CN113098713B - End-to-end reliability assessment method for spatial information network - Google Patents
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Abstract
The invention discloses an end-to-end reliability assessment method for a spatial information network, which combines the characteristics of multiple types of low earth orbit satellite network services, large transmission delay, multiple states of node links and the like, uses a linear weight method to comprehensively consider the influence of the link residual bandwidth, the multiple states of node packet loss rate and delay on the reliability, gives different weights to bandwidth sensitive services, delay sensitive services and reliability sensitive services, calculates the communication reliability under different service background environments, enables the information network communication reliability index to be more comprehensive, and adapts to the special environment of the spatial information network. In the process of modeling the satellite network end-to-end reliability, the invention divides the satellite network communication reliability index in a multi-state mode, so that the space information network communication reliability index is more comprehensive, and the end-to-end communication reliability under different service background environments can be more accurately calculated by aiming at different service QoS requirements through a linear weight method. The invention has good application prospect.
Description
Technical Field
The invention relates to a reliability evaluation technology of a spatial information network, in particular to an end-to-end reliability evaluation method of the spatial information network.
Background
The key of the research on the communication reliability of the spatial information network is to establish an end-to-end reliability evaluation method, and the research on the end-to-end reliability evaluation method of the spatial information network is not abundant at present, so that along with the improvement of the requirement on the service quality of people, the requirement on the reliability is higher and higher, and the problem of establishing the end-to-end reliability evaluation method of the spatial information network is urgently needed to be solved.
At present, network cut-set method, simple path method, state enumeration method, factor decomposition method and repulsion principle method are developed for the reliability evaluation method of the end-to-end communication network of the ground wireless network. The research on the communication reliability of the spatial information network is limited, the methods cannot adapt to the special background environment with multiple states of links and large transmission delay of nodes of the spatial information network, cannot provide directions for the research on the communication reliability of the spatial information network, and cannot accurately calculate the end-to-end reliability of the spatial information network. In terms of research conditions at home and abroad, reliability evaluation of the spatial information network is still an open problem to be solved urgently.
Disclosure of Invention
In order to solve the above problems in the prior art, the invention is to design an end-to-end reliability evaluation method for a spatial information network, which can accurately calculate the end-to-end communication reliability of the spatial information network.
In order to achieve the purpose, the technical scheme of the invention is as follows: an end-to-end reliability evaluation method for a spatial information network comprises the following steps:
A. partitioning multiple states of a spatial information network
The spatial information network is assumed to satisfy:
1) the performance states of the satellite nodes and the inter-satellite links in the spatial information network are statistically independent;
2) any two performance states of the satellite nodes and the inter-satellite links are not overlapped.
The operation period of the satellite is divided into z time segments, each link has a randomly-changed residual bandwidth in each time segment, and only the residual bandwidth of the link is considered in the multi-state arc network. Each node has a random-variation packet loss rate, in the multi-state node network, only the packet loss rate of the node is considered, the node and the link are not influenced mutually, at any time, the satellite node or the inter-satellite link is in a determined performance state, and the performance state of the whole space information network is determined by the performance state grades of the node and the link. The spatial information network is divided into a polymorphic arc network and a polymorphic node network.
