CN108847969B - Network service reliability analysis method based on information flow - Google Patents
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Abstract
The invention discloses a network service reliability analysis method based on information flow, comprising the following steps: determining the weight and fault criterion of each service according to engineering application and user requirements; step two: modeling and dynamically simulating the service operated by the network, including data generation, transmission, queuing and removal; step three: and evaluating the reliability of the service. The invention has the advantages that: (1) the method of the invention can comprehensively analyze the reliability of different performance indexes of the whole network multi-service. The method is used for modeling and dynamically simulating the network operation service based on the information flow model, can obtain the specific performance index value of each service under the multi-service operation, and can realize targeted evaluation according to the specific requirements on the service reliability. (2) The invention carries out multi-service reliability evaluation according to the weight of each service in the whole network service, and embodies the importance degree of different services and the requirement degree of users for different services.
Description
Technical Field
The invention belongs to the technical field of reliability and safety (safety system engineering), and particularly relates to a network service reliability analysis method based on information flow.
Background
Network service reliability refers to the ability of a network to perform specified functions on a service under specified conditions and for specified time. The specified conditions refer to that under the condition that all components (including hardware and software) can normally work, the specified time refers to that the service in the network is in the specified working time, and the specified function refers to that the service quality of the service meets the requirement. The existing service reliability analysis model mainly aims at different fault criteria, such as delay indexes of services, congestion indexes of services and the like. However, multiple services running in the network usually emphasize different performance requirements, for example, the mail service emphasizes packet loss requirements, and the video call service emphasizes delay requirements. The existing service reliability analysis method is difficult to comprehensively analyze the reliability of different performance indexes of multiple services of the whole network. The invention provides a network service reliability analysis method based on information flow, which comprises the specific content of realizing multi-service dynamic simulation based on an information flow model, mainly comprising the processes of data flow generation, transmission, queuing and removal, thereby obtaining different performance index values of each service under the multi-service operation, and further comprehensively carrying out service reliability analysis on different performance indexes of a network. The delay and the packet loss are two most important performance indexes in the network, and are concerned in the network reliability analysis, so the method provided by the invention is explained in detail by selecting the delay and the packet loss. The service reliability analysis method provided by the invention can comprehensively carry out reliability analysis on different performance indexes of the multi-service of the whole network, and can also realize dynamic simulation of the multi-service based on the information flow model according to the specific requirements on the service reliability so as to realize targeted evaluation.
Disclosure of Invention
The invention aims to provide a network service reliability analysis method based on information flow, which aims to solve the problem that in the prior art, reliability analysis is difficult to be comprehensively carried out on different performance indexes of multiple services of the whole network.
The invention provides a network service reliability analysis method based on information flow, which can comprehensively analyze the reliability of different performance indexes of multiple services of the whole network, for example, time delay is calculated according to the time of a service data packet sent from a source node and the time of the service data packet reaching a destination node, the number of packet loss caused by the fact that a buffer area is full in the transmission process of the service data packet, the service data packet is transmitted to a wrong node at each node with a certain probability to generate error codes, and signal attenuation caused by the transmission of network signals along a service path is realized. And aiming at different analyzed performance indexes, correspondingly adjusting the acquired performance data in the dynamic service simulation process realized based on the information flow model, and further performing reliability analysis. The invention selects time delay and packet loss to explain the method in detail, and provides a flow method, which is convenient for application in engineering practice.
The network service reliability analysis method based on the information flow comprises the following specific processes:
the method comprises the following steps: and determining the weight and the fault criterion of each service according to engineering application and user requirements.
For each service i (i is 1, L, M), the performance indexes to be examined are time delay and packet loss, and according to the practical application of engineering and the requirements of users for different services, the weight ω occupied by the service i in the whole network service is determinediFor important services, the weight assignment is high; determining a delay threshold as TiPacket loss threshold is KiAnd M is the total amount of traffic to be evaluated.
Step two: the modeling and dynamic simulation of the services run by the network, including data generation, transmission, queuing, and removal. The method comprises the following specific steps:
(1) and (3) a data generation process: generating all services in the network according to a service generation algorithm, wherein the services comprise service source nodes, destination nodes and service paths;
(2) and (3) data transmission process: and traversing all the nodes to forward the data packets of the node queue according to the node forwarding capability, and determining the next address between the current node and the target node of each transmitted data packet according to the route. The processing capacity of each node is CjI.e. maximum processing per node per time CjAnd forwarding the data packet according to the number of the next node in the service path.
