principle of the sum of the arithmetic series that the maximum value max f of the similarity i，j (t)]Always smaller thanNamely:
it can be seen that even if two different nodes remain connected for a longer period of time, the similarity of the two nodes is always smaller than an upper limit value.
At the update time, if node i and node j are not connected, the similarity f of the two is the same i，j (t) is:
f i，j (t)＝f i，j (t-1)·ω；
and because the maximum value of the similarity is always smaller thanThen:
and then can be derived:
thus, node i and node j are not directly drawn into the same community. Thus, according to the present invention, the above-mentioned selection judgment threshold value isAt the time of updating, it can be ensured that the sameNodes within the community have connectivity and can update the community and the community ID synchronously.
In addition, the longer the connection time between nodes, the higher the similarity, and conversely, the similarity between the nodes is also attenuated as the nodes are disconnected for a long time. Therefore, when the omega value is close to 1, the decision threshold is larger, namely two nodes need to be connected for a long time to be classified into the same community; the closer the ω value is to 0, the smaller the decision threshold, i.e., the two nodes need only have a short time to connect to be included in the same community. However, since the purpose of the community detection is to be able to route nodes in the community as a static graph, the nodes in the same community are required to maintain a high connectivity. Therefore, ω should be set to a larger value, i.e., the determination threshold is made larger, and ω is preferably set to ω > 0.8 in the present invention.
In connection with the inventive concept, when t=kt (k=1, 2, 3.), a community update is performed, the specific update strategy is:
f i，j (t) is more than or equal to lambda, and the node i and the node j are classified into the same community;
f i，j (t) < lambda, then nodes i and j are classified into different communities;
where k is the kth update time.
In addition, when the node i and the node j are in the same community and the node j and the node p are in the same community, the node i and the node p are also classified into the same community. Therefore, each spacecraft performs autonomous community updating according to the mode when the preset community updating period T is reached.
In the invention, the community ID of each community can be generated according to the largest number or the smallest spacecraft number in the community. The method is characterized in that the numbers of all the spacecrafts (satellites) are different, so that the community ID determined by the method can only be the number of the spacecrafts contained in the community and cannot be repeated with other communities. After all communities are updated according to the mode, returning to the step of similarity calculation, and carrying out similarity calculation among spacecrafts again.
In summary, the invention mainly aims at the dynamic topology network of the distributed heterogeneous space-based system, and provides a method capable of effectively carrying out community detection in the spacecraft networking. And moreover, the method can be effectively applied to inter-satellite networks with all node positions rapidly changing, different communities which can be statically routed in each community are detected, and the problems that the traditional community detection method is large in calculated amount and cannot be applied to networks with nodes rapidly changing are solved. At present, the intelligent of a space-based system is realized by autonomously generating information, autonomously distributing and executing tasks by a spacecraft, and the space-based system is a hot spot for current research, and information sharing is a precondition for realizing collaborative optimization of the system. Therefore, the method can effectively reduce the cost of spacecraft information sharing, and has important value for related research and engineering application.
The above description is only one embodiment of the present invention and is not intended to limit the present invention, and various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A distributed community detection method for an inter-satellite dynamic network comprises the following steps:
a. setting all the spacecrafts as a single-node community, and setting the similarity between corresponding nodes of all the spacecrafts as 0;
b. calculating the similarity between corresponding nodes of each spacecraft, and setting a judging threshold according to the maximum value of the similarity;
c. comparing the similarity with a judgment threshold value, and updating communities according to comparison results;
in the step (b), setting the similarity attenuation coefficient to be omega, and then setting the similarity f of the node i and the node j at the time t i，j (t) is:
wherein the similarity attenuation coefficient ω satisfies: 0< ω <1;
if node i and node j remain connected all the time, the similarity f of the two i，j (t) is:
f i，j (t)＝1+f i，j (t-1)·ω；
maximum value max f of similarity i，j (t)]The method comprises the following steps:
max[f i，j (t)]＝1+ω+ω 2 +ω 3 ……；
maximum value max f of similarity i，j (t)]Always smaller thanNamely:
if the node i and the node j are not connected at the time t, the similarity f of the node i and the node j i，j (t) is:
f i，j (t)＝f i，j (t-1)·ω；
as a result of:
therefore:
setting a judgment threshold lambda as follows:
2. the method of claim 1, wherein when t=kt (k=1, 2, 3.) a community update is performed, the update policy is:
f i，j (t) is more than or equal to lambda, and the node i and the node j are classified into the same community;
f i，j (t)<lambda, the node i and the node j are classified into different communities;
wherein T is the community update period, and k is the kth update time.
3. The method of claim 2, wherein node i and node p are classified as the same community when node i and node j are in the same community and node j and node p are in the same community.
4. A method according to claim 3, characterized in that the similarity decay coefficient ω satisfies: omega > 0.8.
5. The method of claim 1, wherein in step (c), each community determines a community ID based on a largest or smallest spacecraft number therein.
6. The method of claim 1, wherein in step (c), after all communities are updated, returning to step (b) for re-similarity calculation.
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| CN107153713A (en) * | 2017-05-27 | 2017-09-12 | 合肥工业大学 | Overlapping community detection method and system based on similitude between node in social networks |
| KR20180137386A (en) * | 2017-06-15 | 2018-12-27 | 한양대학교 산학협력단 | Community detection method and community detection framework apparatus |
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| CN107153713A (en) * | 2017-05-27 | 2017-09-12 | 合肥工业大学 | Overlapping community detection method and system based on similitude between node in social networks |
| KR20180137386A (en) * | 2017-06-15 | 2018-12-27 | 한양대학교 산학협력단 | Community detection method and community detection framework apparatus |
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