A1, dividing multi-state arc network link into multiple states
In the multi-state arc network, assuming that a link set is L {1, 2., n }, a residual bandwidth W of each link is described by using a continuous multi-state random variable distribution, and the residual bandwidth of each link v has k different performance states, which are specifically divided as follows:
in the formula, B 1 ≤B 2 ≤…≤B k-1 ≤B k ，0≤B k ≤B v ，B v For the common link, B, for the total bandwidth of the link v For bandwidth allocation after bandwidth allocation, the link performance state set is S v 0,1,2, …, k-1. At any time, the link residual bandwidth can only be at S v -one performance state of {0,1,2, …, k-1 }. Let X v Multi-state random variable representing the residual bandwidth of link v, where X v ∈S v The multi-state random variables appear with a certain probability, the probabilities are independent, and the multi-state random variable X is v Corresponding random performance state distribution probability of P vi ＝P r {X v ＝S vi }，
i is 1,2, …, k. The links v are in respective sets of performance states S v The probability of the corresponding random performance state distribution when {0,1,2, …, k-1} is { P } v1 ,P v2 ,…,P vk }。
A2, dividing node multi-state of multi-state node network
In a multi-state node network, a node set is assumed to be N ═ 1, 2.. multidot.m }, packet loss rate G of each node is described by adopting continuous multi-state random variable distribution, and packet loss rate of each node e has q different performance states, which are specifically divided as follows:
in the formula, D 1 ≤D 2 ≤…≤D q ，0≤D q Less than or equal to 1, and the node performance state set is N e With {0,1,2, …, q-1}, the node packet loss rate can only be at N at any time e -one performance state of {0,1,2, …, q-1 }. Let Y e Representing a multi-state random variable of packet loss rate of node e, wherein Y e ∈N e The multi-state random variables appear with certain probability, the probability is mutually independent, and the multi-state random variables Y e The corresponding probability of random performance state distribution is P ej ＝P r {X e ＝N ej }，
j is 1,2, …, q, and node e is in the node performance state set N e The probability of the random performance state distribution corresponding to {0,1,2, …, q-1} is { P e1 ,P e2 ,…,P eq }。
B. Computing reliability
B1, calculating the single-path reliability of the multi-state arc network
The end-to-end of the polymorphic arc network has r paths, each path consists of j links, and each link goes through Z j Individual performance states, each corresponding to a set of residual bandwidths, i.e. link j performance states
Corresponding to a set of residual bandwidth distributions of
And the probability of a performance state at each performance state corresponds to
In the formula
Bandwidth remaining multi-state random variable X j The corresponding bandwidth size satisfies the condition X j ≥B L The time link is reliable, B L Recording the minimum supported bandwidth for the normal communication of the path L
The probability of normal communication of information through the link is P Lj ＝∑P j {W fj }. The transmission delay of the corresponding link in the path L is T L ＝{T 1 ,T 2 ,…,T j And taking the link transmission delay as a constraint condition, and obtaining the reliability of the path L by using a series reliability formula as follows:
in the formula, R' (L) is the probability that the path L is normal communication, i.e., the single-path reliability.
B2, calculating single-path reliability of the multi-state node network
The multi-state node network has r paths from end to end, each path consists of j nodes except a source node, j belongs to {1,2, … n }, and each node goes through K j Individual performance states, each corresponding to a packet loss rate, i.e. a set of performance states of node j
Corresponding packet loss rate distribution set as
And the performance state probabilities at each performance state correspond to
In the formula
Then the single path is routed
The individual combined performance states construct a performance state space, a path all possible performance state space L n Is described as
The maximum packet loss rate of the combined performance state meets the maximum packet loss rate of QoS, the path is considered to be reliable in the combined performance state, all combined performance states meeting the conditions are screened out according to the following formula, and the probability of the combined performance state is calculated:
in the formula (I), the compound is shown in the specification,
and
respectively, the packet loss rate and the distribution probability of the node j in the corresponding performance state.
Assume that K combined performance states have K f The combination performance state is reliable, the probability of all reliable combination performance states is the reliability of the path considering the node packet loss rate multi-state, and the specific formula is as follows:
where p (i) is the combined performance state probability that path L satisfies the QoS maximum packet loss rate. R "(L) is the single path reliability of the multi-state node network.
B3, calculating the reliability of the single path comprehensive performance
And the single transmission path has a series structure between nodes and between links. And each transmission path takes the residual bandwidth, the time delay and the node packet loss rate of a link as performance indexes, the reliability of the multi-state of the residual bandwidth of the single-path multi-state arc network and the reliability of the multi-state node packet loss rate of the single-path multi-state arc network are calculated according to a reliability formula of a series structure, and the comprehensive performance reliability of the paths is calculated by using a linear weight method.
The influence of link residual bandwidth, node packet loss rate multi-state and time delay on the end-to-end reliability of the spatial information network is comprehensively considered, the linear weight method is used for obtaining the single-path L comprehensive performance reliability, and the specific formula is as follows:
in the formula, a and b represent weights, respectively, and satisfy the conditions 0. ltoreq. a.ltoreq.1, 0. ltoreq. b.ltoreq.1, and a + b.ltoreq.1. T is i For the transmission delay, P, corresponding to node i in the path Li And R (L) is the reliability of the comprehensive performance of the path L.
