CN108923961A - A kind of multiple entry network service function chain optimization method - Google Patents
A kind of multiple entry network service function chain optimization method Download PDFInfo
- Publication number
- CN108923961A CN108923961A CN201810659293.2A CN201810659293A CN108923961A CN 108923961 A CN108923961 A CN 108923961A CN 201810659293 A CN201810659293 A CN 201810659293A CN 108923961 A CN108923961 A CN 108923961A
- Authority
- CN
- China
- Prior art keywords
- service
- network
- service request
- service function
- shortest path
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0893—Assignment of logical groups to network elements
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
- H04L41/5041—Network service management, e.g. ensuring proper service fulfilment according to agreements characterised by the time relationship between creation and deployment of a service
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
- H04L41/5041—Network service management, e.g. ensuring proper service fulfilment according to agreements characterised by the time relationship between creation and deployment of a service
- H04L41/5051—Service on demand, e.g. definition and deployment of services in real time
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
- H04L67/61—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources taking into account QoS or priority requirements
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
- H04L67/62—Establishing a time schedule for servicing the requests
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
- H04L67/63—Routing a service request depending on the request content or context
Abstract
A kind of multiple entry network service function chain optimization method of the present invention, it carries out link distribution according to service request type quantity of each access node within a time short enough, the link of dynamic backtracking later is reallocated, pass through statistical fractals request type and frequency, and the weighted value of different service requests is distributed according to statistical result, the high service request of prioritized deployment weight, and merge certain services therein according to horsepower requirements to reach the tradeoff and optimization of time delay and energy consumption, reduce network computing resources expense.
Description
Technical field
The invention belongs to network optimisation techniques fields, and in particular to a kind of multiple entry network service function chain optimization method.
Background technique
With the propulsion of SDN/NFV technology, traditional static network service model is no longer satisfied the demand of application.Cause
Tightly coupled relationship between service and special hardware, causes that Internet resources cannot be shared, new business is difficult in its framework
The drawbacks such as fusion.It needs to put into when network expansion more into original deployment new business.Service function chain is by one or more
A virtual network function composition, it is intended to provide complete end-to-end service for network.Service function chain has reduction network construction
With O&M cost, raising network resource utilization, the promotion advantages such as network and service deployment speed.
Research currently for service function chain is concentrated mainly on the single outlet of single entrance and branchiess service chaining portion
In administration's problem, there are no consider multiple entry service chaining deployment bring service node share and collision problem.Therefore, towards connecing more
Access point sends request, and single service provider provides the network of response, such as mobile social networking, the portion EPC of mobile communications network
Point etc., it is necessary to, time delay and energy consumption lower service function chain Deployment Algorithm more efficient for the Demand Design of user.Meanwhile
Multiple entry service function chain algorithm can preferably agree with the network environment of real world, therefore have more compared to traditional algorithm
Application value.
Service function chain (Service Function Chain, SFC) is a kind of network pipe for Web Service Deployment
Reason scheme, it allows network operator that network function is assigned on universal server.Also, SFC allows dynamic combined empty
Quasi- network function, and be deployed to them in the form of virtual machine (VirtualMachine, VM) according to target predetermined
In network on the server of any position, one group of orderly service function chain-ordering chain is formed.Network function such as firewall is born
Carry balanced device and deep-packet detection system can put in a network most suitable position to meet user, service quality and management
Demand.Compared to traditional network, the service function chain based on NFV can largely get rid of and open up to specific physical network
The dependence flutterred reduces the degree of coupling with the network equipment.It is upper between service and service when data traffic passes through service chaining
It hereafter can shared information.In end-to-end service, service chaining only needs a subseries, so that whole process is more just
It is prompt efficient.
Current service chain deployment scheme lacks the end-to-end service visibility of multiple entry.The network of the single single outlet of entrance
Tend to be simple, it is not representative.In multiple entry network, because network environment is more complicated, once network goes wrong.Network
The exclusion of failure will become complicated, be related to the professional knowledge of more networks and service.When service function chain is crossed over
When multiple data centers or management boundary, which can become more acute.
