WO2015149444A1 - 网络异常检测处理方法、装置及计算机存储介质 - Google Patents

网络异常检测处理方法、装置及计算机存储介质 Download PDF

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Publication number
WO2015149444A1
WO2015149444A1 PCT/CN2014/082172 CN2014082172W WO2015149444A1 WO 2015149444 A1 WO2015149444 A1 WO 2015149444A1 CN 2014082172 W CN2014082172 W CN 2014082172W WO 2015149444 A1 WO2015149444 A1 WO 2015149444A1
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Prior art keywords
link
abnormal
normal
status
state
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PCT/CN2014/082172
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English (en)
French (fr)
Inventor
许倩倩
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中兴通讯股份有限公司
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Application filed by 中兴通讯股份有限公司 filed Critical 中兴通讯股份有限公司
Priority to EP14888423.2A priority Critical patent/EP3128781B1/en
Priority to JP2016559959A priority patent/JP6279100B2/ja
Publication of WO2015149444A1 publication Critical patent/WO2015149444A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/04—Arrangements for maintaining operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W76/00—Connection management
    • H04W76/30—Connection release
    • H04W76/38—Connection release triggered by timers

Definitions

  • the present invention relates to the field of mobile communications, and in particular, to a network anomaly detection processing method, apparatus, and computer storage medium. Background technique
  • the network anomaly detection method is to detect the abnormality in the network in a timely and effective manner, and provide corresponding processing methods to minimize the impact of network anomalies on network performance.
  • Network performance indicators include scheduling performance indicators and measurement performance indicators.
  • the scheduling performance indicator is mainly measured by the scheduling feedback of the link.
  • the scheduling feedback refers to the feedback of the correctness of the transmitted data. If the transmitted data receiving end receives correctly, the correct feedback (ACK, Acknowledgement) is sent to the transmitting end; otherwise, the feedback error (NACK) , Negative Acknowledgement ) to the sender. After receiving the NACK, the sender retransmits the data packet that feeds back the NACK. If the receiver still fails to correctly receive the data packet after retransmitting the number of times, the data packet is discarded.
  • the scheduling performance indicator may be a scheduling error packet rate, a scheduling packet loss rate, a continuous packet loss number, and a continuous error packet number.
  • the scheduling error packet rate refers to the ratio of the scheduling packet and the total scheduling packets that feed back the NACK in the scheduling packet.
  • the scheduling packet loss rate refers to the ratio of the new transmission packet and the total scheduling packet of the multiple scheduling feedback NACK; the continuous error packet number refers to the continuous feedback in the scheduling. Number of NACKs; The number of consecutive packet drops refers to the number of consecutive failures of new packets.
  • the measurement performance index is mainly measured by the measured value of the uplink and downlink measurement signals, for example: the measured value of the channel sounding reference signal (SRS, Sounding Reference Signal), channel quality The reported value of the indicator (CQI, Channel Quality Indicator).
  • SRS channel sounding reference signal
  • CQI Channel Quality Indicator
  • embodiments of the present invention provide a network anomaly detection processing method, apparatus, and computer storage medium.
  • the embodiment of the present invention provides a network anomaly detection processing method, where the method includes: periodically counting performance index information of an access link; and performing threshold values corresponding to the performance indicator information and corresponding performance indicator information according to statistics Determining the state of the link; processing the link according to the determined state of the link.
  • the periodic statistics are: counting by a preset time period or by using a preset number of data packets as a period.
  • the performance indicator information is scheduling performance indicator information or measurement performance indicator information.
  • the link comprises an uplink or a downlink.
  • the processing of the link includes: performing statistics on performance index information of the corresponding link for the link with the normal status; and limiting the scheduling resource of the link for the link with the abnormal status,
  • the threshold is re-accessed or released.
  • the link does not return to the normal state or the abnormal threshold is reached in the subsequent statistical period, and continues to be processed according to the abnormal link status.
  • the processing of the link includes: performing, according to the link with the normal status, statistics on the performance of the link; and triggering the link re-access or release on the link with the abnormal status; Limiting the scheduling resource of the link to the link in the observed state, the link in the observed state returns to normal in the subsequent statistical period, and the link is processed according to the state, for the chain in the observed state
  • the route reaches the abnormal threshold in the subsequent statistical period, and uses the re-access or release.
  • the link in the observed state does not return to normal or the abnormal threshold is reached in the subsequent statistical period, and continues to follow the chain in the observed state. Road processing.
  • the link re-accessing includes: when the link re-access is successful, re-stating the performance indicator information of the link in the next statistical period; when the link re-access fails, Then the link is released directly.
  • the embodiment of the present invention further provides a network anomaly detection processing device, where the device includes: an information statistics module, configured to periodically count performance index information of an access link; and a comparison judgment module configured to perform statistics according to the information The performance indicator information of the module statistics and the threshold value corresponding to the corresponding performance indicator information determine the state of the link;
  • a processing module configured to process the link according to a status of the link determined by the determining module.
  • the information statistics module is configured to collect performance index information of the access link by using a preset time period, or to calculate performance index information of the access link by using a preset number of data packets.
  • the processing module is configured to continue to collect performance indicator information of the corresponding link for the link with the normal status; and to limit the scheduling resource of the link for the link with the abnormal status, for the status is not
  • the normal link is restored to normal after the subsequent statistics period. According to the state, the re-access or release is used. For the link whose status is abnormal, the link does not return to the normal state and is not confirmed to be reached.
  • the abnormal threshold continues to be processed according to the abnormal link status.
  • the processing module is configured to continue to count the corresponding chain on the link with the normal status. a performance indicator of the path; triggering the link re-access or release on the link with the abnormal state; limiting the scheduling resource of the link to the link in the observed state, and following the link in the observed state
  • the statistic period is restored to normal.
  • the link is in the normal state.
  • the link in the observed state reaches the abnormal threshold in the subsequent statistics period.
  • the re-access or release is used.
  • the subsequent statistical period is neither restored nor confirmed as reaching the abnormal threshold, and continues to be processed according to the link in the observed state.
  • the processing module is configured to re-count the performance indicator information of the link in the next statistical period when the link re-access is successful, and directly release the link when the re-access failure fails.
  • the link is configured to re-count the performance indicator information of the link in the next statistical period when the link re-access is successful, and directly release the link when the re-access failure fails.
  • the embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the network abnormality detection processing method according to the embodiment of the present invention.
  • the technical solution of the embodiment of the present invention can accurately identify the state of the uplink or the downlink, and determine the state type, and then perform corresponding processing according to the determination result, so as not to affect the scheduling of the normal link in the cell, thereby Try to avoid network performance degradation due to network anomalies, and minimize the impact of network anomalies on network performance.
  • FIG. 1 is a schematic flowchart of a network anomaly detection processing method according to an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of a network anomaly detection processing method according to Embodiment 1 of the present invention
  • 4 is a schematic flowchart of a network abnormality detecting and processing method according to a third embodiment of the present invention
  • FIG. 5 is a schematic structural diagram of a network abnormality detecting apparatus according to a fourth embodiment of the present invention.
  • the base station periodically collects and processes the system during operation.
