CN-122001779-A - Core network service chain rapid reconstruction method based on network function virtualization

CN122001779ACN 122001779 ACN122001779 ACN 122001779ACN-122001779-A

Abstract

The invention discloses a core network service chain rapid reconstruction method based on network function virtualization, which relates to the technical field of communication network data transmission and network service arrangement, and comprises the steps of obtaining a cabinet loop differential pressure sequence and an error correction counting sequence of a candidate take-over host, determining a reconstruction observation window and a reference window based on arrangement event time stamps, respectively calculating a differential ripple index and an error correction peak cluster index according to the change condition of the corresponding sequences, calculating physical interference risk quantity based on the indexes and the synchronous strength of the two sequences in the observation window, finally carrying out risk scoring on the candidate service chain according to the risk quantity, selecting the service chain with the lowest score to execute tangential flow, and outputting reconstruction posterior consistency quantity. The invention can quantify cross-layer interference between short-time instability of a physical layer and communication errors, avoid misjudging hardware transient fluctuation as software overload, and prevent wrong drop point selection and reconstruction oscillation.

Inventors

YAO YIYANG
SHI YANQI
ZHANG ZHANYUAN
WU CHEN
FU HAO
LI DUANYANG
LI YAN
HAN PENG

Assignees

东北大学秦皇岛分校

Dates

Publication Date: 20260508
Application Date: 20260316

Claims (8)

