WO2012109946A1

WO2012109946A1 - Data collection method of large-scale network and network node

Info

Publication number: WO2012109946A1
Application number: PCT/CN2011/085057
Authority: WO
Inventors: 胡斐然; 赵伟
Original assignee: 华为技术有限公司
Priority date: 2011-12-30
Filing date: 2011-12-30
Publication date: 2012-08-23
Also published as: CN102652425A; CN102652425B

Abstract

The present invention relates to a data collection method for a large-scale network and network node. According to the method, the nodes in the entire network are organized according to an N-tree structure, and a recursive mode is used for the statistical collection of the node information so that the monitoring data of the large-scale network nodes are statistically collected in real time without the need to modify the statistical algorithm and other service logics, thus greatly improving the speed of statistical collection of indices such as global resource utilization of the entire network, thereby satisfying in time application scenario requirements such as resource scheduling in time, and greatly reducing the maintenance cost of the large-scale network nodes at the same time.

Description

Data collection method and network node for large-scale network

Technical field

Embodiments of the present invention relate to cloud computing technologies, and in particular, to a data collection method and a network node of a large-scale network. BACKGROUND With the rapid development of cloud computing, the scale of network architectures is also increasing. Therefore, in large-scale networks, statistics on various information data of various network nodes face enormous challenges. In the traditional method, statistical indicators such as the global resource occupancy rate of the entire network are often obtained through post-analysis. In the prior art, the post-analysis method is used to collect statistics on large-scale resource indicators, generally adopting a centralized management mode, and dividing a data warehouse (ie, a management node) and a resource node, wherein the resource nodes are responsible for collecting and transmitting respective resource occupancy rates, and managing The node is responsible for the collection and storage of global resource-related data of the entire network; the post-analysis system is a specialized data mining and analysis system connected with the management node, and performs data mining analysis on the global resource-related data collected and stored by the management node, and finally outputs the data. The results of the analysis are passed to the decision system as the basis for decision making. However, post-analysis based on this architecture takes a long time and often takes hours or even days to get the final analysis.

In a scenario such as resource scheduling, where real-time statistics are needed, the more realistic the data is, the better the effect will be. Therefore, this post-analysis method is meaningless in scenarios such as resource scheduling, and may still be unavailable. This requires a method to solve the large-scale network, the global indicator resource occupancy and other statistical indicators data can be obtained as soon as possible, preferably in real time. Summary of the invention

Embodiments of the present invention provide a data acquisition method and a network node for a large-scale network, which are used to solve The problem that the statistical indicator data such as the global resource occupancy rate cannot be obtained in real time in a large-scale network is determined. In view of this, the embodiment of the present invention provides a data collection method for a large-scale network, including: the management side arbitrarily selects a node in the network as a start node, and sends a network resource occupancy rate statistics request to the start node. The node range of the other nodes in the network, requesting the starting node to perform statistics on the network resource occupancy rate;

The originating node divides other nodes in the network into N groups according to the received network resource occupancy rate statistical request and the node range of other nodes in the network, and randomly selects one node from each group. As a split start node, the network resource occupancy statistics request and the node range of other nodes in the group are separately sent to each of the split start nodes;

Each of the sub-starting nodes determines, according to the received network resource occupancy rate statistical request and the node range of other nodes in the group, whether the number of other nodes in the group is greater than N, and the number of other nodes in the group. If the value is less than or equal to N, the group is not further grouped, and the other nodes in the group are the final nodes, and the network resource occupancy statistics request is separately sent to the final node; if the number of other nodes in the group is greater than N, the other nodes in the group are further divided into N groups, and one node is randomly selected from each group as the next layer starting node, and the network resources are respectively sent to each of the next layer starting nodes. Occupancy statistics request and node range of other nodes in the group;

Repeat the above determining steps until the number of other nodes except the starting node in all the packets is less than or equal to N;

Each of the final nodes collects the network resource occupancy rate of the final node according to the received network resource occupancy rate statistics request, and reports the statistical result to the branch node to which the final node belongs;