The values of a and b are related to the service type, and different weight values are given by using a subjective weight method according to the QoS service type. For bandwidth sensitive services, the overall performance reliability R (L) depends on the link residual bandwidth multi-state reliability P Li A larger value is required to be given as a weight coefficient a, namely a is more than or equal to 0.7 and less than 1; for the time delay sensitive service spatial information network, the requirement on transmission time delay is higher, paths which do not meet the time delay requirement are deleted through QoS maximum time delay constraint, and equal numerical values are given as weight coefficients a and b; for the reliability sensitive service, the comprehensive performance reliability r (l) depends on the combined probability p (i) of the maximum packet loss rate performance state satisfying QoS, and a larger value is required to be given as the weight coefficient b, i.e. b is greater than or equal to 0.7 and less than 1.
B4, computing the end-to-end reliability of spatial information network
It is set that r transmission paths exist from a source node to a destination node, a parallel structure is formed between paths in multiple paths, and according to a reliability formula of the parallel structure, the end-to-end reliability of the spatial information network is as follows:
wherein R (L) represents the reliability of the transmission path L, B min For QoS minimum Bandwidth, T i Delay for path i.
Compared with the prior art, the invention has the following effective effects:
1. in the process of modeling the end-to-end reliability of the spatial information network, the invention determines the performance states of the link and the node by dividing the link residual bandwidth and the node packet loss rate, and considers the influence of the transmission delay on the reliability, so that the information network communication reliability index is more comprehensive and is suitable for the special environment of the spatial information network.
2. The invention divides the services into bandwidth sensitive service, delay sensitive service and reliability sensitive service aiming at different QoS requirements of different services through a linear weighting method, and can more accurately calculate the end-to-end communication reliability under different service background environments.
3. In conclusion, the end-to-end reliability mathematical model of the spatial information network has good application prospect.
Drawings
Fig. 1 is a spatial information network simulation topology diagram.
Fig. 2 is a graph comparing end-to-end reliability of bandwidth sensitive traffic.
Fig. 3 is a graph comparing end-to-end reliability of delay sensitive traffic.
Fig. 4 is an end-to-end reliability comparison graph of reliability sensitive traffic.
Detailed Description
The present invention is illustrated by the following specific examples.
In the spatial information network, the operation period of a satellite is constant, the period T is divided into m time segments, in each time segment, the topology is assumed to be constant, the topology structure of the satellite network in a certain time segment is as shown in fig. 1, and the node set is V ═ { V ═ V 1 ,v 2 ,v 3 ,v 4 ,v 5 ,v 6 ,v 7 ,v 8 ,v 9 ,v 10 ,v 11 },v 1 Is a source node, v 11 Is the destination node.
Given link bandwidths (10,7,6,5,6,5,10,3,9,8,7,6,7,8,7,10), the distributions of the remaining bandwidth per link and the packet loss rate of the nodes (except the source node) in the multi-state performance parameters are shown in table 1 and table 2.
TABLE 1 residual Bandwidth Performance parameter distribution
Table 2 packet loss rate performance parameter distribution
Defining a service request (s, d, W) min ,T max ,G max )，v 1 Is a source node, v 11 For the destination node, the link propagation delay is (18,11,19,12,5,16,15,12,6,15,18,9,8,24,17), W min ,T max ,G max For multi-service QoS requirements, the different service QoS requirements are shown in table 3.
TABLE 3 Multi-service QoS requirements
The document of end-to-end reliability index algorithm of the communication network considering the transmission capacity is used for reference to obtain an end-to-end feasible path, and the widest shortest path principle is used for carrying out bandwidth allocation to obtain the multipath of { a 1 a 4 a 5 +a 2 a 6 a 9 +a 3 a 10 a 12 a 14 +a 2 a 7 a 12 a 14 }。
TABLE 4 Multi-service reliability
As can be seen from table 4, the source node, the destination node, and the network have the same multi-state distribution, different transmission services, and an obvious difference in end-to-end reliability. QoS difference is not considered in the disjoint and reliable models, the reliability obtained by different services is the same under the same state environment, compared with the disjoint and reliable models, the theoretical reliability result is closer to a simulation value, the accuracy is obviously improved, and the reliability model provided by the invention has certain effectiveness.
And changing the performance states of the nodes and the links, and calculating theoretical reliability, simulation reliability, intersection and reliability under the same performance state environment, wherein each service obtains 10 groups of experimental results. Respectively calculating the accuracy of a theoretical reliability model and the accuracy of an uncrossed reliability model, wherein the model accuracy is the closeness degree of a model calculation value and an experimental simulation value, and the calculation method comprises the following steps: accuracy ═ model calculated value-experimental simulation value)/experimental simulation value 100%.