  • the performance indicator information of the access link is compared with the preset threshold information to obtain link state information, and corresponding links are processed according to the link state information.
  • FIG. 1 is a schematic flowchart of a network anomaly detection processing method according to an embodiment of the present invention. The method steps disclosed in the embodiment of the present invention are as shown in FIG. 1. The method includes:
  • Step S101 The base station periodically collects performance indicator information of the access link.
  • Step S102 The base station determines the state of the link according to the statistical performance indicator information and the corresponding threshold value of the corresponding performance indicator information.
  • the uplink observation state and the downlink observation state indicate that the link abnormality has not been completely determined, and only the link has an abnormal trend.
  • the base station collects the performance indicator information of the specific link.
  • the state of the link is a state corresponding to the specific threshold range.
  • the threshold range may be set according to network performance requirements and a statistical manner.
  • the threshold may include the following types: a normal threshold and an abnormal threshold, and the abnormal threshold may be specifically divided into an observation threshold and an abnormal threshold.
  • These types of thresholds can be set separately on the uplink and downlink.
  • the normal threshold is a threshold used to determine whether the link is normal, and the status of the link within the threshold is normal.
  • the abnormal threshold is a threshold with respect to the normal threshold. If the performance index of the link reaches the range of the abnormal threshold, the link status may be determined to be abnormal.
  • the abnormal threshold can be further divided into an observation threshold and an abnormal threshold.
  • the observation period threshold is a threshold used to determine whether the link needs to continue to collect related information.
  • a link that reaches this threshold is a link with an abnormal possibility. You need to continue to collect statistics to determine the link status.
  • the abnormal threshold is a threshold used to determine whether the link is abnormal, and the link reaching the threshold is determined to be an abnormal link.
  • the abnormal threshold can be further divided into a threshold that is directly determined to be abnormal, or can be determined as an abnormal threshold after the link performance is not improved after multiple observation periods.
  • the threshold range information may be that the scheduling performance information of the uplink and downlink or the threshold information of the measurement performance information may be set to be periodic, and the period may be a period in a certain period of time, or may be a certain amount of data.
  • the package is a certain period. If 2S is used as a cycle, it is also possible to transmit 100 packets as one cycle. And the periods of different types of information of different links may be the same or different.
  • how to set the threshold may be configured and saved in the base station according to the policy of the operator in a specific area.
  • the LTE network performance indicator requires that the scheduling error rate threshold is generally 10%, and the scheduling packet loss rate threshold is generally 1%. If the network performance requirements are high, the basic performance indicators can be slightly improved. Poorly performing links limit scheduling resources, re-access or release of abnormal links, and ensure network performance requirements.
  • the uplink normal threshold can be set to the scheduling error packet rate of 6%, the threshold for directly determining the uplink abnormality is set to the scheduling error packet rate of 8%, and the uplink observation period threshold is set to the scheduling packet loss rate of 7%;
  • the downlink normal threshold is set to the scheduling packet loss rate of 0.6%, the downlink observation period threshold is set to the scheduling packet loss rate of 0.6%-0.8%, and the downlink abnormal threshold is set to five consecutive periods as the observation period.
  • the threshold information period of the uplink and downlink links, and the statistics period of different threshold indicators of the uplink and downlink links may be the same or different.
  • the threshold may be degraded based on the basic performance indicator.
  • the scheduling error packet rate threshold is generally 10%
  • the scheduling packet loss rate threshold is generally 1%, and the operator's network property in a specific area.
  • the metrics are not very high. Therefore, you can set the uplink normal threshold to 12% of the scheduled packet loss rate and the uplink abnormal threshold to 15% of the scheduled packet loss rate.
  • the downlink normal threshold is set to a scheduling error rate of 1.3%
  • the downlink abnormal threshold is set to a scheduling error rate of 1.6%.
  • the statistical period of the uplink and downlink threshold information may be a time period or a chain. A certain data packet is transmitted for a certain period, and the statistical periods of different threshold indicators of the uplink and downlink may be the same or different.
  • Step S103 The base station processes the link according to the state information of the link.
  • the base station continues to count the links in the normal state of the uplink or the downlink, and does not perform any processing on the corresponding links.
  • the base station limits its scheduling resources to the link in the observed state, and limits the scheduling of the corresponding link; and unilaterally limits its scheduling resources, that is, the link in the uplink observation state only limits the The uplink scheduling resource of the link, the link in the downlink observation state only limits the downlink scheduling resources of the link, and continues to count the related information of the corresponding link while limiting the scheduling resources of the corresponding link, and the corresponding link is observed. If the link returns to the normal state in the subsequent statistical period, the link is processed according to the normal state; if the link is still not restored in the subsequent statistical period, further confirm whether the link is up.
  • the abnormal threshold is that the link that reaches the abnormal threshold is processed according to the abnormal link. If the link does not return to normal and the link does not reach the abnormal threshold in the subsequent statistics period, continue to follow the status.
  • the normal link processing mode continues to be processed.
  • the base station continues to collect the performance index of the corresponding link for the link with the normal state; the link with the abnormal state is triggered to re-access or release the link;
  • the link of the state limits the scheduling resource of the link, and the link in the observed state returns to normal in the subsequent statistical period, according to the link processing in which the state is normal, and the link in the observed state is subsequently
  • the statistics period reaches the abnormal threshold and is re-accessed or released.
  • the link in the observed state does not return to normal in the subsequent statistical period. It is also not confirmed that the abnormal threshold is reached, and the link processing in the observed state continues.
  • the base station uses a policy for triggering the corresponding link to re-access the base station or directly releasing the link that is determined to be in an abnormal state in the uplink or downlink. If the link re-access is successful, the link for re-accessing the base station re-statistics the performance indicator information of the link in the next cycle, according to the new link processing; when the link re-access fails , the link is released directly.
  • the base station performs the same processing on the link that is determined to be abnormal according to the processing mode of the link in the observed state.
  • step S101 to step S103 are repeated in the next scheduling cycle.
  • the embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the network abnormality detection processing method according to the embodiment of the present invention.
  • the first embodiment is a method for the network abnormality detection and processing by using the statistical performance index information by the base station
  • FIG. 2 is a schematic flowchart of the network abnormality detection processing method according to the first embodiment of the present invention. As shown in FIG. 2, the method includes:
  • Step 201 The base station counts the number of consecutive packet drops of all uplinks and the scheduled packet loss rate of the downlink. Take the six links of the base station as an example. The current statistics of all links are as follows:
  • the statistics of the uplink are:
  • Link 1 The number of consecutive packet drops is 5 times;
  • Link 2 The number of consecutive packet loss is 6 times
  • Link 3 The number of consecutive packet drops is 20 times.
  • the downlink sends 100 packets for one statistical period:
  • Link 1 The probability of NACK for the current scheduling window scheduling feedback is 15%
  • Link 2 The probability of the current scheduling window scheduling feedback NACK is 45%
  • Link 3 Already in observation state and 4 consecutive scheduling windows in observation period, current scheduling
  • the probability of window scheduling feedback NACK is 70%.
  • Step 202 The base station compares the statistical performance indicator information with the corresponding threshold, and obtains link state information according to the comparison result.