After receiving the statistics of the network resource occupancy rate reported by the node under its jurisdiction, each branching node performs the calculation and statistics again according to the statistics of the network resource occupancy rate of the starting node, and reports the statistical result to the starting point. The upper layer to which the node belongs is divided into the starting node, and is reported to the starting node layer by layer, and the final network resource occupancy rate is calculated by the starting node; The initial node reports the calculated final network resource occupancy rate to the management terminal. The embodiment of the invention further provides a network node, including:

a receiving unit, configured to receive a network resource occupancy rate request and a node range of other nodes in the set to which the node belongs, where the network resource occupancy rate statistics request includes a source IP address of the request and a destination IP address of the request, The start time and end time of the statistics and the resource metric name of the request statistic, the node range includes a set consisting of node identifiers or a set consisting of IP addresses of nodes;

a determining a grouping unit, configured to determine, according to the network resource occupancy rate statistical request and a node range of other nodes in the set to which the node belongs, whether the number of other nodes in the set is greater than N, if the number of other nodes in the set is less than or equal to N, the group is not further grouped, and the network resource occupancy statistics request is separately sent to other nodes in the set; if the number of other nodes in the set is greater than N, the other nodes in the set are continued Dividing into N groups, arbitrarily selecting one node from each group, and separately sending the network resource occupancy rate statistics request and the node range of other nodes in the group to the node;

The resource occupancy statistics unit is configured to perform statistical reporting on the network resource occupancy rate of the node, and after receiving the statistical result of the network resource occupancy rate reported by the ruled node, perform calculation and statistics again according to the following calculation formula, and obtain the node to the network. The statistical result of the resource occupancy rate is reported, and the statistical result is reported: (the resource occupancy rate of the node + the sum of the resource occupancy rates of the nodes under the jurisdiction) I (1 + the number of nodes under its jurisdiction).

According to the foregoing technical solution, the data collection method of the large-scale network provided by the embodiment of the present invention organizes the nodes of the entire network according to the N-tree structure, and adopts a recursive manner for the information statistics of the nodes, so that the statistical algorithm does not need to be modified. Other business logic can perform real-time statistics on large-scale network node monitoring data, which greatly improves the statistical speed of indicators such as global resource occupancy rate of the entire network, thereby meeting the requirements of timely response to application scenarios such as resource scheduling, and also The maintenance cost of large-scale network nodes is greatly reduced. DRAWINGS In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below. Obviously, the drawings in the following description are only It is a certain embodiment of the present invention, and other drawings can be obtained from those skilled in the art without any creative work.

1 is a schematic diagram of a large-scale cloud computing network applied according to an embodiment of the present invention;

2 is a schematic diagram of organizing resource nodes of a whole network according to a tree hierarchical structure according to an embodiment of the present invention;

3 is a schematic flowchart of recursive grouping of nodes in a whole network according to an embodiment of the present invention; FIG. 4 is a schematic flowchart of a method for collecting data on a large-scale network according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of message interaction of a data collection method for a large-scale network according to an embodiment of the present invention;

FIG. 6 is a schematic structural diagram of a network node according to an embodiment of the present invention. detailed description

The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention. It is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.

The system environment applied in the embodiment of the present invention is as shown in FIG. 1. Figure 1 is a schematic diagram of a large-scale cloud computing network. In Figure 1, when the management level needs to collect the resource occupancy rate of the entire network, a node is randomly selected from the network as the entry point for the statistical operation, and the computing node reports the statistics of the resource occupancy rate of the entire network to the management layer. As a result, the management uses this result to determine whether it is necessary to expand or reduce the capacity of the network. The computing node in FIG. 1 may also be referred to as a resource node or a network node, which is not limited in this embodiment of the present invention.

Based on the system environment shown in FIG. 1, the method logic of the embodiment of the present invention is as follows: 1. As shown in Figure 2, the resource nodes (ie, compute nodes) of the entire network are organized according to a tree-like hierarchical structure, but the status of each layer is equivalent, and the information statistics of the nodes are recursive, so that the network can be implemented. The scale is getting bigger and bigger, but only need to increase the number of levels without modifying the statistical algorithm and other business logic; and each resource node is a computing node, which consists of two components. The task of one component is to complete the relationship with other nodes. Information synchronization, the task of another component is to perform recursive statistical reporting of indicators such as resource occupancy between nodes.

2. In order to simplify the maintenance of tree-level resources, all resource nodes are grouped into a decentralized computing node information synchronization group (as shown in Figure 1), wherein the information synchronization algorithm includes but is not limited to Gossip and other methods. Each compute node maintains all compute node information, including but not limited to: the heartbeat of the node, the state of the node (failure check / live / dead ), the node's current load.

3. The management terminal can initiate a statistical request for statistical indicators such as the resource occupancy rate of the entire network from any network resource node (decentralized computing node), then the selected starting node will group all other nodes, and the grouping method Grouping methods include, but are not limited to, binary trees; the starting node will first divide the other nodes into n groups, pick a distribution point from each group, and distribute statistical requests to these distribution points. The distribution point recursively divides the computing nodes under its jurisdiction into n components, until it is not subdivided. The entire network node grouping logic is shown in Figure 3.

4. At the same time of distribution, the computing node receiving the request starts to perform statistical calculation of indicators such as its own resource occupancy rate, and waits for the calculation result of the computing node under its jurisdiction. After the statistical results of all the computing nodes of the jurisdiction are reported, The computing node performs the summary statistics according to the following formula: (the resource occupancy rate of the node + the sum of the resource occupancy rates of the nodes under the jurisdiction) / (1 + the number of nodes under its jurisdiction); and then reports the statistical summary result to the distribution of the upper layer The node, and so on, the statistical result of the statistical indicators such as the resource occupancy rate of the entire network will be summarized to the node originally requested by the management terminal, thereby completing the resource statistics operation of the entire network.

Embodiment 1

FIG. 4 is a schematic flowchart of a data collection method for a large-scale network according to an embodiment of the present invention; As shown in FIG. 4, the data collection method of the large-scale network in this embodiment may include the following steps: The S10CK management end arbitrarily selects one node in the network as a starting node, and sends the network resource occupancy rate to the starting node. Statistic request and a node range of other nodes in the network, requesting the starting node to perform statistics on network resource occupancy rate;

Specifically, the network is a decentralized node information synchronization network, and each node in the network maintains information of all nodes. The network resource occupancy statistics request includes: a source IP address of the initiating request (such as an IP address of the management end) and a destination IP address of the receiving request (such as a node IP address randomly selected by the management terminal as a starting node), and statistics The start time and end time and the resource metric name for the request statistics. The resource metric is a metric that measures resource usage, such as CPU utilization, memory usage, and network outflow. The node range includes: a set consisting of node identifiers or a set consisting of node IP addresses. It should be noted that the range of the node may be carried in the network resource usage statistics request, or may be separately sent, which is not limited in this embodiment of the present invention.

S110. The starting node divides other nodes in the network into N groups according to the received network resource occupancy rate statistics request and the node range of other nodes in the network, and arbitrarily selects each group. a node is used as a split start node, and the network resource occupancy statistics request and the node range of other nodes in the group are respectively sent to each of the split start nodes;

It should be noted that the node range of other nodes in the network is a set of node identifiers or IP addresses of all other nodes except the start node in the network; and the node ranges of other nodes in the group are in the group. A collection of node identities or IP addresses of all other nodes except the starting node. In addition, the other nodes in the network are divided into N groups, which may be halved or unequal, and preferably N is equal to 2, but in practical applications, it may be selected according to specific situations, and this embodiment of the present invention does not Make a limit.

For example, there are 99 nodes (identified as 1 -99) in the whole network, except for the starting node (for example, 1), and 98 nodes (2-99). If N is 2, then it can be divided into 2 groups, and then select one starting node from each group (such as 2 and 51 respectively), then the range of the first group is (3-50), The range of the two groups is (52-99); but if N is 10, then it can be divided into 10 groups, and then one sub-start node is selected from each group (such as 2, 12, 22, 32, 42, 52 respectively). 62, 72, 82, 92), then the range of the first group is 3-11, the range of the second group is 13-21, and the range of the third group to the tenth group is 23-31, 33-41 43-51, 53-61, 63-71, 73-81, and 93-99.

S120. Each of the sub-starting nodes determines, according to the received network resource occupancy rate statistical request and the node range of other nodes in the group, whether the number of other nodes in the group is greater than N, if other nodes in the group If the number of the nodes is less than or equal to N, the group is not further grouped, and the other nodes in the group are the final nodes, and the network resource occupancy statistics request is separately sent to the final node; if other nodes in the group are If the number is greater than N, the other nodes in the group are further divided into N groups, and one node is randomly selected from each group as the next layer starting node, and the next node is sent to each of the next layer. Network resource occupancy statistics request and node range of other nodes in the group;

For example, suppose the network has 99 nodes, N is 10, then 10 groups, it should be 9 groups of 10 nodes, a group of 8 nodes, because you want to select a root node (that is, the starting node). In addition, among the 10 groups, there is one sub-root node in each group (that is, the sub-start node), wherein 9 sub-root nodes each have 9 nodes, and 1 sub-root node has 7 nodes. When the root node sends a statistical request to 10 sub-root nodes, the scope of the node to which each sub-root node belongs is attached. When the sub-root node finds that the number of its own nodes cannot be divided into statistical groups, it directly issues the information to the subordinate node. Statistical request, the scope of the affiliation node is no longer attached to the statistic request. After each node receives the statistic request, if it finds that there is no affiliation node range in the request, then it knows that it is a leaf node (ie, the final node). Report the statistics of your own resource usage directly.

S130, repeating the foregoing determining step, until the number of other nodes except the starting node in all the packets is less than or equal to N;

S140, each final node performs statistics on the network resource occupancy rate of the final node according to the received network resource occupancy rate statistical request, and reports the statistical result to the branching node to which the final node belongs; S150. After receiving the statistics of the network resource occupancy rate reported by the node under the control, each branching node performs the calculation and statistics again according to the statistics of the network resource occupancy rate of the starting node, and reports the statistical result to the branch. The upper layer to which the start node belongs is divided into the start node, and is reported to the start node layer by layer, and the final network resource occupancy rate is calculated by the start node;

Specifically, the step is statistically reported in a recursive manner until all statistical results are summarized to the starting node. Wherein, the starting node and the starting node are all calculated according to the following formula:

(The sum of the resource usage of the node + the sum of the resource usage of the node under the jurisdiction) / (1 + the number of nodes under the jurisdiction) S160, the starting node reports the calculated final network resource occupancy rate to the management terminal.

The data collection method of the large-scale network provided by the embodiment of the present invention is performed according to the nodes of the entire network.

The N-tree structure is organized, and the information statistics of the nodes are recursively, so that the statistical algorithms and other business logics can be modified, and real-time statistics of large-scale network node monitoring data can be performed, which greatly improves the global resources of the entire network. The statistical speed of indicators such as occupancy rate, so as to meet the requirements of timely application scenarios such as resource scheduling, and greatly reduce the maintenance cost of large-scale network nodes. Embodiment 2

FIG. 5 is a schematic diagram of message interaction of a data collection method for a large-scale network according to an embodiment of the present invention. The management end is the management layer of the whole network; the starting node is a computing node in the entire network randomly selected by the management layer; the governing node is the starting node grouping all the nodes of the whole network, and after being divided into N groups, a computing node randomly selected from each group (ie, the starting node in the first embodiment); an n-th node under the jurisdiction, which is a node where the governing node performs n times of similar starting nodes for the nodes in the group (equivalent In the first embodiment, the nth layer is divided into starting nodes); and the final node is the node after the grouping is no longer possible. As shown in FIG. 5, the data collection method of the large-scale network in this embodiment may include the following steps: In this step, the source IP address of the network-wide resource occupancy statistics request message is the IP address of the management end, and the destination IP address is the IP address of the computing node randomly selected from the current network. The statistical request message also includes statistics. The start time and the statistics end time, as well as the resource metric name of the request statistics, such as CPU utilization, memory usage, network outflow, and so on.

202. The starting node sends the quorum resource occupancy statistics request and the affiliation node range to the quorum node;

In this step, the source IP address in the quorum resource occupancy rate request message is the IP address of the starting node, and the destination IP address is a group of nodes other than the starting node in the whole network, and each group is divided into N groups. The IP address of a computing node randomly selected; the node will be the starting node of the next layer, and the other computing nodes in the group will be the node of the computing node; the statistical request part is the same as 201 The request in the same is the same, but it also needs to be accompanied by the scope of the node to which each starting node belongs.

203. The affiliation node sends the quorum resource occupancy rate request and the ruling node range to the admin node n layer node;

In this step, the quorum resource occupancy rate request initiated by the affiliation node and the source IP address of the message of the affiliation node range are the IP address of each sub-start node, and the destination IP address is the starting node. The nodes under the jurisdiction are divided into N groups again, and the IP address of one computing node is randomly selected from each group; the node will be the starting node of the next layer, and other computing nodes in the group will be used as the computing node. The governing node; the statistical request part is the same as the request in 201, but it also needs to be accompanied by the scope of the node to which each starting node belongs.

204. The n-th node under the jurisdiction sends a statistical resource occupancy rate request to the final node;

In this step, the jurisdiction resource occupancy statistics request initiated by the subordinate n-th node is similar to 203, but does not need to be accompanied by the scope of the node to which each subordinate n-node belongs.

205. The final node returns a resource occupancy rate request response to the subordinate n-th node. In this step, the source IP address in the resource occupancy statistics request response sent by the final node is the IP address of the final node, and the destination IP address is the IP address of the starting node of the upper layer, and the statistical request response includes the local The metric name of the resource, such as CPU utilization, memory usage, network outflow, etc., and the specific values corresponding to these metric names.

206. The n-layer node receives the sum of the resource occupancy rate of each node and the resource occupancy rate, and divides the total number of nodes under the jurisdiction by 1 to obtain the statistical result of the average resource occupancy rate of the node under the layer;

207. A statistical result of the resource occupancy rate of the layer to which the n-th node belongs to the subordinate node; in this step, the source IP in the statistical result of the average resource occupancy rate of the layer of the subordinate node sent by the n-th node The address is the IP address of the starting node of the layer, and the destination IP is the IP address of the starting node of the upper layer (that is, the source address from the statistical request); the average resource occupancy rate of the governing node includes the resource. Metric names, such as CPU utilization, memory usage, network outflows, etc., and the specific statistical averages for these metric names.

208. The sum of the resource occupancy rate of each layer node received by the subordinate node plus the resource occupancy rate of the node is divided by the total number of nodes under the jurisdiction, and the average resource occupancy rate of the hierarchical node of the layer is obtained;

209. The affiliation node reports the statistics of the resource occupancy rate of the layer to the starting node. In this step, the average resource occupancy statistics result of the tier node of the tier node sent by the appointing node is similar to 207.

210. The starting node adds the total resource occupancy rate of each layer node to its own resource occupancy rate, and divides the total number of nodes under the jurisdiction by one to obtain the statistical result of the average network resource occupancy rate. In this step, the starting node initiates The source IP address of the network resource occupancy rate request response is the IP address of the initiating node, and the destination IP address is the IP address of the management end. The average resource occupancy rate of the entire network includes the metric name of the resource, such as CPU utilization. , memory usage, network outflows, etc., and the specific statistical averages for these metric names.

According to the data collection method of the large-scale network provided by the embodiment, the nodes of the entire network are organized according to the N-tree structure, and the information statistics of the nodes are recursively, so that no repair is needed. By changing the statistical algorithm and other business logic, real-time statistics can be collected on the monitoring data of large-scale network nodes, which greatly improves the statistical speed of indicators such as the global resource occupancy rate of the entire network, so as to meet the requirements of timely application scenarios such as resource scheduling. At the same time, the maintenance cost of large-scale network nodes is greatly reduced. Embodiment 3

An embodiment of the present invention further provides a network node device that is applied to the foregoing method embodiments. FIG. 6 is a schematic structural diagram of a network node according to an embodiment of the present invention. As shown in FIG. 6, the network node 30 provided by the embodiment of the present invention may include a receiving unit 31, a determining grouping unit 32, and a resource occupancy statistics unit 33. The receiving unit 31 is configured to receive a network resource occupancy rate statistics request and a node range of other nodes in the set to which the local node belongs, where the network resource occupancy rate statistics request includes a source IP address of the request and a destination IP address of the request. The address, the start time and the end time of the statistics, and the resource metric name of the request statistic, the node range includes a set consisting of the node identifier or a set consisting of the IP addresses of the nodes; the determining grouping unit 32 is configured to use the network resource according to the network resource The occupancy statistics request and the node range of other nodes in the set to which the node belongs, determine whether the number of other nodes in the set is greater than N. If the number of other nodes in the set is less than or equal to N, the group is not further grouped. Sending the network resource occupancy statistics request to other nodes in the set separately; if the number of other nodes in the set is greater than N, the other nodes in the set are further divided into N groups, and any group is randomly selected. Selecting a node to separately send the network to the node The resource occupancy rate statistics request and the node range of other nodes in the group; the resource occupancy rate statistics unit 33 is configured to perform statistical reporting on the network resource occupancy rate of the node, and receive the network resource occupancy rate statistical result reported by the ruled node. After that, the calculation result is calculated again according to the following calculation formula, and the statistical result of the network resource occupancy rate of the node is obtained, and the statistical result is reported: (the resource occupancy rate of the node + the sum of the resource occupancy rates of the ruled nodes) I (1 + The number of nodes).