(3) And (3) data queuing process: and according to the queue storage scheduling algorithm of the nodes, each node transmits and receives data packets in each time step. In each time step, each node goes through two operations, sending and receiving data packets; firstly, all queues are traversed, and if a data packet exists in the queue, C of the queue is processed according to a queue storage scheduling algorithmjForwarding the data packet, and if no data packet exists, not operating; secondly, storing the received data packets from other nodes in a queue according to a queue storage scheduling algorithm, wherein the size of a cache queue of each node is QjI.e. maximum storable Q in each nodejAfter the data packets arrive at the node, queuing the data packets according to the queue storage scheduling rule of the node, and sequentially waiting for being forwarded, wherein if no idle cache exists, the node cannot accept new data packets, and the data packets are discarded at the moment.
(4) And (3) data removal process: if the data packet reaches the destination node according to the service path, the data packet is removed from the network, otherwise, the data packet is continuously forwarded to the next node. And recording the arrival time of the data packet arriving at the destination node to calculate the time delay, and if the time delay is within the allowed transmission time, considering that the data packet is successfully transmitted.
Step three: and evaluating the reliability of the service.
The service reliability for a single service, i.e. for service i (i ═ 1, L, M), is expressed as follows:
Ri＝P(Delayi≤Ti,Lossi≤Ki)
wherein, for service i, DelayiRepresenting the time delay generated during the operation of service i, L ossiThe number of lost packets. According to the weight occupied by each service, the service reliability expression of the multiple services is as follows:
wherein, ω isiIs the weight occupied by the service i in the whole network service.
Step three provides a method for calculating the service reliability, wherein the total service amount, the service weight and the fault criterion are determined according to the step one, and the time delay and the packet loss value are calculated through the step two. Specifically, the present invention obtains the performance index value of the service through dynamic simulation of the service, and further obtains the approximate value of the service reliability, and the flow is shown in fig. 1, specifically as follows:
(1) determining a network topology structure, the total amount M of services to be evaluated, the weight occupied by each service, the time delay threshold and the packet loss threshold of each service, the processing capacity of each node and the size of a cache queue, and inputting the total simulation time T;
(2) and for each time step, performing discrete event simulation of the service according to the four processes in the step two, wherein the simulation process specifically comprises the following steps:
(2.1) setting the simulation time t as 1, the total number of successfully operated services as 0, and the servicesNumber of times success of i operationiWhen the packet loss number of the service i is 0, the packet loss number is L ossi＝0；
(2.2) generating M services, including the number of data packets of each service, the source node, the destination node and the service path of each service;
(2.3) adding the data packet into the queue of the source node, recording the time t generated by the data packet, if the queue of the node is full, discarding the data packet, and the packet loss number of the corresponding service is L ossi＝Lossi+1；
(2.4) storing a scheduling algorithm according to the queues of the nodes, and forwarding a corresponding number of data packets by each node according to the processing capacity of each node;
(2.5) judging whether the data packet which is not discarded of each service reaches the destination node, if so, removing the data packet, and recording the arrival time t of the data packet to obtain the transmission Delayi. If the time delay does not exceed the time delay threshold of the service and the number of the lost packets does not exceed the packet loss threshold of the service, the service is considered to be successfully transmitted, and success is correspondingly realizedi＝successi+1, success + 1; if the destination node is not reached, forwarding to the next node;
(2.6) judging whether the node cache queue is full, if not, arranging the newly arrived data packets in the node cache region according to the queue storage scheduling algorithm of the node, if so, discarding the redundant data packets, considering that the data packets are not transmitted successfully, and determining the packet loss number of the corresponding service to be L ossi＝Lossi+1；
(2.7) simulation time t ═ t + 1;
(2.8) judging whether T is less than or equal to T, and if so, entering (2.2); if not, the simulation time length is reached, and the step (3) is entered.
(3) And calculating the reliability of the service. In (2), at each time step, M services are randomly generated, that is, each time step is equivalent to a simulated random sampling, and the Delay and the packet loss number of each service are recorded, so as to obtain the Delay in the service reliability expressioniAnd lossiAnd then determines whether each service is successfully transmitted, so L for service i (i equals to 1)And M) the service reliability calculation formula is as follows:
wherein, successiFor the number of times that service i runs successfully, alliIs the total number of runs of service i. The calculation formula of the business reliability of the multiple businesses is as follows:
wherein, ω isiIs the weight occupied by the service i in the whole network service.
The invention provides a network service reliability analysis method based on information flow, which has the advantages that:
(1) the network service reliability analysis method based on the information flow can comprehensively analyze the reliability of different performance indexes of multiple services of the whole network. The method is used for modeling and dynamically simulating the network operation service based on the information flow model, can obtain the specific performance index value of each service under the multi-service operation, and can realize targeted evaluation according to the specific requirements on the service reliability.