  • the performance indicator information of the uplink is the number of consecutive packet loss
  • the threshold corresponding to the performance indicator information of the uplink is:
  • the threshold value in the normal state is 10 times, that is, the packet is not lost after 10 consecutive times or less, and the uplink is determined to be in a normal state;
  • threshold value in the observation state is 20 times, that is, continuous packet loss 20 times or more, it is determined that the uplink is in an observation state
  • the uplink is determined to be in an abnormal state.
  • the performance indicator information of the downlink is a probability of scheduling a feedback NACK, and the statistical period of the probability is to send 100 scheduling packets as one cycle, and the threshold value corresponding to the performance indicator information of the downlink is :
  • the threshold value in the normal state is 20%, that is, less than 20 scheduling packets in the 100 scheduling packets feed back NACK, it is determined that the downlink is in a normal state
  • the threshold value of the observed state is 40%, that is, more than 40 scheduling packets in the 100 scheduling packets are fed back NACK, and then the downlink is determined to be in an observation state;
  • the threshold value in the abnormal state is that the five consecutive scheduling windows are in the observation period, that is, in the continuous 500 packets, and more than 40 scheduling packets in each of the 100 scheduling packets feed back NACK, and the downlink is determined to be in an abnormal state.
  • the status of the corresponding link is: Upstream:
  • Link 1 is in a normal state
  • Link 2 in a normal state
  • Link 3 In observation.
  • Link 1 is in a normal state
  • Step 203 The base station processes the corresponding link according to the status information of each link.
  • Link 1 continue to count performance indicator information of the link
  • Link 2 continue to count performance indicator information of the link
  • Link 3 Enter the observation period, limit the downlink scheduling resources of the link, continue to collect the performance indicator information of the link in the subsequent statistical period, and determine the status of the link.
  • Link 1 continue to count performance indicator information of the link
  • Link 2 Entering the observation period, limiting the downlink scheduling resources of the link, and continuing to count the performance indicator information of the link in the subsequent statistical period and determining the status of the link;
  • Link 3 Initiating re-access to the link, if the link re-access is successful, re-stating the performance indicator information of the link, and repeating steps 201 to 203; if the link is heavy If the access fails, the link is directly released.
  • the embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the network abnormality detection processing method according to the embodiment of the present invention.
  • the second embodiment is a flowchart of a method for the network abnormality detection and processing performed by the base station by using the statistical performance index information.
  • FIG. 3 is a schematic flowchart of the network abnormality detection processing method according to the second embodiment of the present invention; : Step 301: The base station collects the SRS measurement invalidity probability of all uplinks and the scheduled packet loss rate of the downlink.
  • the statistic of the uplink is as follows:
  • Link 3 Already in observation state and 4 consecutive statistical windows are in observation state, the current statistical window SRS measurement invalidity probability is 70%.
  • the downlink counts 100 new packets as a statistical window.
  • Link 1 The current scheduling window packet loss probability is 5%
  • Link 2 The probability of packet loss in the current scheduling window is 45%
  • Link 3 The current scheduling window packet loss probability is 20%.
  • Step 302 The base station compares the statistical performance indicator information with the corresponding threshold, and obtains link state information according to the comparison result.
  • the performance indicator information of the uplink is a SRS measurement validity ratio, and a window statistic is adopted, and 100 SRS measurement values are a statistic window; a threshold value corresponding to the performance indicator information of the uplink For:
  • the threshold value in the normal state is 20%, that is, less than 20 of the 100 measured values are invalid, it is determined that the uplink is in a normal state
  • the threshold value in the observation state is 30%, that is, more than 30 of the 100 measured values are invalid, it is determined that the uplink is in an observation state
  • the threshold value in the abnormal state is that the five consecutive statistical windows are in the observation period, that is, among the 500 consecutive measurement values, if more than 30 measurement values are invalid for every 100 measurement values, the uplink is determined to be in an abnormal state.
  • the performance indicator information of the downlink is a downlink packet loss probability
  • the downlink packet loss probability is a method of window cut statistics
  • 100 new data packets are a statistics window
  • the downlink performance indicator is used.
  • the threshold value in the normal state is 20%, that is, when less than 20 packets of 100 packets are lost, it is determined that the downlink is in a normal state
  • the threshold value in the observation state is 30%, that is, more than 30 packet loss packets in 100 packets, and it is determined that the downlink is in an observation state;
  • the threshold value in the abnormal state is that the five consecutive statistical windows are in the observation period, that is, in the continuous 500 packets, more than 30 packets out of every 100 packets are dropped, and the downlink is determined to be abnormal.
  • the status of the corresponding link is: Uplink:
  • Link 1 is in a normal state
  • Link 3 is in a normal state.
  • Step 303 The base station processes the corresponding link according to the status information of each link.
  • Link 1 Entering the observation period, continuing to count the performance indicator information of the link in the subsequent statistical period and determining the status of the link;
  • Link 2 is in a normal state, and continues to count performance indicator information of the link
  • Link 3 In an abnormal state, the link is released directly.
  • the link 1 is in the normal state and continues to collect the performance indicator information of the link.
  • the link 2 enters the observation period, limits the downlink scheduling resources of the link, and continues to count the performance indicators of the link in the subsequent statistics period. Information and determining the status of the link;
  • Link 3 In the normal state, continue to collect statistics on the performance indicators of the link.
  • the embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the network abnormality detection processing method according to the embodiment of the present invention.
  • FIG. 4 is a schematic flowchart of a network anomaly detection processing method according to Embodiment 3 of the present invention; as shown in FIG. 4, the method includes:
  • Step 401 The base station collects the scheduling packet loss rate of all uplinks.
  • the base station has three uplinks as an example, and all the current link statistics are as follows:
  • the uplink uses the statistics of the newly transmitted data packet in 2S as a statistical period:
  • Link 1 The current period packet loss rate is 5%
  • Link 3 The current period packet loss rate is 20%.
  • Step 402 The base station compares the obtained performance indicator information with a corresponding threshold, and obtains link state information according to the comparison result.
  • the performance indicator information of the uplink is an uplink packet loss rate of a statistical period
  • the threshold corresponding to the performance indicator information of the uplink is:
  • the threshold value in the normal state is 10%, that is, the packet loss rate in the newly transmitted data packet in the 2S is less than 10%, and the link is determined to be in a normal state;
  • the threshold value in the abnormal state is 15%, that is, the packet loss rate is high in the newly transmitted data packet in 2S. At 15%, the link is determined to be in an abnormal state.
  • the status of the corresponding link is: Upstream:
  • Link 1 is in a normal state
  • Step 403 The base station processes the corresponding link according to the status information of each link.
  • link 1 is in a normal state, and continues to count performance indicator information of the link;
  • Link 2 Entering the observation period, limiting the downlink scheduling resources of the link, and continuing to count the performance indicator information of the link in the subsequent statistical period and determining the status of the link;
  • Link 3 Enter the observation period, limit the downlink scheduling resources of the link, continue to collect the performance indicator information of the link in the subsequent statistical period, and determine the status of the link.
  • the embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the network abnormality detection processing method according to the embodiment of the present invention.