1. A core network service chain rapid reconstruction method based on network function virtualization is characterized by comprising the following steps: s1, acquiring a cabinet loop differential pressure sequence of a cabinet where each candidate take-over host is located, an error correction counting sequence of the candidate take-over host, an arranging event time stamp and a candidate service chain set, and determining a reconstruction observation window and a reference window based on the arranging event time stamp; S2, calculating a differential ripple index according to differential changes of the differential pressure sequence of the cabinet loop in the reconstruction observation window and the reference window; s3, calculating an error correction peak cluster index according to the increment change of the error correction counting sequence in the reconstruction observation window and the reference window; s4, calculating physical interference risk based on the differential ripple index, the error correction peak cluster index and the synchronization strength of the cabinet loop differential pressure sequence and the error correction counting sequence in the reconstruction observation window; and S5, according to the physical interference risk quantity, risk scoring is carried out on each candidate service chain in the candidate service chain set, the candidate service chain with the lowest score is selected for tangential flow, and the reconstruction posterior consistency quantity is output.
2. The method for quickly reconstructing a service chain of a core network based on network function virtualization according to claim 1, wherein determining a reconstruction observation window and a reference window based on an orchestration event time stamp comprises: acquiring an arrangement triggering time and a tangential flow finishing time, and determining a time period from the arrangement triggering time to the tangential flow finishing time as a reconstruction observation window; The time stamp of the last service chain change or instance lifecycle change event immediately before the orchestration trigger time is obtained as a pre-time stamp, and the time period from the pre-time stamp to the orchestration trigger time is determined as a reference window.
3. The method for quickly reconstructing a service chain of a core network based on network function virtualization according to claim 2, wherein calculating a differential ripple index according to a differential change of a differential pressure sequence of a cabinet loop in a reconstruction observation window and a reference window comprises: Calculating the difference between the differential pressure values of adjacent time stamps in the cabinet loop differential pressure sequence to obtain a differential pressure differential sequence; respectively calculating the median absolute deviation of the differential pressure differential sequence in the reconstruction observation window and the reference window to obtain the robust scale of the reconstruction observation window and the robust scale of the reference window; Acquiring the minimum value of the absolute value of a non-zero differential pressure differential sequence in a reference window as a first self-adaptive stability term; dividing the reconstruction observation window robust scale by the sum of the reference window robust scale and the first adaptive stability term to obtain a differential pressure ripple index.
4. A method for fast reconstructing a service chain of a core network based on network function virtualization according to claim 3, wherein calculating an error correction spike cluster index according to incremental changes of error correction count sequences in a reconstruction observation window and a reference window comprises: the error correction count sequence comprises a forward error correction count sequence and a cyclic redundancy check count sequence; Respectively calculating the count increment of adjacent time stamps in the forward error correction count sequence and the cyclic redundancy check count sequence to obtain a forward error correction count increment sequence and a cyclic redundancy check count increment sequence; Respectively taking the median of the forward error correction count increment sequence and the cyclic redundancy check count increment sequence in the reference window as a first peak discrimination baseline and a second peak discrimination baseline; constructing an incremental sample which is larger than a first peak discrimination baseline in the reconstruction observation window as a forward error correction peak sample set; Constructing an increment sample larger than a second peak discrimination baseline in the reconstruction observation window as a cyclic redundancy check peak sample set; obtaining the minimum value of which the sum of the forward error correction count increment and the cyclic redundancy check count increment in the reconstruction observation window is greater than zero as a second self-adaptive stabilizing item; dividing the increment summation result of the forward error correction peak sample set by the sum of the forward error correction total increment and the second adaptive stabilization term in the reconstruction observation window to obtain a first energy duty ratio; Dividing the increment summation result of the cyclic redundancy check peak sample set by the sum of the cyclic redundancy check total increment and a second adaptive stabilization term in the reconstruction observation window to obtain a second energy duty ratio; The maximum value of the first energy duty ratio and the second energy duty ratio is used as an error correction peak cluster index.
5. The method for quickly reconstructing a service chain of a core network based on network function virtualization according to claim 4, wherein calculating the physical interference risk amount based on the differential ripple index, the error correction peak cluster index, and the synchronization strength of the cabinet loop differential pressure sequence and the error correction count sequence in the reconstruction observation window comprises: taking the absolute value of the difference value between adjacent time stamps of the differential pressure sequence of the cabinet loop as a first calculation sequence, and taking the sum of the forward error correction count increment and the cyclic redundancy check count increment of the corresponding time stamp as a second calculation sequence; Acquiring a median time span of adjacent samples as a sampling interval, dividing the time length of a reconstruction observation window by the sampling interval and rounding up to determine a lag range of correlation calculation; calculating normalized cross-correlation sequences of the first calculation sequence and the second calculation sequence in a hysteresis range, and taking the maximum non-negative correlation value in the normalized cross-correlation sequences as the synchronization intensity; And multiplying the differential ripple index, the error correction peak cluster index and the synchronization strength to obtain the physical interference risk.
6. The method for quickly reconstructing service chains of a core network based on network function virtualization according to claim 5, wherein performing risk scoring on each candidate service chain in a candidate service chain set according to a physical interference risk amount, selecting a candidate service chain with a lowest score for tangential flow comprises: For each candidate service chain in the candidate service chain set, acquiring a corresponding drop point host set; Calculating the physical interference risk quantity of each candidate host in the drop point host set; Acquiring byte count increment of an uplink port of each candidate takeover host in the reference window, and calculating the proportion of the byte count increment of a single candidate takeover host to the total byte count increment of the set of drop point hosts to obtain the flow weight of each candidate takeover host; carrying out product summation on the flow weight of each candidate takeover host and the corresponding physical interference risk quantity to obtain a risk score of the corresponding candidate service chain; And taking the candidate service chain with the smallest risk score as a target service chain, and cutting the target service chain.
7. The method for quickly reconstructing a service chain of a core network based on network function virtualization according to claim 6, wherein outputting a reconstruction posterior consistency quantity comprises: acquiring the actual duration recorded in the system health check period, and rearwards extending the current cutting completion time to the actual duration recorded in the system health check period to form a posterior window; Recalculating the risk score of the target service chain in the posterior window to obtain a posterior risk score; and outputting the difference value between the posterior risk score of the target service chain and the risk score of the target service chain before the cut-off as the reconstruction posterior consistency quantity.
8. A core network service chain rapid reconstruction system based on network function virtualization, which is applied to the core network service chain rapid reconstruction method based on network function virtualization as claimed in any one of claims 1 to 7, and is characterized in that the system comprises: The data acquisition module is used for acquiring a cabinet loop differential pressure sequence of a cabinet where each candidate take-over host is located, an error correction counting sequence of the candidate take-over host, an arranging event time stamp and a candidate service chain set, and determining a reconstruction observation window and a reference window based on the arranging event time stamp; The differential ripple calculation module is used for calculating a differential ripple index according to the differential change of the differential pressure sequence of the cabinet loop in the reconstruction observation window and the reference window; the error correction peak calculation module is used for calculating an error correction peak cluster index according to the increment change of the error correction counting sequence in the reconstruction observation window and the reference window; The risk amount calculation module is used for calculating the physical interference risk amount based on the differential ripple index, the error correction peak cluster index and the synchronization strength of the cabinet loop differential pressure sequence and the error correction counting sequence in the reconstruction observation window; and the tangential flow reconstruction decision module is used for scoring risks of each candidate service chain in the candidate service chain set according to the physical interference risk quantity, selecting the candidate service chain with the lowest score for tangential flow, and outputting a reconstruction posterior consistency quantity.