When deployment services function chain, the Topological dependence of service function chain directly determines the complexity of network
Property, the service function chain deployment issue in ecotopia is mainly considered in current service chain solution, and service section is not considered
The networks such as point failure burst factor.The simple operations of service function sequence etc are changed in service function chain, it is necessary to change
Logic or physical topology.The some pairs of higher networks of reliability requirement such as seem outstanding if problem this kind of in industry internet
For protrusion.When needing deployment services in production environment, equipment downtime will lead to if there are error configurations, give production department
Door brings massive losses.
Summary of the invention
Goal of the invention of the invention is：In order to solve problem above existing in the prior art, the invention proposes one kind
Multiple entry network service function chain optimization method.
The technical scheme is that：A kind of multiple entry network service function chain optimization method, includes the following steps：
A, network environment is initialized, time delay weight coefficient and energy consumption weight coefficient are set；
B, network request is judged whether there is；If so, then by the service request in period τ according to entry number and service
Request type is classified, and entrance set and service request type set are established；If it is not, then carrying out step E；
C, all kinds of service requests in step A are ranked up according to weight vectors, obtain the ordered set being incremented by by numerical value,
And export service request policing type sequential vector；
D, service function deployment is carried out using Parallels-merge algorithm and energy optimization is handled；
E, the virtual network function that do not dispose is judged whether there is；If so, return step B；If it is not, then operation terminates.
Further, weight vectors are expressed as in step C：
Wk=pk×fk
Wherein, WkFor weight vectors, pkFor k-th of element in the service request type set in period τ, fkFor request
K-th of element in frequency vector.
Further, step D carries out service function deployment and energy optimization processing using Parallels-merge algorithm,
Specifically include it is following step by step：
D1, judgement currently need to dispose with the presence or absence of service request；If so, carrying out step D2；If it is not, then operating knot
Beam；
D2, each entry request quantity, service request type set, entrance set and service request policing type are obtained
Sequential vector；
The sequencing of D3, the service request provided according to service request policing type sequential vector, using being based on
Ordered vector in step B is mapped in physical network by the K shortest path algorithm of dijkstra's algorithm, obtains a plurality of shortest path collection
Close P；
D4, judge whether shortest path set P is empty set；If so, the error message that output network capacity is full；If it is not,
Then carry out step D5；
D5, judge whether the number of nodes for including on shortest path set P is greater than required for current service request type virtually
Service number；If so, carrying out step D6；If it is not, then return step D3；
D6, the shortest path in shortest path set is merged by merging identical Virtual Service type using backtracking method, and counted
Calculate time delay, the energy consumption for merging and being followed by the shortest path and access port of portal content provider to content supplier, deposit Dvec with
Evec matrix；
D7, judge whether Dvec and Evec matrix is empty set；If so, operation terminates；If it is not, carrying out step D8；
D8, judge whether increased time delay is less than the energy consumption of reduction；If so, merging Virtual Service function；If it is not, then returning
Return step D7；
D9, network topology side right matrix is updated, and judges whether network reliability is greater than reliability thresholds；If so, behaviour
Work terminates；If it is not, then return step D7.
Further, the shortest path for merging and being followed by portal content provider is calculated in step D6, is expressed as：
D (AP, CP)=d (AP, vi)+d(vi,CP)
Wherein, d (AP, CP) indicates the shortest distance between access point AP to content supplier CP, d (AP, vi) indicate from AP
To the node v that placed some Virtual Service functioniDistance, d (vi, CP) and it indicates to placed the section of some Virtual Service function
Point viTo the distance of CP.