  • FIG. 5 is a schematic structural diagram of a network anomaly detecting apparatus according to Embodiment 4 of the present invention. As shown in FIG. 4, the apparatus includes:
  • the information statistic module 51 is configured to periodically calculate the performance indicator information of the access link.
  • the determining module 52 is configured to determine, according to the performance indicator information and the corresponding threshold value corresponding to the performance indicator information, that is calculated by the information statistic module 51. The status of the link;
  • the processing module 53 is configured to process the link according to the status of the link determined by the determining module 52.
  • the information statistic module 51 is configured to collect performance indicator information of the access link by using a preset time period, or use a preset number of data packets as a period. Statistics of performance indicators of the access link.
  • the processing module 53 is configured to continue to collect performance index information of the corresponding link for a link with a normal status, and limit the scheduling of the link for a link with an abnormal status.
  • the link is normal to the link in the subsequent statistical period, and the link is processed according to the normal state.
  • the link For the link whose status is abnormal, the link reaches the abnormal threshold in the subsequent statistical period. If the link is abnormal, the link that is in the normal state is not restored to the normal state and is not confirmed to reach the abnormal threshold. The link continues to be processed according to the abnormal status.
  • the processing module 53 is configured to continue to collect performance indicators of the corresponding link for a link with a normal status, and trigger the link re-access or for a link with an abnormal status. Releasing; limiting the scheduling resource of the link to the link in the observed state, and returning to the link in the observed state in the subsequent statistical period, according to the normal link processing, for the observed state The link reaches the abnormal threshold in the subsequent statistics period, and uses the re-access or release. The link in the observed state does not return to normal or the abnormal threshold is reached in the subsequent statistical period. Link processing.
  • the processing module 53 is configured to continue to collect performance indicators of the corresponding link for a link with a normal status, and trigger the link re-access or for a link with an abnormal status. Releasing; limiting the scheduling resource of the link to the link in the observed state, and returning to the link in the observed state in the subsequent statistical period, according to the normal link processing, for the observed state The link reaches the abnormal threshold in the subsequent statistics period, and uses the re-access or release. The link in the observed state does not return to normal or the abnormal threshold is reached in the subsequent statistical period. Link processing.
  • the network abnormality detecting and processing device may be used in an actual application.
  • the base station is implemented; the information statistics module 51, the determining module 52, and the processing module 53 in the device may be implemented by a central processing unit (CPU), a digital signal processor (DSP) in the device. , Digital Signal Processor ) or Field Programmable Gate Array (J).
  • CPU central processing unit
  • DSP digital signal processor
  • J Field Programmable Gate Array