Description

Core network service chain rapid reconstruction method based on network function virtualization Technical Field The invention relates to the technical field of communication network data transmission and network service arrangement, in particular to a core network service chain rapid reconstruction method based on network function virtualization. Background The control plane and user plane functions of the core network are gradually deployed on the cloud infrastructure in a virtualized mode, and a plurality of virtual network functions are sequentially organized in a service chain mode to bear various communication services. In order to meet the requirement of high reliability, when the bottom node fails or the reconfiguration requirement is caused, the core network service chain needs to be quickly reconfigured so as to ensure the continuity of the service. In the high-density deployment scene of the liquid cooling cabinet, the reconstruction action of the service chain often and the migration of the network function instance occur, and at the moment, the cabinet entity cooling loop is extremely easy to generate a short-time hydraulic transient state due to pump control adjustment or flow redistribution, and the short-time ripple fluctuation phenomenon of differential pressure is shown. At the same time, the uplink port of the candidate host is also often accompanied by clustered spike surge of forward error correction count or cyclic redundancy check count, and the transient physical layer environment disturbance and link transmission error have significant negative effects on the tangential flow reliability in the reconstruction observation window. The existing service chain reconstruction strategy carries out candidate chain evaluation and selection according to network link reachability and general server performance indexes, and potential cross-layer interference influence between differential pressure short-time fluctuation of a cabinet cooling circuit and host port error correction count surge phenomenon is difficult to identify and quantify. Because of lacking the means for quantifying and comprehensively considering the phenomenon of short-time instability of a physical layer, the communication abnormality caused by the transient fluctuation of the hardware is easily misjudged as the processing overload or system arrangement invalidation of a software layer in a reconstruction window in the prior art, and the missing and misjudgment of the analysis visual angle can directly cause wrong service chain drop point selection decision, thereby causing the core network service chain to repeatedly cut and reconstruct and oscillate among a plurality of drop points, greatly prolonging the recovery time of network service and seriously degrading the service experience of an integral user. Disclosure of Invention The invention aims to solve the defects that in the prior art, the cross-layer interference influence between short-time instability of a physical layer and link communication errors is difficult to quantify, hardware transient fluctuation is easily misjudged as software overload, and error drop point selection and repeated reconfiguration oscillation are caused. In order to solve the problems existing in the prior art, the invention adopts the following technical scheme: A core network service chain quick reconstruction method based on network function virtualization comprises the following steps: s1, acquiring a cabinet loop differential pressure sequence of a cabinet where each candidate take-over host is located, an error correction counting sequence of the candidate take-over host, an arranging event time stamp and a candidate service chain set, and determining a reconstruction observation window and a reference window based on the arranging event time stamp; S2, calculating a differential ripple index according to differential changes of the differential pressure sequence of the cabinet loop in the reconstruction observation window and the reference window; s3, calculating an error correction peak cluster index according to the increment change of the error correction counting sequence in the reconstruction observation window and the reference window; s4, calculating physical interference risk based on the differential ripple index, the error correction peak cluster index and the synchronization strength of the cabinet loop differential pressure sequence and the error correction counting sequence in the reconstruction observation window; and S5, according to the physical interference risk quantity, risk scoring is carried out on each candidate service chain in the candidate service chain set, the candidate service chain with the lowest score is selected for tangential flow, and the reconstruction posterior consistency quantity is output. Preferably, determining the reconstruction observation window and the reference window based on the orchestration event time stamp comprises: acquiring an arra