(2) The invention carries out multi-service reliability evaluation according to the weight of each service in the whole network service, and embodies the importance degree of different services and the requirement degree of users for different services.
Drawings
Fig. 1 is a flow chart of the method for evaluating the reliability of the service.
Fig. 2 is a diagram of a network topology.
Fig. 3 is a multi-service reliability graph.
Fig. 4 is a single traffic reliability graph.
Detailed Description
The invention will be described in further detail below with reference to the drawings and examples.
The invention relates to a network service reliability analysis method based on information flow, which can comprehensively analyze the reliability of different performance indexes of multiple services of the whole network. The invention selects time delay and packet loss to explain the method provided by the invention in detail, and the following is a case for analyzing the reliability of network service, and the concrete steps are as follows:
the method comprises the following steps: and determining the weight and the fault criterion of each service according to engineering application and user requirements.
For each service i (i ═ 1, L, M), the performance indicators to be examined are delay and packet loss, in this embodiment, the weight occupied by each service is taken to be 1, that is, ω isi1 is ═ 1; taking the time delay threshold value of all services as TiPacket loss threshold K10iAnd respectively taking the total amount of the service as M100, 200, L and 1500 to carry out service reliability analysis.
Step two: the modeling and dynamic simulation of the services run by the network, including data generation, transmission, queuing, and removal. The method comprises the following specific steps:
(1) and (3) a data generation process: and generating all services in the network according to the service generation algorithm, wherein the services comprise service source nodes, destination nodes and service paths. In this embodiment, the network service includes three types, i.e., a random service, a customized service, and a programmatic service, the ratio of the three types of services is 3:3:4, and the definition and generation manner are as follows:
① random type service, selecting service path between source node and destination node to send data according to certain routing algorithm, in this embodiment, the generation mode of the random type service is that the service path between source node O and destination node D is generated according to shortest path, when there are multiple shortest paths, one is selected as service path randomly.
②, defining a certain node as a node which must be accessed, and selecting a service path according to a certain routing algorithm, in this embodiment, the generation mode of the customized service is that, because the node degree distribution in the network determines the importance degree of the network node to a certain extent, the embodiment defines the node with the maximum node degree in the network as the node S which must pass through, the service path of the customized service can be segmented and regarded as the sum of the shortest path from O to S and the shortest path from S to D.
③ programmed service, wherein a link is defined as a link that must be passed through in the service flow, and a service path is selected according to a routing algorithm1→P2The service path of the programmed service can be segmented and regarded as the source node O to P1The shortest path of (B) must be a link P1→P2And P2Sum of shortest paths to destination node D.
In addition, the present embodiment assumes that each service generates one packet at each time step.
(2) And (3) data transmission process: and traversing all the nodes to forward the data packets of the node queue according to the node forwarding capability, and determining the next address between the current node and the target node of each transmitted data packet according to the route. In this embodiment, the processing capacity of each node is
CjFor the processing capability of node j, BEjThe betweenness of the node j, C, and N are the total processing capacity, where C is 10000 and N is 38 in this example. Each node processes C at most at each momentjAnd forwarding the data packet according to the number of the next node in the service path.
(3) And (3) data queuing process: and according to the queue storage scheduling algorithm of the nodes, each node transmits and receives data packets in each time step. In this embodiment, it is assumed that the queue storage scheduling algorithms of the nodes are all first-in-first-out (FIFO) strategies. In each time step, each node goes through two operations, sending and receiving data packets; firstly, all queues are traversed, and if a data packet exists in the queue, C at the front end of the queue is processedjForwarding the data packet, and if no data packet exists, not operating; secondly, storing the received data packet from other nodes in queueAt the tail of the queue, the buffer queue size of each node is
Wherein Q isjIs the buffer queue size of node j, BEjQ is the total queue resource, N is the number of network nodes, Q is 10000, and N is 38. Then at most Q can be stored in each nodejAnd after the data packets arrive at the node, queuing the data packets by adopting a first-in first-out queuing rule, waiting for being forwarded in sequence, and discarding the data packets if no idle cache exists and the node cannot accept new data packets.
(4) And (3) data removal process: if the data packet reaches the destination node according to the service path, the data packet is removed from the network, otherwise, the data packet is continuously forwarded to the next node. And recording the arrival time of the data packet arriving at the destination node to calculate the time delay, and if the time delay is within the allowed transmission time, considering that the data packet is successfully transmitted.
Step three: and evaluating the reliability of the service.