  • embodiments of the present invention can be provided as a method, or a computer program product. Accordingly, the present invention can take the form of a hardware embodiment, a software embodiment, or a combination of software and hardware aspects. Moreover, the invention can be embodied in the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) including computer usable program code.
  • a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) including computer usable program code.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded into a computer or other programmable data processing device Having a series of operational steps performed on a computer or other programmable device to produce computer-implemented processing, such that instructions executed on a computer or other programmable device are provided for implementing a process or processes in a flowchart and/or Or block diagram the steps of a function specified in a box or multiple boxes.
  • the embodiment of the present invention determines the state of the uplink or the downlink, determines the state type, and performs corresponding processing according to the determination result, so as not to affect the scheduling of the normal link in the cell, thereby avoiding network performance due to network abnormality as much as possible. The decline, to minimize the impact of network anomalies on network performance.

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Abstract

本发明公开了一种网络异常检测处理方法、装置及计算机存储介质；其中，所述的方法包括以下步骤：周期性统计接入链路的性能指标信息；根据统计的所述性能指标信息和相应性能指标信息对应的门限值确定链路的状态；根据确定的所述链路状态对所述链路进行处理。

Description

网络异常检测处理方法、 装置及计算机存储介质 技术领域
本发明涉及移动通信领域， 尤其涉及网络异常检测处理方法、 装置及 计算机存储介质。 背景技术
随着移动通信网络的发展， 运营商越来越重视网络性能指标， 当多个 终端通过通信链路接入基站调度时， 如果无线链路出现异常， 而基站又没 有行之有效的异常检测处理方法时， 网络吞吐率就会大幅度下降， 同时亦 会导致网络频谱效率降低， 不利于网络的稳定性。 网络异常检测方法就是 针对网络中的异常问题， 及时有效地进行检测， 并提供相应的处理方式， 最大程度地减小网络异常对网络性能的影响。
网络性能指标有调度性能指标和测量性能指标等。 调度性能指标主要 通过链路的调度反馈衡量， 调度反馈指对发送数据的正确性的反馈， 如果 发送的数据接收端正确接收， 则反馈正确（ACK, Acknowledgement )给发 送端； 否则反馈错误（NACK, Negative Acknowledgement )给发送端。 发 送端收到 NACK后， 会重传反馈 NACK的数据包， 如果重传达到一定次数 后， 接收端还是没有正确接收该数据包， 则丟弃该数据包。 所述的调度性 能指标可以为调度错包率、 调度丟包率、 连续丟包次数和连续错包次数等。 调度错包率指调度包中反馈 NACK的调度包和全部调度包的比值； 调度丟 包率指多次调度反馈 NACK的新传包和全部调度包的比值； 连续错包次数 指调度中连续反馈 NACK的次数； 连续丟包次数指新传包连续调度失败的 次数。 测量性能指标主要通过上下行链路测量信号的测量值衡量， 例如： 信道探测参考信号（SRS, Sounding Reference Signal )的测量值， 信道质量 指标（CQI, Channel Quality Indicator ) 的上报值等。
现有技术中虽有网络异常检测方法， 但是未能全面准确的检测出网络 上下行链路的不同性能指标下降所导致的网络异常， 并且亦没有对异常做 出针对性的处理， 在网络性能提升方面的作用不明显。 发明内容
为解决现有存在的技术问题， 本发明实施例提供一种网络异常检测处 理方法、 装置及计算机存储介质。
为达到上述目的， 本发明实施例的技术方案是这样实现的：
本发明实施例提供了一种网络异常检测处理方法， 所述的方法包括： 周期性统计接入链路的性能指标信息； 根据统计的所述性能指标信息和相 应性能指标信息对应的门限值确定链路的状态； 根据确定的所述链路的状 态对所述链路进行处理。
优选地， 所述周期性统计为： 以预设时间为周期统计或以预设数量的 数据包为周期统计。
优选地， 所述性能指标信息是调度性能指标信息或测量性能指标信息。 优选地， 所述链路包括上行链路或下行链路。
优选地， 所述对链路进行处理包括： 对状态为正常的链路继续统计相 应链路的性能指标信息； 对状态为非正常的链路限制所述链路的调度资源，
门限， 采用重接入或释放， 对于所述状态为非正常的链路在随后的统计周 期既未恢复正常状态也未确认为达到异常门限， 继续按照状态为非正常的 链路处理。
优选地， 所述对链路进行处理包括： 对状态为正常的链路继续统计相 应链路的性能指标； 对状态为异常的链路触发所述链路重接入或者释放； 对处于观察状态的链路限制所述链路的调度资源， 对于所述处于观察状态 的链路在随后的统计周期恢复正常， 按照状态为正常的链路处理， 对于所 述处于观察状态的链路在随后的统计周期达到异常门限， 采用重接入或释 放， 对于所述处于观察状态的链路在随后的统计周期既未恢复正常也未确 认为达到异常门限， 继续按照处于观察状态的链路处理。
优选地， 所述链路重接入， 包括： 当所述链路重接入成功， 则在下一 个统计周期重新统计所述链路的性能指标信息； 当所述链路重接入失败时， 则直接释放所述链路。
本发明实施例还提供了一种网络异常检测处理装置， 所述的装置包括： 信息统计模块， 配置为周期性统计接入链路的性能指标信息； 比较判断模块， 配置为根据所述信息统计模块统计的所述性能指标信 息和相应性能指标信息对应的门限值确定链路的状态；
处理模块， 配置为根据所述确定模块确定的所述链路的状态对所述链 路进行处理。
优选地， 所述信息统计模块， 配置为以预设时间为周期统计接入链路 的性能指标信息 , 或以预设数量的数据包为周期统计接入链路的性能指标 信息。
优选地， 所述处理模块， 配置为对状态为正常的链路继续统计相应链 路的性能指标信息； 对状态为非正常的链路限制所述链路的调度资源， 对 于所述状态为非正常的链路在随后的统计周期恢复正常， 按照状态为正常 限， 采用重接入或释放， 对于所述状态为非正常的链路在随后的统计周期 既未恢复正常状态也未确认为达到异常门限， 继续按照状态为非正常的链 路处理。