Further, step D6 further includes by d (AP, vi) and d (AP, vj)+l(ei,j) compare：
As d (AP, vi)=d (AP, vj)+l(ei,j) when, In (vj)=In (vi)；
As d (AP, vi) > d (AP, vj)+l(ei,j) when, In (vj)=In (vi)+d(AP,vj)-d(AP,vi)+l(ei,j)；
As d (AP, vi) < d (AP, vj)+l(ei,j) when, In (vj)=In (vi)+2l(ei,j)；
Wherein, l (ei,vi) it is node viWith node vjBetween minimal time delay, In () be time delay increment, l (ei,j) be
Current service chain layout strategy band loop.
The beneficial effects of the invention are as follows：The present invention can carry out network for the weighted value of different energy consumptions and time delay excellent
Change, quickly processing and coordination multiple entry network delay and energy optimization problem, meter of the message in service catenary system is effectively reduced
Resource occupation is calculated, the end-to-end time delay during long-play is reduced, to improve service chaining system stability, optimizes user
Service experience.
Detailed description of the invention
Fig. 1 is the flow diagram of multiple entry network service function chain optimization method of the invention.
Fig. 2 is the flow diagram of Parallels-merge algorithm in the embodiment of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.
As shown in Figure 1, being the flow diagram of multiple entry network service function chain optimization method of the invention.It is a kind of to enter more
Mouth network service function chain optimization method, includes the following steps：
A, network environment is initialized, time delay weight coefficient and energy consumption weight coefficient are set；
B, network request is judged whether there is；If so, then by the service request in period τ according to entry number and service
Request type is classified, and entrance set and service request type set are established；If it is not, then carrying out step E；
C, all kinds of service requests in step A are ranked up according to weight vectors, obtain the ordered set being incremented by by numerical value,
And export service request policing type sequential vector；
D, service function deployment is carried out using Parallels-merge algorithm and energy optimization is handled；
E, the virtual network function that do not dispose is judged whether there is；If so, return step B；If it is not, then operation terminates.
In an alternate embodiment of the present invention where, above-mentioned steps A obtains physical network G=(N, L), multiple entry network
Access point AP (Access_Point) and content supplier CP (Content_Provider), setting meet the time delay of user QoS
Weight α, energy consumption weight beta, the set Policy={ p of the service request type in period τ1,p2,p3...pnAnd corresponding ask
Seek frequency vector F={ f1,f2,f3...fn, reliability requirement R ∈ (0,1).
In an alternate embodiment of the present invention where, all entry numbers in above-mentioned steps B traverses network are asked with service
Type is sought, and is classified according to entry number and service request type, entrance set and service request type set are established.
In an alternate embodiment of the present invention where, above-mentioned steps C classifies to all kinds of service requests in period τ
With weighting sequence processing, weight sequencing is pressed to every class service request p, the weight vectors of all kinds of service requests is calculated, is expressed as：
Wk=pk×fk
Wherein, WkFor weight vectors, pkFor k-th of element in the service request type set Policy in period τ, fk
For k-th of element in request frequency vector.
Again to the weight vectors W of all kinds of service requestskIt is ranked up, obtains the ordered set being incremented by by numerical value, and export
Service request policing type sequential vector.
In an alternate embodiment of the present invention where, above-mentioned steps D carries out service function using Parallels-merge algorithm
It can dispose and energy optimization is handled, as shown in Fig. 2, for the process signal of Parallels-merge algorithm in the embodiment of the present invention
Figure, specifically include it is following step by step：
D1, judgement currently need to dispose with the presence or absence of service request；If so, carrying out step D2；If it is not, then operating knot
Beam；
D2, each entry request quantity, service request type set, entrance set and service request policing type are obtained
Sequential vector；
The sequencing of D3, the service request provided according to service request policing type sequential vector, using being based on
Ordered vector in step B is mapped in physical network by the K shortest path algorithm of dijkstra's algorithm, obtains a plurality of shortest path collection
Close P；
D4, judge whether shortest path set P is empty set；If so, the error message that output network capacity is full；If it is not,
Then carry out step D5；
D5, judge whether the number of nodes for including on shortest path set P is greater than required for current service request type virtually
Service number；If so, carrying out step D6；If it is not, then return step D3；
D6, the shortest path in shortest path set is merged by merging identical Virtual Service type using backtracking method, and counted
Calculate time delay, the energy consumption for merging and being followed by the shortest path and access port of portal content provider to content supplier, deposit Dvec with
Evec matrix；
D7, judge whether Dvec and Evec matrix is empty set；If so, operation terminates；If it is not, carrying out step D8；
D8, judge whether increased time delay is less than the energy consumption of reduction；If so, merging Virtual Service function；If it is not, then returning
Return step D7；
D9, network topology side right matrix is updated, and judges whether network reliability is greater than reliability thresholds；If so, behaviour
Work terminates；If it is not, then return step D7.