Fig. 2 shows a comparison of end-to-end reliability obtained by three different methods when transmitting bandwidth sensitive traffic. It can be seen that the performance states are different, the reliability results obtained by calculation are different, and compared with the non-intersection and reliability, the theoretical reliability accuracy improvement of the invention is 9.01% at the maximum value and 2.79% at the minimum value.
Fig. 3 shows end-to-end reliability comparisons obtained by three different methods when transmitting delay sensitive services. It can be seen that compared with the disjoint and reliable values, the theoretical reliability accuracy of the invention is improved by 5.78% at the maximum and 1.89% at the minimum.
Fig. 4 shows a comparison of end-to-end reliability obtained by three different methods when transmitting reliability sensitive services. Compared with the disjoint and reliable values, the theoretical reliability accuracy of the method is improved by 6.62 percent at the maximum value and 1.23 percent at the minimum value.
For 3 different service types, it can be seen that there is a significant difference between the theoretical reliability and the disjoint and model reliability. Compared with a non-intersection reliability model, the reliability model provided by the invention has obviously improved accuracy, and the theoretical reliability calculated by using the reliability model is closer to the simulation reliability, because the invention classifies the services while considering the characteristics of the nodes and the links, and gives different weights to different services, which shows that the reliability model provided by the invention can more accurately calculate the end-to-end reliability of the satellite network.
The present invention is not limited to the embodiment, and any equivalent idea or change within the technical scope of the present invention is to be regarded as the protection scope of the present invention.
Claims (1)
1. An end-to-end reliability evaluation method of a spatial information network is characterized in that: the method comprises the following steps:
A. partitioning multiple states of a spatial information network
The spatial information network is assumed to satisfy:
1) the performance states of the satellite nodes and the inter-satellite links in the spatial information network are statistically independent;
2) any two performance states of the satellite node and the inter-satellite link are not overlapped;
dividing the operation period of the satellite into z time segments, wherein each link has randomly-changed residual bandwidth in each time segment, and only the residual bandwidth of the link is considered in the multi-state arc network; each node has a random variable packet loss rate, in the polymorphic node network, only the packet loss rate of the node is considered, the node and the link are not influenced mutually, at any moment, the satellite node or the inter-satellite link is in a determined performance state, and the performance state of the whole spatial information network is determined by the performance state grades of the node and the link; therefore, the space information network is divided into a polymorphic arc network and a polymorphic node network;
a1, dividing multi-state arc network link into multiple states
In the multi-state arc network, assuming that a link set is L {1, 2., n }, a residual bandwidth W of each link is described by using a continuous multi-state random variable distribution, and the residual bandwidth of each link v has k different performance states, which are specifically divided as follows:
in the formula, B 1 ≤B 2 ≤…≤B k-1 ≤B k ，0≤B k ≤B v ，B v For the common link, B, for the total bandwidth of the link v For the allocated bandwidth after bandwidth allocation, the link performance state set is S v 0,1,2, …, k-1 }; at any time, the link residual bandwidth can only be at S v (ii) one performance state of {0,1,2, …, k-1 }; let X v Multi-state random variable representing the residual bandwidth of link v, where X v ∈S v The multi-state random variables appear with a certain probability, the probabilities are independent, and the multi-state random variable X is v The corresponding probability of random performance state distribution is P vi ＝P r {X v ＝S vi }，
The links v are in respective sets of performance states S v The probability of the corresponding random performance state distribution when {0,1,2, …, k-1} is { P } v1 ,P v2 ,…,P vk }；
A2, dividing node multi-state of multi-state node network
In a multi-state node network, a node set is assumed to be N ═ 1, 2.. multidot.m }, packet loss rate G of each node is described by adopting continuous multi-state random variable distribution, and packet loss rate of each node e has q different performance states, which are specifically divided as follows:
in the formula, D 1 ≤D 2 ≤…≤D q ，0≤D q Less than or equal to 1, and the node performance state set is N e When the node packet loss rate is only N at any time, the node packet loss rate is {0,1,2, …, q-1} e (ii) one performance state of {0,1,2, …, q-1 }; let Y e Representing a multi-state random variable of packet loss rate of node e, wherein Y e ∈N e The multi-state random variables appear with certain probability, the probabilities are independent, and the multi-state random variable Y e The corresponding probability of random performance state distribution is P ej ＝P r {X e ＝N ej }，
And node e is in the set of node performance states N e The probability of the random performance state distribution corresponding to {0,1,2, …, q-1} is { P e1 ,P e2 ,…,P eq }；
B. Computing reliability
B1, calculating the single-path reliability of the multi-state arc network