优选地， 所述处理模块， 配置为对状态为正常的链路继续统计相应链 路的性能指标； 对状态为异常的链路触发所述链路重接入或者释放； 对处 于观察状态的链路限制所述链路的调度资源， 对于所述处于观察状态的链 路在随后的统计周期恢复正常， 按照状态为正常的链路处理， 对于所述处 于观察状态的链路在随后的统计周期达到异常门限， 采用重接入或释放， 对于所述处于观察状态的链路在随后的统计周期既未恢复正常也未确认为 达到异常门限， 继续按照处于观察状态的链路处理。
优选地， 所述处理模块， 配置为当所述链路重接入成功， 则在下一个 统计周期重新统计所述链路的性能指标信息； 当所述链路重接入失败时， 则直接释放所述链路。
本发明实施例还提供了一种计算机存储介质 , 所述计算机存储介质中 存储有计算机可执行指令， 所述计算机可执行指令用于执行本发明实施例 所述的网络异常检测处理方法。
采用本发明实施例的技术方案， 能准确的识别出上行或下行链路的状 态， 并对状态类型进行判定， 才艮据判定结果进行相应的处理， 以免影响小 区内正常链路的调度， 从而尽可能避免由于网络异常导致网络性能的下降， 最大程度地减小网络异常对网络性能的影响。 附图说明
图 1是本发明实施例的网络异常检测处理方法的流程示意图； 图 2是本发明实施例一的网络异常检测处理方法的流程示意图； 图 3 是本发明实施例二的网络异常检测处理方法的流程示意图； 图 4是本发明实施例三的网络异常检测处理方法的流程示意图； 图 5是本发明实施例四的网络异常检测装置的组成结构示意图。 具体实施方式
在本发明的各种实施例中， 基站在工作过程中， 会周期性的收集并统 计接入链路的性能指标信息， 与预设的门限信息进行比较， 得到链路状态 信息， 根据链路状态信息对相关链路做相应的处理。
图 1 是本发明实施例的网络异常检测处理方法的流程示意图； 本发明 实施例公开的方法步骤如图 1所示， 所述方法包括：
步骤 S101 : 基站周期性的统计接入链路的性能指标信息。
步骤 S102: 基站根据统计的所述性能指标信息和相应性能指标信息对 应的门限值确定链路的状态。 正常状态， 上行非正常状态， 下行正常状态， 下行非正常状态； 其中， 所 述上行非正常状态又可分为上行观察状态和上行异常状态； 所述下行非正 常状态可分为下行观察状态和下行异常状态。 所述上行观察状态和所述下 行观察状态表示还没有完全确定链路异常， 仅是有异常趋势的链路 。
具体的， 所述基站统计具体链路的性能指标信息， 当所述性能指标信 息对应的数值落入相应门限范围内， 则所述链路的状态为具体门限范围对 应的状态。
其中， 所述门限范围可以根据网络性能要求和统计方式设置。
所述门限可以包括以下几种类型： 正常门限和非正常门限， 非正常门 限又可以具体分为观察期门限和异常门限。
这几类门限可以分上下行链路单独设置。
所述正常门限是用来确定链路是否正常的门限， 对于在此门限范围内 的链路其状态为正常。
所述非正常门限是相对于正常门限的一种门限， 链路的性能指标达到 了非正常门限的范围就可以认定相应链路状态为非正常。
所述非正常门限又可以具体分为观察期门限和异常门限
所述观察期门限是用来判断链路是否需要继续统计相关信息的门限， 达到此门限范围的链路为具有异常可能性的链路， 需要经过继续统计相关 信息进而判断其链路状态。
所述异常门限是用来确定链路是否异常的门限， 对于达到此门限的链 路确定为异常链路。 该异常门限又可以分为直接确定为异常的门限， 也可 以为经过多次观察期后链路性能没有好转才确定为异常的门限。
上述门限范围信息可以为上下行链路的调度性能信息或测量性能信 所述门限范围信息可以设定为周期性的， 该周期可以为时间上一定的 周期， 也可以为以统计一定数量的数据包为一定的周期。 如以 2S为一个周 期， 也可以以传送 100个数据包为一个周期。 并且不同链路不同类型信息 的周期可以相同也可以不同。
具体怎样设置所述门限值， 可以根据运营商在特定区域的策略进行配 置并保存在基站中。 如： LTE 网络性能指标中要求调度错包率门限一般是 10%, 调度丟包率门限一般是 1%, 如果对网络性能要求高， 可以在基本性 能指标的基础上稍做提升， 尽快对调度性能差的链路限制调度资源， 对异 常链路重接入或者释放， 保证网络性能的需求。 此时可以将上行正常门限 设置为调度错包率 6%,将直接确定上行链路异常的门限设置为调度错包率 8%, 将上行观察期门限设置为调度丟包率为 7%; 将下行正常门限设置为 调度丟包率 0.6%, 将下行观察期门限设置为调度丟包率为 0.6%-0.8%, 将 下行异常门限设置为连续 5 个周期为观察期。 所述上下行链路的门限信息 期， 并且上下行链路不同门限指标的统计周期可以相同也可以不相同。
对于网络性能指标要求不是很高的场合， 所述门限值可以在基本性能 指标的基础上做一定的下降。 如在 LTE网络性能指标中要求调度错包率门 限一般是 10%, 调度丟包率门限一般是 1%, 特定区域内运营商对网络的性 能指标要求不是很高， 所以可以根据运营商的策略对指标进行适当的 P争低， 可以将上行正常门限设置为调度丟包率 12%, 将上行非正常门限设置为调 度丟包率 15%, 将下行正常门限设置为调度错包率 1.3%, 将下行非正常门 限设置为调度错包率 1.6%, 同样所述上下行链路的门限信息的统计周期可 以为时间周期也可以为以链路传输一定的数据包为一定周期， 并且上下行 链路不同门限指标的统计周期可以相同也可以不相同。
步骤 S103 : 基站根据链路的状态信息对链路进行处理。
这里， 所述基站对上行或下行处于正常状态的链路继续统计， 对相应 的链路不做任何处理。
依据本发明实施例的一个方面， 所述基站对处于观察状态的链路限制 其调度资源， 限制相应链路的调度； 同时单方限制其调度资源， 即处于上 行观察状态的链路仅限制所述链路的上行调度资源， 处于下行观察状态的 链路仅限制所述链路的下行调度资源 , 在限制相应链路的调度资源的同时 继续统计相应链路的相关信息， 相应的链路处于观察状态后在随后的统计 周期内若所述链路恢复正常状态， 则按照状态为正常的链路处理； 在随后 的统计周期若所述链路仍未恢复正常， 进一步确认所述链路是否达到异常 门限， 对于达到异常门限的链路按照状态异常的链路处理， 对于在随后的 统计周期若所述链路既未恢复正常又未确认所述链路达到异常门限， 继续 按照对状态为非正常的链路的处理方式继续处理。
依据本发明实施例的另一个方面， 所述基站对状态为正常的链路继续 统计相应链路的性能指标； 对状态为异常的链路触发所述链路重接入或者 释放； 对处于观察状态的链路限制所述链路的调度资源， 对于所述处于观 察状态的链路在随后的统计周期恢复正常， 按照状态为正常的链路处理， 对于所述处于观察状态的链路在随后的统计周期达到异常门限， 采用重接 入或释放， 对于所述处于观察状态的链路在随后的统计周期既未恢复正常 也未确认为达到异常门限， 继续按照处于观察状态的链路处理。 其中， 所述基站对于上行或下行判断为异常状态的链路， 采用触发相 应链路重接入基站或者直接释放的策略。 针对重接入基站的链路如果所述 链路重接入成功， 则在下一个周期重新统计所述链路的性能指标信息， 按 照新的链路处理； 当所述链路重接入失败时， 则直接释放所述链路。
所述基站对于判断为非正常的链路， 按照处于观察状态的链路的处理 方式进行同样的处理。
下一个调度周期重复上面的步骤 S101至步骤 S103。
本发明实施例还提供了一种计算机存储介质 , 所述计算机存储介质中 存储有计算机可执行指令， 所述计算机可执行指令用于执行本发明实施例 所述的网络异常检测处理方法。
下面通过具体的实施例并结合附图来对本发明进行详细说明。
实施例一为基站利用统计到的性能指标信息进行网络异常检测与处理 的方法， 图 2是本发明实施例一的网络异常检测处理方法的流程示意图； 如图 2所示， 所述方法包括：
步骤 201 :基站统计所有上行链路的连续丟包次数和下行链路的调度丟 包率。 以所述基站有 6个链路为例， 目前统计的所有链路信息如下：
上行链路的统计结果为：
链路 1 : 连续丟包次数为 5次；
链路 2: 连续丟包次数为 6次；
链路 3: 连续丟包次数为 20次。
下行链路以发送 100个包为一个统计周期：
链路 1： 当前调度窗调度反馈 NACK的概率为 15%;
链路 2: 当前调度窗调度反馈 NACK的概率为 45%;
链路 3: 已经处于观察状态并且连续 4个调度窗处于观察期， 当前调度 窗调度反馈 NACK的概率为 70%。
步骤 202: 基站将统计得到的性能指标信息和相应的门限值进行比较， 根据比较结果得到链路状态信息。
这里， 所述上行链路的性能指标信息为连续丟包次数， 则所述上行链 路的性能指标信息对应的门限值为：
处于正常状态的门限值为 10次，也就是连续 10次或 10次以下不丟包， 则判定所述上行链路为正常状态；