In an alternate embodiment of the present invention where, the access point of above-mentioned steps D2 acquisition multiple entry network and each access
The service request type of point, according to ordered vector Vector W in step AkThe high weighting service of prioritized deployment.
In an alternate embodiment of the present invention where, above-mentioned steps D3 is obtained using shortest path first from access port to interior
Hold the shortest path p of provider CP0, k=1, Di=d records pathi；
In an alternate embodiment of the present invention where, above-mentioned steps D4 judges from the service request that access point is initiated to content
Provider paths traversed PathkIt whether is empty；If so, illustrating that current network cannot dispose the service function of the type
Chain, the full error message of output network capacity；If it is not, then carrying out step D5；
In an alternate embodiment of the present invention where, above-mentioned steps D5 judges that the number of nodes for including on shortest path set P is
It is no be greater than current service request type policy required for Virtual Service number, due to service function chain must satisfy it is end-to-end
What is serviced is reliable, if path meets the number that node number is greater than Virtual Service, i.e., by obtaining, residue can on shortest path
The number of nodes of service is provided, judges whether number of nodes is greater than Virtual Service number, if so then execute step D6；If the section of chain road
Points then return to step D3 less than Virtual Service number and calculate new shortest path.
In an alternate embodiment of the present invention where, above-mentioned steps D6 is solved using backtracking method and is provided from access port to content
The kth shortest path of the shortest path of quotient CP, and calculate a point v on access port to the shortest path of content supplieriAnd its
Adjacent node vjIncreased time delay；It is expressed as：
D (AP, CP)=d (AP, vi)+d(vi,CP)
Wherein, d (AP, CP) indicates the shortest distance between access point AP to content supplier CP, d (AP, vi) indicate from AP
To the node v that placed some Virtual Service functioniDistance, d (vi, CP) and it indicates to placed the section of some Virtual Service function
Point viTo the distance of CP；
According to Graph Theory by d (AP, vi) and d (AP, vj)+l(ei,j) compare：
As d (AP, vi)=d (AP, vj)+l(ei,j) when, In (vj)=In (vi), k=k+1；
As d (AP, vi) > d (AP, vj)+l(ei,j) when, In (vj)=In (vi)+d(AP,vj)-d(AP,vi)+l(ei,j)；
As d (AP, vi) < d (AP, vj)+l(ei,j) when, In (vj)=In (vi)+2l(ei,j)；
Wherein, l (ei,vi) it is node viWith node vjBetween minimal time delay, In () be time delay increment, l (ei,j) be
Current service chain layout strategy band loop.