The service reliability for a single service, i.e. for service i (i ═ 1, L, M), is expressed as follows:
Ri＝P(Delayi≤Ti,Lossi≤Ki)
wherein, for service i, DelayiRepresenting the time delay generated during the operation of service i, L ossiThe number of lost packets. In this embodiment, the weight occupied by each service is 1, and the service reliability expression of multiple services is as follows:
the invention obtains the performance index value of the service through dynamic simulation of the service, and further obtains the approximate value of the reliability of the service, and the flow is shown in figure 1, and the method specifically comprises the following steps:
(1) determine the topology of the network (in this embodiment, for exampleThe network topology shown in fig. 2), the total amount of traffic to be evaluated is M-100, 200, L, 1500, respectively, and the delay threshold for all traffic is TiPacket loss threshold K10 i0, weight ω i1 is ═ 1; processing capacity of each node CjAnd buffer queue size QjAs stated in step two, the total simulation time T is 100;
(2) and for each time step, performing discrete event simulation of the service according to the four processes in the step two, wherein the simulation process specifically comprises the following steps:
(2.1) setting the simulation time t as 1, the total number of successfully operated services success as 0, and the number of times of successfully operated services iiWhen the packet loss number of the service i is 0, the packet loss number is L ossi＝0；
And (2.2) generating M services, including a source node, a destination node and a service path of the services, wherein the ratio of the three services of the random service, the customized service and the programmed service is 3:3: 4. In this embodiment, each service generates one data packet at each time step, and whether one data packet is successfully transmitted represents whether one corresponding service is successfully transmitted;
(2.3) adding the data packet into the queue of the source node, recording the time t generated by the data packet, if the queue of the node is full, discarding the data packet, and the packet loss number of the corresponding service is L ossi＝Lossi+1, that is, the service is not successfully transmitted;
(2.4) storing a scheduling algorithm according to the queues of the nodes, and forwarding a corresponding number of data packets by each node according to the processing capacity of each node;
(2.5) judging whether the data packet reaches the destination node, if so, removing the data packet, and recording the arrival time t of the data packet to obtain the transmission Delayi. If the time delay does not exceed the time delay threshold of the service, the service is considered to be successfully transmitted, and success is correspondingly giveni＝successi+1, success + 1; if the destination node is not reached, forwarding to the next node;
(2.6) judging whether the node cache queue is full, if not, arranging the newly arrived data packets in the nodes according to the queue storage scheduling algorithm of the nodesIf the point buffer area is full, the redundant data packets are discarded, the data packets are considered to be unsuccessfully transmitted, and the packet loss number of the corresponding service is L ossi＝Lossi+1, that is, the service is not successfully transmitted;
(2.7) simulation time t ═ t + 1;
(2.8) judging whether t is less than or equal to 100, and if so, entering (2.2); if not, the simulation duration is reached, and the step (3) is entered;
(3) and calculating the reliability of the service. In (2), at each time step, M services are randomly generated, that is, each time step is equivalent to a simulated random sampling, and the Delay and the packet loss number of each service are recorded, so as to obtain the Delay in the service reliability expressioniAnd lossiTherefore, the calculation formula of the service reliability for the service i (i ═ 1, L, M) is as follows:
wherein, successiFor the number of times that service i runs successfully, alliIs the total number of runs of service i. In this embodiment, since each service generates one data packet at each time step, all is usediThat is, the total number of packets transmitted for service i, successiI.e. the number of successfully transmitted data packets for service i. The calculation formula of the business reliability of the multiple businesses is as follows:
the success is the number of the services which are successfully operated in the network, and all is the total number of the services which are operated in the network. In this embodiment, success is the number of data packets successfully transmitted in the network, and all is the total number of data packets transmitted.
Thus, the reliability of multiple services under different total services (as shown in fig. 3) and the reliability of a single service (as shown in fig. 4, the reliability of each service when the total service is 900) can be obtained.
Claims (1)
1. A network service reliability analysis method based on information flow is characterized in that: the method comprises the following steps:
the method comprises the following steps: determining the weight and fault criterion of each service according to engineering application and user requirements;
for each service i, the performance indexes to be inspected are time delay and packet loss; determining the weight omega occupied by the service i in the whole network service according to the actual engineering application and the requirements of users on different servicesiFor important services, the weight assignment is high; determining a delay threshold as TiPacket loss threshold is KiM is the total amount of traffic to be evaluated; wherein, i is 1, …, M;
step two: modeling and dynamically simulating the service operated by the network, including data generation, transmission, queuing and removal; the method comprises the following specific steps:
(1) and (3) a data generation process: generating all services in the network according to a service generation algorithm, wherein the services comprise service source nodes, destination nodes and service paths;
(2) and (3) data transmission process: traversing all nodes to forward data packets of the node queue according to the node forwarding capability, and determining a next hop address between a current node and a target node of each transmitted data packet according to a route; the processing capacity of each node is CjI.e. maximum processing per node per time CjThe data packet is forwarded according to the serial number of the next node in the service path;
(3) and (3) data queuing process: according to a queue storage scheduling algorithm of the nodes, each node transmits and receives data packets in each time step; in each time step, each node goes through two operations, sending and receiving data packets; firstly, all queues are traversed, and if a data packet exists in the queue, C of the queue is processed according to a queue storage scheduling algorithmjForwarding the data packet, and if no data packet exists, not operating; secondly, storing the received data packets from other nodes in a queue according to a queue storage scheduling algorithm, wherein the size of a cache queue of each node is QjI.e. each ofMaximum storable Q in a nodejAfter the data packets arrive at the node, queuing according to the queue storage scheduling rule of the node, and sequentially waiting for being forwarded, wherein if no idle cache exists, the node cannot accept new data packets, and the data packets are discarded;
(4) and (3) data removal process: if the data packet reaches the destination node according to the service path, removing the data packet from the network, otherwise, continuously forwarding the data packet to the next node; recording the arrival time of a data packet arriving at a destination node to calculate time delay, and if the time delay is within the allowed transmission time, considering that the data packet is successfully transmitted;
step three: evaluating the reliability of the service;
the service reliability for a single service, i.e. for service i, the service reliability expression is as follows:
Ri＝P(Delayi≤Ti,Lossi≤Ki)
wherein, for service i, DelayiRepresenting the time delay generated during the operation of service i, L ossiThe number of lost packets; according to the weight occupied by each service, the service reliability expression of the multiple services is as follows:
wherein, ω isiThe weight of the service i in the whole network service;
the third step obtains the performance index value of the service through dynamic simulation of the service, and further obtains an approximate value of the service reliability, which is specifically as follows:
(1) determining a network topology structure, the total amount M of services to be evaluated, the weight occupied by each service, the time delay threshold and the packet loss threshold of each service, the processing capacity of each node and the size of a cache queue, and inputting the total simulation time T;
(2) and for each time step, performing discrete event simulation of the service according to the four processes in the step two, wherein the simulation process specifically comprises the following steps:
(2.1) let the simulation time t equal to 1, run asThe total number of successful services, success, is 0, and the number of times success of the service iiWhen the packet loss number of the service i is 0, the packet loss number is L ossi＝0；
(2.2) generating M services, including the number of data packets of each service, the source node, the destination node and the service path of each service;
(2.3) adding the data packet into the queue of the source node, recording the time t generated by the data packet, if the queue of the node is full, discarding the data packet, and the packet loss number of the corresponding service is L ossi＝Lossi+1；
(2.4) according to the queue storage scheduling algorithm of the nodes, each node forwards a corresponding number of data packets according to the processing capacity of the node;
(2.5) judging whether the data packet which is not discarded of each service reaches the destination node, if so, removing the data packet, and recording the arrival time t of the data packet to obtain the transmission Delayi(ii) a If the time delay does not exceed the time delay threshold of the service and the number of the lost packets does not exceed the packet loss threshold of the service, the service is considered to be successfully transmitted, and success is correspondingly realizedi＝successi+1, success + 1; if the destination node is not reached, forwarding to the next node;
(2.6) judging whether the node cache queue is full, if not, arranging the newly arrived data packets in the node cache region according to the queue storage scheduling algorithm of the node, if so, discarding the redundant data packets, considering that the data packets are not transmitted successfully, and determining the packet loss number of the corresponding service to be L ossi＝Lossi+1；
(2.7) simulation time t ═ t + 1;
(2.8) judging whether T is less than or equal to T, and if so, entering (2.2); if not, the simulation duration is reached, and the step (3) is entered;
(3) calculating the reliability of the service; in (2), at each time step, M services are randomly generated, that is, each time step is equivalent to a simulated random sampling, and the Delay and the packet loss number of each service are recorded, so as to obtain the Delay in the service reliability expressioniAnd lossiFurther, whether each service is transmitted successfully is judged; therefore, it isThe calculation formula of the service reliability for the service i is as follows:
wherein, successiFor the number of times that service i runs successfully, alliThe total number of times of operation of the service i; the calculation formula of the business reliability of the multiple businesses is as follows:
wherein, ω isiIs the weight occupied by the service i in the whole network service.
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| 基于网络链路性能测量的网络可靠性分析系统的设计与实现;薛鹏;《工程硕士学位论文》;20090731;全文 * |
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