处于观察状态的门限值为 20次， 也就是连续丟包 20次或 20次以上， 则判定所述上行链路处于观察状态；
处于异常状态的门限值为 60次， 也就是连续丟包 60次或 60次以上， 则判定所述上行链路为异常状态。
这里， 所述下行链路的性能指标信息为调度反馈 NACK的概率， 所述 概率的统计周期以发送 100个调度包为一个周期， 则所述下行链路的性能 指标信息对应的门限值为：
处于正常状态的门限值为 20%, 也就是 100个调度包中少于 20个调度 包反馈 NACK, 则判定所述下行链路处于正常状态；
处于观察状态的门限值为 40%, 也就是 100个调度包中超过 40个调度 包反馈 NACK, 则判定所述下行链路处于观察状态；
处于异常状态的门限值为连续 5个调度窗处于观察期，也就是连续 500 个包中， 每 100个调度包中超过 40个调度包反馈 NACK, 则判定所述下行 链路为异常状态。
根据步骤 201中的统计结果和相应的门限值， 相应链路的状态为： 上行：
链路 1 : 处于正常状态；
链路 2: 处于正常状态； 链路 3: 处于观察状态。
下行：
链路 1 : 处于正常状态；
链路 2: 处于观察状态；
链路 3: 处于异常状态。
步骤 203: 基站根据每个链路的状态信息对相应链路进行处理。
这里， 才艮据步骤 202中确定的所述链路的状态， 则相应的处理方式为： 上行：
链路 1 : 继续统计所述链路的性能指标信息；
链路 2: 继续统计所述链路的性能指标信息；
链路 3: 进入观察期， 限制所述链路的下行调度资源， 在后续统计周期 继续统计所述链路的性能指标信息并进行所述链路的状态的判断。
下行：
链路 1 : 继续统计所述链路的性能指标信息；
链路 2: 进入观察期， 限制所述链路的下行调度资源， 在后续统计周期 继续统计所述链路的性能指标信息并进行所述链路的状态的判断；
链路 3: 对所述链路发起重接入， 如果所述链路重接入成功， 则重新统 计所述链路的性能指标信息， 重复执行步骤 201至步骤 203; 如果所述链路 重接入失败， 则直接释放所述链路。
本发明实施例还提供了一种计算机存储介质 , 所述计算机存储介质中 存储有计算机可执行指令， 所述计算机可执行指令用于执行本发明实施例 所述的网络异常检测处理方法。
实施例二为基站利用统计到的性能指标信息进行网络异常检测与处理 的方法流程， 图 3 是本发明实施例二的网络异常检测处理方法的流程示意 图； 如图 3所示， 所述方法包括： 步骤 301 : 基站统计所有上行链路的 SRS测量无效性概率和下行链路 的调度丟包率。
以所述基站有 6个链路为例， 目前统计的所有链路信息如下： 上行链路以统计 100个 SRS测量值为一个统计窗为例， 所述上行链路 的统计结果为：
链路 1 : 当前统计窗 SRS测量无效性概率为 35%;
链路 2: 当前统计窗 SRS测量无效性概率为 15%;
链路 3: 已经处于观察状态并且连续 4个统计窗处于观察状态， 当前统 计窗 SRS测量无效性概率为 70%。
下行链路以统计 100个新传数据包为一个统计窗。
链路 1 : 当前调度窗丟包概率为 5%;
链路 2: 当前调度窗丟包概率为 45%;
链路 3: 当前调度窗丟包概率为 20%。
步骤 302: 基站将统计得到的性能指标信息和相应的门限值进行比较， 根据比较结果得到链路状态信息。
这里， 所述上行链路的性能指标信息为 SRS测量有效性比例， 采用截 窗统计的方式， 100个 SRS测量值为一个统计窗； 在所述上行链路的性能 指标信息对应的门限值为：
处于正常状态的门限值为 20%, 也就是 100个测量值中少于 20个测量 值是无效的， 则判定所述上行链路为正常状态；
处于观察状态的门限值为 30%, 也就是 100个测量值中超过 30个测量 值是无效的， 则判定所述上行链路处于观察状态；
处于异常状态的门限值为连续 5个统计窗处于观察期，也就是连续 500 个测量值中， 每 100个测量值中超过 30个测量值无效， 则判定所述上行链 路为异常状态。 这里， 所述下行链路的性能指标信息为下行丟包概率， 所述下行丟包 概率采用截窗统计的方式， 100个新传数据包为一个统计窗， 则所述下行链 路的性能指标信息对应的门限值为：
处于正常状态的门限值为 20%, 也就是 100个数据包中少于 20个数据 包丟包时， 判定所述下行链路处于正常状态；
处于观察状态的门限值为 30%, 也就是 100个包中超过 30个数据包丟 包， 判定所述下行链路处于观察状态；
处于异常状态的门限值为连续 5个统计窗处于观察期，也就是连续 500 个包中， 每 100个包中超过 30个数据包丟包， 判定所述下行链路为异常状 态。
根据步骤 301中的统计结果和相应的门限值， 相应链路的状态为： 上行：
链路 1 : 处于观察状态；
链路 2: 处于正常状态；
链路 3: 处于异常状态。
下行：
链路 1 : 处于正常状态；
链路 2: 处于观察状态；
链路 3: 处于正常状态。
步骤 303: 基站根据每个链路的状态信息对相应链路进行处理。
这里， 才艮据步骤 302中确定的所述链路的状态， 则相应的处理方式为： 上行：
链路 1 : 进入观察期， 在后续统计周期继续统计所述链路的性能指标信 息并进行所述链路的状态的判断；
链路 2: 处于正常状态， 继续统计所述链路的性能指标信息； 链路 3: 处于异常状态， 直接释放所述链路。
下行：
链路 1 : 处于正常状态， 继续统计所述链路的性能指标信息； 链路 2: 进入观察期， 限制所述链路的下行调度资源， 在后续统计周期 继续统计所述链路的性能指标信息并进行所述链路的状态的判断；
链路 3: 处于正常状态， 继续统计所述链路的性能指标信息。
本发明实施例还提供了一种计算机存储介质 , 所述计算机存储介质中 存储有计算机可执行指令， 所述计算机可执行指令用于执行本发明实施例 所述的网络异常检测处理方法。
图 4是本发明实施例三的网络异常检测处理方法的流程示意图；如图 4 所示， 所述方法包括：
步骤 401 : 基站统计所有上行链路的调度丟包率。
本实施例以基站有 3 个上行链路为例， 则目前统计的所有链路信息如 下：
上行链路以统计 2S内新传数据包为一个统计周期：
链路 1 : 当前周期丟包率为 5%;
链路 2: 当前周期丟包率为 45%;
链路 3: 当前周期丟包率为 20%。
步骤 402: 基站将统计得到的性能指标信息和相应的门限值进行比较， 根据比较结果得到链路状态信息。
这里， 所述上行链路的性能指标信息为一个统计周期的上行丟包率， 则所述上行链路的性能指标信息对应的门限值为：
处于正常状态的门限值为 10%,也就是 2S内新传数据包中丟包率低于 10%, 则判定所述链路为正常状态；
处于非正常状态的门限值为 15%,也就是 2S内新传数据包中丟包率高 于 15%, 则判定所述链路非正常状态。
才艮据步骤 401中的统计结果和相应的指标门限， 相应链路的状态为： 上行：
链路 1 : 处于正常状态；
链路 2: 处于非正常状态；
链路 3: 处于非正常状态。
步骤 403: 基站根据每个链路的状态信息对相应链路进行处理。
这里， 才艮据步骤 402中确定的所述链路的状态， 则相应的处理方式为： 链路 1 : 处于正常状态， 继续统计所述链路的性能指标信息；
链路 2: 进入观察期， 限制所述链路的下行调度资源， 在后续统计周期 继续统计所述链路的性能指标信息并进行所述链路的状态的判断；
链路 3: 进入观察期， 限制所述链路的下行调度资源， 在后续统计周期 继续统计所述链路的性能指标信息并进行所述链路的状态的判断。
本发明实施例还提供了一种计算机存储介质 , 所述计算机存储介质中 存储有计算机可执行指令， 所述计算机可执行指令用于执行本发明实施例 所述的网络异常检测处理方法。
图 5是本发明实施例四的网络异常检测装置的组成结构示意图，如图 4 所示， 所述装置包括：
信息统计模块 51 , 配置为周期性统计接入链路的性能指标信息； 确定模块 52,配置为根据所述信息统计模块 51统计的所述性能指标信 息和相应性能指标信息对应的门限值确定链路的状态；
处理模块 53 ,配置为根据所述确定模块 52确定的所述链路的状态对所 述链路进行处理。
依据本发明实施例的一个方面， 所述信息统计模块 51 , 配置为以预设 时间为周期统计接入链路的性能指标信息， 或以预设数量的数据包为周期 统计接入链路的性能指标信息。