In an alternate embodiment of the present invention where, above-mentioned steps D8 judges whether α Δ D is less than β Δ E, and Δ D is increased
Time delay value, Δ E are the reduced value of energy consumption；If so, merging Virtual Service function, opened from the last one service in farthest path
Begin to shortest path loop fusion；If it is not, then carrying out step D7；
The present invention is from the service request type set Policy in the access point acquisition time section τ of multiple entry network, to every
The service request set of a type counts the quantity of service of the service request type in the access point AP of all multiple entry networks, directly
To the last one service request policy-k is deployed to, deployment completion service request k is just moved out every time, obtains service request
Physical location of the type set Policy corresponding with service in physical network GNetwork overall delay
Σ D and physical network total energy consumption are empty set until P.It indicates to use fnType of service, and it is deployed in nkPhysics section
On point, k indicates that k-th of Ingress node, i indicate the i-th class service request, j1Indicate the jth of the service request1A service；Indicate occupied bandwidth bi, and it is deployed in lkOn physical link；j2Indicate the jth that the service request occupies2
A physical link；
In an alternate embodiment of the present invention where, above-mentioned steps D9 updates network topology side right matrix, and judges network
Whether reliability is greater than reliability thresholds；If so, operation terminates；If it is not, then return step D7, is wanted according to the reliability of setting
The summation reliability thresholds insecure service of polishing in a network, until 1- Π (1-r) >=R；Wherein r be every a kind of service can
By property coefficient, company multiplies the unreliable coefficient r of all services, until meeting coefficient of reliability R.
The present invention is based on Dynamic Programmings and Principle of Statistics, according to each access node within a time short enough
Service request type quantity carries out link distribution, and the link of dynamic backtracking later is reallocated, and is existed according to current network horsepower requirements
Under the premise of guaranteeing end-to-end service, judge whether the stabilization and section for needing to exchange network for by sacrificing certain network delay
Energy；It solves the time delay Yu energy consumption complex optimization problem of service function chain Dynamical Deployment under multiple entry network, passes through SDN switch
It obtains the topology information of current network and saves as adjacency matrix/adjacency list, it is assumed that network has multiple in defined very short time τ
Access point AP is simultaneously emitted by a plurality of network service request, by statistical fractals request type and frequency, and according to statistical result point
Weighted value with different service requests, the high service request of prioritized deployment weight, and it is therein certain according to horsepower requirements merging
It services to reach the tradeoff and optimization of time delay and energy consumption, reduces network computing resources expense.
Those of ordinary skill in the art will understand that the embodiments described herein, which is to help reader, understands this hair
Bright principle, it should be understood that protection scope of the present invention is not limited to such specific embodiments and embodiments.This field
Those of ordinary skill disclosed the technical disclosures can make according to the present invention and various not depart from the other each of essence of the invention
The specific variations and combinations of kind, these variations and combinations are still within the scope of the present invention.
Claims (5)
1. a kind of multiple entry network service function chain optimization method, which is characterized in that include the following steps：
A, network environment is initialized, time delay weight coefficient and energy consumption weight coefficient are set；
B, network request is judged whether there is；If so, then by the service request in period τ according to entry number and service request
Type is classified, and entrance set and service request type set are established；If it is not, then carrying out step E；
C, all kinds of service requests in step A are ranked up according to weight vectors, obtain the ordered set being incremented by by numerical value, and defeated
Service request policing type sequential vector out；
D, service function deployment is carried out using Parallels-merge algorithm and energy optimization is handled；
E, the virtual network function that do not dispose is judged whether there is；If so, return step B；If it is not, then operation terminates.
2. multiple entry network service function chain optimization method as described in claim 1, which is characterized in that in step C weight to
Amount is expressed as：
Wk=pk×fk
Wherein, WkFor weight vectors, pkFor k-th of element in the service request type set in period τ, fkFor request frequency
K-th of element in vector.