Further, the network node provided by the embodiment of the present invention may further include:

The node information synchronization unit 34 is configured to synchronize the node information of the entire network, so that the node maintains the network. Information about all nodes in .

The network node according to the embodiment of the present invention organizes the nodes of the entire network according to the N-tree structure, and adopts a recursive manner for the information statistics of the nodes, so that the statistical algorithm and other business logics can be modified without requiring modification of the statistical algorithm and other business logics. The network node monitors the data for real-time statistics, which greatly improves the statistical speed of the global resource occupancy rate and other indicators of the entire network, thereby meeting the requirements of timely response to application scenarios such as resource scheduling, and greatly reducing the maintenance of large-scale network nodes. cost.

It should be noted that the receiving unit 31, the determining grouping unit 32, the resource occupancy rate counting unit 33, and the node information synchronizing unit 34 in the third embodiment are all hardware.

A person skilled in the art can understand that all or part of the steps of implementing the above method embodiments may be completed by using hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, and the program is executed when executed. The foregoing storage medium includes: ROM, RAM, magnetic disk or optical disk, and the like, which can store various program codes. Finally, the above embodiments are only used to illustrate the technical solution of the present invention. The invention is described in detail with reference to the foregoing embodiments, and those of ordinary skill in the art should understand that the technical solutions described in the foregoing embodiments may be modified or some of the techniques may be The features are equivalent to the equivalents; and the modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

Rights request

A data collection method for a large-scale network, characterized in that it comprises:

The management side arbitrarily selects a node in the network as a starting node, and sends a network resource occupancy statistics request to the starting node and a node range of other nodes in the network, and requests the starting node to perform network resource occupancy rate. Statistics

After receiving the statistics of the network resource occupancy rate reported by the node under its jurisdiction, each branching node performs the calculation and statistics again according to the statistics of the network resource occupancy rate of the starting node, and reports the statistical result to the starting point. The upper layer to which the node belongs is divided into the starting node, and is reported to the starting node layer by layer, and the final network resource occupancy rate is calculated by the starting node; The initial node reports the calculated final network resource occupancy rate to the management terminal.

2. The method according to claim 1, wherein the network is a network of decentralized node information synchronization, and each node in the network maintains information of all nodes.

The method according to claim 1 or 2, wherein the network resource occupancy statistics request includes: a source IP address for initiating a request, a destination IP address for receiving the request, a start time and an ending time of the statistics. And the name of the resource metric that requested the statistic.

The method according to claim 1 or 2 or 3, wherein the node range comprises: a set consisting of node identifiers or a set consisting of IP addresses of nodes.

The method according to any one of claims 1 to 4, wherein the branching start node of each layer receives the statistical result of the network resource occupancy reported by the node under its jurisdiction, and combines the splitting The statistics of the network resource occupancy rate of the starting node are calculated again, including:

The sub-initial node of each layer collects and calculates the network resource occupancy rate of the node at the same time when the network resource occupancy rate statistics request is sent;

After receiving the statistics of the network resource occupancy rate reported by the node under its jurisdiction, perform the calculation and statistics again according to the following calculation formula, and obtain the statistical result of the network resource occupancy rate of the starting node:

(The resource occupancy rate of this node + the sum of the resource occupancy rates of the nodes under its jurisdiction) I (1 + the number of nodes under its jurisdiction).

The method according to any one of claims 1 to 5, wherein the calculation of the final network resource occupancy rate by the starting node comprises:

The initiating node collects and calculates the network resource occupancy rate of the node at the same time when the network resource occupancy rate statistics request is sent;

After receiving the statistics of the network resource occupancy rate reported by the node under its jurisdiction, the calculation is performed according to the following formula to obtain the final network resource occupancy rate:

7. A network node, comprising:

a receiving unit, configured to receive a network resource occupancy rate request and a node range of other nodes in the set to which the node belongs, where the network resource occupancy rate request includes a source of the request The IP address and the destination IP address of the received request, the start time and end time of the statistic, and the resource metric name of the request statistic, the node range including a set consisting of node identifiers or a set consisting of the IP addresses of the nodes;

The network node according to claim 7, wherein the network node further comprises: a node information synchronization unit, configured to synchronize the node information of the entire network, so that the node maintains information of all nodes in the network.