依据本发明实施例的另一个方面， 所述处理模块 53 , 配置为对状态为 正常的链路继续统计相应链路的性能指标信息； 对状态为非正常的链路限 制所述链路的调度资源， 对于所述状态为非正常的链路在随后的统计周期 恢复正常， 按照状态为正常的链路处理， 对于所述状态为非正常的链路在 随后的统计周期达到异常门限， 采用重接入或释放， 对于所述状态为非正 常的链路在随后的统计周期既未恢复正常状态也未确认为达到异常门限， 继续按照状态为非正常的链路处理。
依据本发明实施例的另一个方面， 所述处理模块 53 , 配置为对状态为 正常的链路继续统计相应链路的性能指标； 对状态为异常的链路触发所述 链路重接入或者释放； 对处于观察状态的链路限制所述链路的调度资源， 对于所述处于观察状态的链路在随后的统计周期恢复正常， 按照状态为正 常的链路处理， 对于所述处于观察状态的链路在随后的统计周期达到异常 门限， 采用重接入或释放， 对于所述处于观察状态的链路在随后的统计周 期既未恢复正常也未确认为达到异常门限， 继续按照处于观察状态的链路 处理。
依据本发明实施例的另一个方面， 所述处理模块 53 , 配置为对状态为 正常的链路继续统计相应链路的性能指标； 对状态为异常的链路触发所述 链路重接入或者释放； 对处于观察状态的链路限制所述链路的调度资源， 对于所述处于观察状态的链路在随后的统计周期恢复正常， 按照状态为正 常的链路处理， 对于所述处于观察状态的链路在随后的统计周期达到异常 门限， 采用重接入或释放， 对于所述处于观察状态的链路在随后的统计周 期既未恢复正常也未确认为达到异常门限， 继续按照处于观察状态的链路 处理。
在本发明实施例中， 所述网络异常检测处理装置在实际应用中， 可由 基站实现； 所述装置中的信息统计模块 51、 确定模块 52和处理模块 53 , 在实际应用中， 均可由所述装置中的中央处理器（ CPU, Central Processing Unit ), 数字信号处理器（DSP, Digital Signal Processor )或现场可编程门阵 歹 'J ( FPGA, Field Programmable Gate Array ) 实现。
通过具体实施方式的说明， 应当可对本发明实施例为达成预定目的所 采取的技术手段及功效得以更加深入且具体的了解， 然而所附图示仅是提 供参考与说明之用， 并非用来对本发明加以限制。 同时在不沖突的情况下， 实施例和实施例中的特征可以相互组合。
本领域内的技术人员应明白， 本发明的实施例可提供为方法、 或计算 机程序产品。 因此， 本发明可采用硬件实施例、 软件实施例、 或结合软件 和硬件方面的实施例的形式。 而且， 本发明可采用在一个或多个其中包含 有计算机可用程序代码的计算机可用存储介质 (包括但不限于磁盘存储器 和光学存储器等）上实施的计算机程序产品的形式。
本发明是参照根据本发明实施例的方法和计算机程序产品的流程图和 / 或方框图来描述的。 应理解可由计算机程序指令实现流程图和 /或方框图中 的每一流程和 /或方框、 以及流程图和 /或方框图中的流程和 /或方框的结合。 可提供这些计算机程序指令到通用计算机、 专用计算机、 嵌入式处理机或 其他可编程数据处理设备的处理器以产生一个机器， 使得通过计算机或其 他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流 程或多个流程和 /或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理 设备以特定方式工作的计算机可读存储器中， 使得存储在该计算机可读存 储器中的指令产生包括指令装置的制造品， 该指令装置实现在流程图一个 流程或多个流程和 /或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备 上， 使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机 实现的处理， 从而在计算机或其他可编程设备上执行的指令提供用于实现 在流程图一个流程或多个流程和 /或方框图一个方框或多个方框中指定的功 能的步骤。
以上所述， 仅为本发明的较佳实施例而已， 并非用于限定本发明的保 护范围。 工业实用性
本发明实施例通过识别出上行或下行链路的状态， 并对状态类型进行 判定， 根据判定结果进行相应的处理， 以免影响小区内正常链路的调度， 从而尽可能避免由于网络异常导致网络性能的下降， 最大程度地减小网络 异常对网络性能的影响。

Claims

权利要求书
1、 一种网络异常检测处理方法， 所述方法包括以下步骤：
周期性统计接入链路的性能指标信息；
根据统计的所述性能指标信息和相应性能指标信息对应的门限值确定 链路的状态；
根据确定的所述链路的状态对所述链路进行处理。
2、 根据权利要求 1所述的方法， 其中， 所述周期性统计为： 以预设时 间为周期统计或以预设数量的数据包为周期统计。
3、 根据权利要求 1所述的方法， 其中， 所述性能指标信息是调度性能 指标信息或测量性能指标信息。
4、 根据权利要求 3所述的方法， 其中， 所述链路包括上行链路或下行 链路。
5、 根据权利要求 1所述的方法， 其中， 所述对链路进行处理包括： 对 状态为正常的链路继续统计相应链路的性能指标信息； 对状态为非正常的 链路限制所述链路的调度资源， 对于所述状态为非正常的链路在随后的统 计周期恢复正常， 按照状态为正常的链路处理， 对于所述状态为非正常的 链路在随后的统计周期达到异常门限， 采用重接入或释放， 对于所述状态 为非正常的链路在随后的统计周期既未恢复正常状态也未确认为达到异常 门限， 继续按照状态为非正常的链路处理。
6、 根据权利要求 1所述的方法， 其中， 所述对链路进行处理包括： 对 状态为正常的链路继续统计相应链路的性能指标； 对状态为异常的链路触 发所述链路重接入或者释放； 对处于观察状态的链路限制所述链路的调度 资源， 对于所述处于观察状态的链路在随后的统计周期恢复正常， 按照状 态为正常的链路处理， 对于所述处于观察状态的链路在随后的统计周期达 到异常门限， 采用重接入或释放， 对于所述处于观察状态的链路在随后的 统计周期既未恢复正常也未确认为达到异常门限， 继续按照处于观察状态 的链路处理。
7、 根据权利要求 5或 6所述的方法， 其中， 所述链路重接入， 包括： 当所述链路重接入成功， 则在下一个统计周期重新统计所述链路的性能指 标信息； 当所述链路重接入失败时， 则直接释放所述链路。
8、 一种网络异常检测处理装置， 所述的装置包括：
信息统计模块， 配置为周期性统计接入链路的性能指标信息； 确定模块， 配置为根据所述信息统计模块统计的所述性能指标信息和 相应性能指标信息对应的门限值确定链路的状态；
处理模块， 配置为根据所述确定模块确定的所述链路的状态对所述链 路进行处理。
9、 根据权利要求 8所述的装置， 其中， 所述信息统计模块， 配置为以 预设时间为周期统计接入链路的性能指标信息 , 或以预设数量的数据包为 周期统计接入链路的性能指标信息。
10、 根据权利要求 8所述的装置， 其中， 所述处理模块， 配置为对状 态为正常的链路继续统计相应链路的性能指标信息； 对状态为非正常的链 路限制所述链路的调度资源， 对于所述状态为非正常的链路在随后的统计 周期恢复正常， 按照状态为正常的链路处理， 对于所述状态为非正常的链 路在随后的统计周期达到异常门限， 采用重接入或释放， 对于所述状态为 非正常的链路在随后的统计周期既未恢复正常状态也未确认为达到异常门 限， 继续按照状态为非正常的链路处理。
11、 根据权利要求 8 所述的装置， 其中， 所述处理模块， 配置为对状 态为正常的链路继续统计相应链路的性能指标； 对状态为异常的链路触发 所述链路重接入或者释放； 对处于观察状态的链路限制所述链路的调度资 源， 对于所述处于观察状态的链路在随后的统计周期恢复正常， 按照状态 为正常的链路处理， 对于所述处于观察状态的链路在随后的统计周期达到 异常门限， 采用重接入或释放， 对于所述处于观察状态的链路在随后的统 计周期既未恢复正常也未确认为达到异常门限， 继续按照处于观察状态的 链路处理。
12、 根据权利要求 10或 11所述的装置， 其中， 所述处理模块， 配置 为当所述链路重接入成功， 则在下一个统计周期重新统计所述链路的性能 指标信息； 当所述链路重接入失败时， 则直接释放所述链路。
13、 一种计算机存储介质， 所述计算机存储介质中存储有计算机可执 行指令， 所述计算机可执行指令用于执行权利要求 1至 7任一项所述的网 络异常检测处理方法。
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