3. multiple entry network service function chain optimization method as claimed in claim 2, which is characterized in that step D is used
Parallels-merge algorithm carry out service function deployment and energy optimization processing, specifically include it is following step by step：
D1, judgement currently need to dispose with the presence or absence of service request；If so, carrying out step D2；If it is not, then operation terminates；
D2, each entry request quantity, service request type set, entrance set and service request policing type sequence are obtained
Vector；
The sequencing of D3, the service request provided according to service request policing type sequential vector, using being based on
Ordered vector in step B is mapped in physical network by the K shortest path algorithm of dijkstra's algorithm, obtains a plurality of shortest path collection
Close P；
D4, judge whether shortest path set P is empty set；If so, the error message that output network capacity is full；If it is not, then into
Row step D5；
D5, judge whether the number of nodes for including on shortest path set P is greater than Virtual Service required for current service request type
Number；If so, carrying out step D6；If it is not, then return step D3；
D6, the shortest path in shortest path set is merged by merging identical Virtual Service type using backtracking method, and calculates conjunction
And it is followed by time delay, the energy consumption of the shortest path and access port of portal content provider to content supplier, it is stored in Dvec and Evec square
Battle array；
D7, judge whether Dvec and Evec matrix is empty set；If so, operation terminates；If it is not, carrying out step D8；
D8, judge whether increased time delay is less than the energy consumption of reduction；If so, merging Virtual Service function；If it is not, then returning to step
Rapid D7；
D9, network topology side right matrix is updated, and judges whether network reliability is greater than reliability thresholds；If so, operation knot
Beam；If it is not, then return step D7.
4. multiple entry network service function chain optimization method as claimed in claim 3, which is characterized in that calculate and close in step D6
And it is followed by the shortest path of portal content provider, it is expressed as：
D (AP, CP)=d (AP, vi)+d(vi,CP)
Wherein, d (AP, CP) indicates the shortest distance between access point AP to content supplier CP, d (AP, vi) indicate from AP to placement
The node v of some Virtual Service functioniDistance, d (vi, CP) and it indicates to placed the node v of some Virtual Service functioniIt arrives
The distance of CP.
5. multiple entry network service function chain optimization method as claimed in claim 4, which is characterized in that step D6 further include by
d(AP,vi) and d (AP, vj)+l(ei,j) compare：
As d (AP, vi)=d (AP, vj)+l(ei,j) when, In (vj)=In (vi)；
As d (AP, vi) > d (AP, vj)+l(ei,j) when, In (vj)=In (vi)+d(AP,vj)-d(AP,vi)+l(ei,j)；
As d (AP, vi) < d (AP, vj)+l(ei,j) when, In (vj)=In (vi)+2l(ei,j)；
Wherein, l (ei,vi) it is node viWith node vjBetween minimal time delay, In () be time delay increment, l (ei,j) it is current clothes
Chain layout strategy be engaged in loop.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810659293.2A CN108923961B (en) | 2018-06-25 | 2018-06-25 | Multi-entry network service function chain optimization method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810659293.2A CN108923961B (en) | 2018-06-25 | 2018-06-25 | Multi-entry network service function chain optimization method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108923961A true CN108923961A (en) | 2018-11-30 |
| CN108923961B CN108923961B (en) | 2020-02-21 |
Family
ID=64421092
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810659293.2A Active CN108923961B (en) | 2018-06-25 | 2018-06-25 | Multi-entry network service function chain optimization method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108923961B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111614779A (en) * | 2020-05-28 | 2020-09-01 | 浙江工商大学 | Dynamic adjustment method for optimizing and accelerating micro service chain |
| CN114172820A (en) * | 2021-11-26 | 2022-03-11 | 广东技术师范大学 | Cross-domain SFC dynamic deployment method, device, computer equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105721535A (en) * | 2014-12-23 | 2016-06-29 | 英特尔公司 | Parallel processing of service functions in service function chains |
| CN107124303A (en) * | 2017-04-19 | 2017-09-01 | 电子科技大学 | The service chaining optimization method of low transmission time delay |
| CN107332913A (en) * | 2017-07-04 | 2017-11-07 | 电子科技大学 | A kind of Optimization deployment method of service function chain in 5G mobile networks |