The multi-state arc network has r paths from end to end, each path is composed of j links, and each link goes through Z j Individual performance states, each corresponding to a set of residual bandwidths, i.e. link j performance states
Corresponding to a set of residual bandwidth distributions of
And the probability of a performance state at each performance state corresponds to
In the formula
Bandwidth remaining multi-state random variable X j The corresponding bandwidth size satisfies the condition X j ≥B L The time-link is reliable and the time-link is reliable,B L recording the minimum supported bandwidth for the normal communication of the path L
The probability of normal communication of information through the link is P Lj ＝∑P j {W fj }; the transmission delay of the corresponding link in the path L is T L ＝{T 1 ,T 2 ,…,T j And taking the link transmission delay as a constraint condition, and obtaining the reliability of the path L by using a series reliability formula as follows:
in the formula, R' (L) is the probability that the path L is normal communication, i.e., the single-path reliability;
b2, calculating single-path reliability of the multi-state node network
The end-to-end of the polymorphic node network has r paths, each path consists of j nodes except a source node, j belongs to {1,2, … n }, and each node experiences K j Individual performance state, each performance state corresponds to a packet loss rate, namely a node j performance state set
Corresponding to the packet loss rate distribution set as
And the probability of a performance state at each performance state corresponds to
In the formula
Then the single path is routed
Individual combined performance states build performance state nullsInter, path all possible performance state space L n Is described as
The maximum packet loss rate of the combined performance state meets the maximum packet loss rate of QoS, the path is considered to be reliable in the combined performance state, all combined performance states meeting the conditions are screened out according to the following formula, and the probability of the combined performance state is calculated:
in the formula (I), the compound is shown in the specification,
and
respectively is the packet loss rate and the distribution probability of the node j in the corresponding performance state;
assume that K combined performance states have K f The combination performance state is reliable, the probability of all reliable combination performance states is the reliability of the path considering the node packet loss rate multi-state, and the specific formula is as follows:
wherein, P (i) is the probability that the path L satisfies the QoS maximum packet loss rate combination performance state; r "(L) is the single-path reliability of the multi-state node network;
b3, calculating the reliability of the single path comprehensive performance
The single transmission path is characterized in that serial structures are arranged between nodes and between links in the path; each transmission path takes the residual bandwidth, the time delay and the node packet loss rate of a link as performance indexes, the reliability of the multi-state of the residual bandwidth of the single-path multi-state arc network and the reliability of the multi-state of the packet loss rate of the multi-state node network are calculated according to a reliability formula of a series structure, and the comprehensive performance reliability of the path is calculated by using a linear weight method;
the influence of link residual bandwidth, node packet loss rate multi-state and time delay on the end-to-end reliability of the spatial information network is comprehensively considered, the linear weight method is used for obtaining the single-path L comprehensive performance reliability, and the specific formula is as follows:
in the formula, a and b represent weights respectively, and satisfy the conditions that a is not less than 0 and not more than 1, b is not less than 0 and not more than 1, and a + b is 1; t is i The transmission time delay corresponding to the node i in the path, and R (L) the comprehensive performance reliability of the path L;
the values of a and b are related to the service type, and different weight values are given by using a subjective weight method according to the QoS service type; for bandwidth sensitive services, the overall performance reliability R (L) depends on the link residual bandwidth multi-state reliability P Li A larger value is required to be given as a weight coefficient a, namely a is more than or equal to 0.7 and less than 1; the requirement of a time delay sensitive service spatial information network on transmission time delay is higher, paths which do not meet the time delay requirement are deleted through QoS maximum time delay constraint, and equal numerical values are given as weight coefficients a and b; for the reliability sensitive service, the comprehensive performance reliability R (L) depends on the combined performance state probability P (i) meeting the QoS maximum packet loss rate, and a larger value is required to be given as a weight coefficient b, namely b is more than or equal to 0.7 and less than 1;
b4, computing the end-to-end reliability of spatial information network
It is set that r transmission paths exist from a source node to a destination node, a parallel structure is formed between paths in multiple paths, and according to a reliability formula of the parallel structure, the end-to-end reliability of the spatial information network is as follows:
wherein, B min For QoS minimum Bandwidth, T i Is a pathi propagation delay.
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