| CN107395506A (en) * | 2017-09-07 | 2017-11-24 | 电子科技大学 | A kind of service function chain dispositions method of propagation delay time optimization |
| US20180097696A1 (en) * | 2016-09-30 | 2018-04-05 | International Business Machines Corporation | System, method and computer program product for network function optimization based on locality and function type |
-
2018
- 2018-06-25 CN CN201810659293.2A patent/CN108923961B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105721535A (en) * | 2014-12-23 | 2016-06-29 | 英特尔公司 | Parallel processing of service functions in service function chains |
| US20180097696A1 (en) * | 2016-09-30 | 2018-04-05 | International Business Machines Corporation | System, method and computer program product for network function optimization based on locality and function type |
| CN107124303A (en) * | 2017-04-19 | 2017-09-01 | 电子科技大学 | The service chaining optimization method of low transmission time delay |
| CN107332913A (en) * | 2017-07-04 | 2017-11-07 | 电子科技大学 | A kind of Optimization deployment method of service function chain in 5G mobile networks |
| CN107395506A (en) * | 2017-09-07 | 2017-11-24 | 电子科技大学 | A kind of service function chain dispositions method of propagation delay time optimization |
Non-Patent Citations (1)
| Title |
|---|
| 刘蓓: ""基于NFV的网络中虚拟服务功能链的部署和迁移"", 《中国优秀硕士学位论文全文数据库（电子期刊），信息科技辑》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111614779A (en) * | 2020-05-28 | 2020-09-01 | 浙江工商大学 | Dynamic adjustment method for optimizing and accelerating micro service chain |
| CN114172820A (en) * | 2021-11-26 | 2022-03-11 | 广东技术师范大学 | Cross-domain SFC dynamic deployment method, device, computer equipment and storage medium |
| CN114172820B (en) * | 2021-11-26 | 2024-03-05 | 广东技术师范大学 | Cross-domain SFC dynamic deployment method, device, computer equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108923961B (en) | 2020-02-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108260169B (en) | QoS guarantee-based dynamic service function chain deployment method | |
| Wang et al. | Algorithms for a facility location problem with stochastic customer demand and immobile servers | |
| Tong et al. | Adaptive call admission control under quality of service constraints: a reinforcement learning solution | |
| CN108900358A (en) | Virtual network function dynamic migration method based on deepness belief network resource requirement prediction | |
| CN103746852B (en) | Service routing configuration method and network management equipment | |
| Popovskij et al. | Control and adaptation in telecommunication systems: Mathematical Foundations | |
| CN108833279A (en) | The method of Multi-constraint QoS paths based on business classification in software defined network | |
| Xie et al. | Virtualized network function forwarding graph placing in SDN and NFV-enabled IoT networks: A graph neural network assisted deep reinforcement learning method | |
| CN109831522A (en) | A kind of vehicle connection cloud and mist system dynamic resource Optimal Management System and method based on SMDP | |
| CN104468408B (en) | For dynamically adjusting the method and control centre's server of service bandwidth | |
| CN107454019A (en) | Software defined network distribution method of dynamic bandwidth, device, equipment and storage medium | |
| CN110298381A (en) | A kind of cloud security service functional tree Network Intrusion Detection System | |
| CN112217725B (en) | Delay optimization method based on edge calculation | |
| CN108206790A (en) | A kind of selection of SDN joint routes and resource allocation methods based on network slice | |
| CN108510150A (en) | A kind of spinning CPS and its real-time task processing method based on edge calculations | |
| CN108923961A (en) | A kind of multiple entry network service function chain optimization method | |
| CN107682191A (en) | A kind of power scheduling network information centralized management method and system | |
| Ebrahimi et al. | Joint resource and admission management for slice-enabled networks | |
| CN106161603A (en) | A kind of method of networking, equipment and framework | |
| CN108616377A (en) | Business chain virtual machine control method and system | |
| Li et al. | Efficient adaptive matching for real-time city express delivery | |
| CN109636338A (en) | A kind of broad band photoelectrical operation management platform system | |
| CN108718287A (en) | Data exchange system and its method for building up and device and communication system | |
| Brown et al. | Optimizing admission control while ensuring quality of service in multimedia networks via reinforcement learning | |
| Hojeij et al. | Dynamic placement of O-CU and O-DU functionalities in open-ran architecture |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |