CN111083578B - Multi-objective optimization method for service classification light path roundabout route - Google Patents
Multi-objective optimization method for service classification light path roundabout route Download PDFInfo
- Publication number
- CN111083578B CN111083578B CN201911217794.6A CN201911217794A CN111083578B CN 111083578 B CN111083578 B CN 111083578B CN 201911217794 A CN201911217794 A CN 201911217794A CN 111083578 B CN111083578 B CN 111083578B
- Authority
- CN
- China
- Prior art keywords
- data
- light path
- text
- path
- power communication
- 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.)
- Active
Links
- 238000005457 optimization Methods 0.000 title claims abstract description 33
- 238000000034 method Methods 0.000 title claims abstract description 21
- 230000003287 optical effect Effects 0.000 claims abstract description 67
- 238000004891 communication Methods 0.000 claims abstract description 50
- 230000005540 biological transmission Effects 0.000 claims abstract description 34
- 238000000605 extraction Methods 0.000 claims abstract description 10
- 230000002068 genetic effect Effects 0.000 claims abstract description 10
- 238000004364 calculation method Methods 0.000 description 5
- 238000012423 maintenance Methods 0.000 description 3
- 230000004075 alteration Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q11/00—Selecting arrangements for multiplex systems
- H04Q11/0001—Selecting arrangements for multiplex systems using optical switching
- H04Q11/0062—Network aspects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q11/00—Selecting arrangements for multiplex systems
- H04Q11/0001—Selecting arrangements for multiplex systems using optical switching
- H04Q11/0062—Network aspects
- H04Q2011/0073—Provisions for forwarding or routing, e.g. lookup tables
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q11/00—Selecting arrangements for multiplex systems
- H04Q11/0001—Selecting arrangements for multiplex systems using optical switching
- H04Q11/0062—Network aspects
- H04Q2011/0079—Operation or maintenance aspects
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q11/00—Selecting arrangements for multiplex systems
- H04Q11/0001—Selecting arrangements for multiplex systems using optical switching
- H04Q11/0062—Network aspects
- H04Q2011/0086—Network resource allocation, dimensioning or optimisation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q11/00—Selecting arrangements for multiplex systems
- H04Q11/0001—Selecting arrangements for multiplex systems using optical switching
- H04Q11/0062—Network aspects
- H04Q2011/009—Topology aspects
Abstract
The invention provides a multi-objective optimization method for a service-classified light path roundabout route. Obtaining electric power communication standing book data through field characteristic analysis and field characteristic extraction according to the electric power communication standing book text, and establishing a field path relation by combining the electric power communication standing book data so as to construct an optical transmission topological graph; analyzing and associating the service resources borne by the optical transmission topological graph by combining with the electric power communication standing book data; sequentially searching all circuitous routes of each light path in the optical transmission topological graph through a depth-first traversal algorithm; and constructing a multi-objective optimization model of the light path roundabout routes, and solving the optimal route in all the roundabout routes of each light path through a genetic algorithm. The invention realizes the intelligent optimization of the light path roundabout route and improves the efficiency of handling the power communication fault.
Description
Technical Field
The invention belongs to the technical field of power communication, and particularly relates to a multi-objective optimization method for a service-classified light path roundabout route.
Background
With the construction of smart power grids, power communication networks play an increasingly important role. The communication network light path alternate route optimization is regularly developed, and the method is an effective means for improving the operation and maintenance working capacity. Although the conventional optical path roundabout routing can provide the selectable optimized routing, the selectable optimized routing does not cover all the selectable routes, and the given selectable optimized routing does not consider the traffic carried on the optical path of the power communication network. Due to the rapid development of the communication network, especially the rapid increase of the light path bearing service, great difficulty is further brought to the development of the traditional communication network light path roundabout route optimization. Therefore, by combining the optical path route optimization method of service classification, the selectable optimized route of the communication network is researched, the fault handling efficiency of communication professionals can be rapidly improved, the service technical knowledge and the operation and maintenance management level are comprehensively improved, and the smooth information of various services of the communication network is guaranteed.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a service classification multi-objective optimization method for a roundabout light path route.
The technical scheme of the invention is a multi-objective optimization method for a service-classified light path roundabout route, which specifically comprises the following steps:
step 1: obtaining electric power communication standing book data through field characteristic analysis and field characteristic extraction according to the electric power communication standing book text, and establishing a field path relation by combining the electric power communication standing book data so as to construct an optical transmission topological graph;
step 2: analyzing and associating the service resources borne by the optical transmission topological graph by combining with the electric power communication standing book data;
and step 3: sequentially searching all circuitous routes of each light path in the optical transmission topological graph through a depth-first traversal algorithm;
and 4, step 4: constructing a multi-objective optimization model of the light path roundabout routes, and solving an optimal route in all the roundabout routes of each light path through a genetic algorithm;
preferably, the power communication ledger text in step 1 includes:
the method comprises the following steps of starting site name text, terminating site name text, service importance level text, site alarm quantity text, light path length text and light path historical failure rate text;
the field characteristic analysis in the step 1 is as follows:
respectively carrying out field characteristic analysis on a starting site name text, a terminating site name text, a service importance level text, a site alarm quantity text, a light path length text and a light path historical fault rate text, namely counting key prompt symbols appearing in each power communication ledger text;
the field feature extraction in the step 1 is as follows:
according to the content behind the key prompt, obtaining corresponding electric power communication ledger data in each electric power communication ledger text by a character extraction method, namely initial site name data, termination site name data, service importance level data, site alarm quantity data, optical path length data and site historical fault rate data;
the field path relationship establishment in the step 1 is as follows:
establishing a field path relation according to the initial station name data and the termination station name data, specifically a light path from the initial station name data to the termination station name data;
the step 1 of constructing the optical transmission topological graph comprises the following steps:
and establishing a field path relation according to all initial site name data and ending site name data of the electric power communication ledger data in sequence, thereby obtaining an optical transmission topological graph.
Preferably, the service resources associated with the analysis of the power communication ledger data in step 2 are:
constructing different types of business key fields, and classifying the business name data by combining the business key fields with a field identification method so as to obtain different types of business data;
and traversing the path relation of each field in the step 1 in sequence, and counting the number of different types of services borne on each light path in the optical transmission topological graph.
Preferably, the sequentially finding all the detour routes of each optical path in the optical transmission topological graph through the depth-first traversal algorithm in step 3 is as follows:
obtaining all detours between the initial station name data and the final station name data in each field path relationship through the each field path relationship in the step 1 and a depth-first traversal algorithm, namely all detours of each light path in the optical transmission topological graph;
preferably, the step 4 of constructing the multi-objective optimization model of the light path roundabout route is as follows:
calculating the transmission distance of the optical path according to the optical path length data in all the circuitous routes of each optical path;
calculating the comprehensive historical fault rate of the stations in each roundabout route according to the historical fault rate data of the stations;
calculating the comprehensive station alarm quantity in each roundabout route according to the station alarm quantity;
calculating the comprehensive load importance rate of each optical path by combining the service importance level data in the step 1 and the number of services bearing different types on each optical path in the step 2, and further calculating the comprehensive load importance rate in each roundabout route by combining the comprehensive load rate of each optical path;
weighting the optical path transmission distance, the comprehensive station historical fault rate, the comprehensive station alarm quantity and the comprehensive load importance rate, and establishing an optical path roundabout route multi-target optimization model by using the minimization of a weighting result as an optimization target;
in step 4, the genetic algorithm solves the optimal route in all the detour routes of each light path as follows:
and according to the multi-objective optimization model of the light path roundabout route, optimizing by using a genetic algorithm to minimize the weighted result as an optimization objective to obtain the optimal route.
The invention can improve the fault handling efficiency of communication professionals, comprehensively improve the service technical knowledge and the operation and maintenance management level, and ensure the stable operation of various services of the communication network.
Drawings
FIG. 1: the method of the invention is a flow chart.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention introduces data in Huashi 10G network management system as original data to develop the specific implementation mode of the invention.
The following describes a method for multi-objective optimization of light path roundabout routes for service classification according to an embodiment of the present invention with reference to fig. 1, which specifically includes the following steps:
step 1: obtaining electric power communication standing book data through field characteristic analysis and field characteristic extraction according to the electric power communication standing book text, and establishing a field path relation by combining the electric power communication standing book data so as to construct an optical transmission topological graph;
the electric power communication standing book text is electric power communication historical data obtained through data in a 10G network management system;
in step 1, the power communication standing book text comprises:
the method comprises the following steps of starting site name text, terminating site name text, service importance level text, site alarm quantity text, light path length text and light path historical failure rate text;
the field characteristic analysis in the step 1 is as follows:
respectively carrying out field characteristic analysis on a starting site name text, a terminating site name text, a service importance level text, a site alarm quantity text, a light path length text and a light path historical fault rate text, namely counting key prompt symbols appearing in each power communication ledger text;
the field feature extraction in the step 1 is as follows:
according to the content behind the key prompt, obtaining corresponding electric power communication ledger data in each electric power communication ledger text, namely initial site name data, termination site name data, service importance level data, site alarm quantity data, optical path length data and site historical fault rate data, by a character extraction method, namely a word frequency reverse file frequency algorithm;
the field path relationship establishment in the step 1 is as follows:
establishing a field path relation according to the initial station name data and the termination station name data, specifically a light path from the initial station name data to the termination station name data;
the step 1 of constructing the optical transmission topological graph comprises the following steps:
and establishing a field path relation according to all initial site name data and ending site name data of the electric power communication ledger data in sequence, thereby obtaining an optical transmission topological graph.
Step 2: analyzing and associating the service resources borne by the optical transmission topological graph by combining with the electric power communication standing book data;
in step 2, the service resources associated with the analysis of the power communication ledger data are:
constructing different types of business key fields, classifying the business name data by combining the business key fields with a field identification method, namely a word matching method, thereby obtaining different types of business data, wherein the different types of business data are divided into:
the importance levels of the relay protection service data, the dispatching automation service data, the data communication network service data and the conference television service data are reduced in sequence, and the load importance weights are 0.6, 0.2, 0.1 and 0.1 respectively;
traversing the path relation of each field in the step 1 in sequence, and counting the number of different types of services borne on each light path in the optical transmission topological graph, namely respectively counting
And step 3: sequentially searching all circuitous routes of each light path in the optical transmission topological graph through a depth-first traversal algorithm;
in step 3, sequentially finding all detour routes of each optical path in the optical transmission topological graph through the depth-first traversal algorithm is as follows:
obtaining all detours between the initial station name data and the final station name data in each field path relationship through the each field path relationship in the step 1 and a depth-first traversal algorithm, namely all detours of each light path in the optical transmission topological graph;
and 4, step 4: constructing a multi-objective optimization model of the light path roundabout routes, and solving an optimal route in all the roundabout routes of each light path through a genetic algorithm;
the step 4 of constructing the multi-objective optimization model of the light path roundabout route comprises the following steps:
in all the roundabout routes of each optical path, calculating the optical path transmission distance according to the optical path length data, wherein the specific calculation method comprises the following steps:
wherein Q isi,jThe number of alternate routes from the start site i to the end site j, start is the number of start sites, end is the number of end sites, Lx,i,jThe optical path transmission distance of the x-th alternate route between the starting station i and the ending station j, Nx,i,jThe number of light paths for the xth alternate route from the starting station i to the ending station j, Sx,i,j,kThe distance of the kth optical path in the xth detour route from the starting point i to the ending point j is shown as pathx,i,j
And calculating the comprehensive historical fault rate of the station in each roundabout route according to the historical fault rate data of the station, wherein the specific calculation method comprises the following steps:
wherein alpha isx,i,j,kThe station historical failure rate of the kth optical path in the xth roundabout route from the starting point i to the ending station j is set;
and calculating the comprehensive station alarm quantity in each roundabout route according to the station alarm quantity, wherein the specific calculation method comprises the following steps:
wherein, betax,i,j,kThe station alarm number of the kth optical path in the xth roundabout route from the starting point i to the ending station j;
and (2) calculating the comprehensive load importance rate of each optical path by combining the service importance levels in the step (1) and the number of services bearing different types on each optical path in the step (2), wherein the specific calculation method comprises the following steps:
wherein, loadx,i,j,kIs the comprehensive load importance rate, M, of the kth optical path in the xth roundabout route from the starting point i to the ending point jx,i,j,kIs the number of the service in the kth optical path in the xth alternate route from the starting point i to the ending point j, gammax,i,j,k,lCombining the l-th service in the k-th optical path in the xth roundabout route between the starting point i and the ending point j with the load importance weight corresponding to the service importance level in the step 1;
and further calculating the comprehensive load importance rate in each roundabout route by combining the comprehensive load rate of each optical path, wherein the specific calculation method comprises the following steps:
weighting the optical path transmission distance, the comprehensive station historical fault rate, the comprehensive station alarm quantity and the comprehensive load importance rate specifically comprises the following steps:
η1Lx,i,j+η2Ex,i,j+η3Wx,i,j+η4totalx,i,j
wherein eta is1、η2、η3、η4Respectively a first weighting coefficient, a second weighting coefficient, a third weighting coefficient and a fourth weighting coefficient;
and establishing a multi-objective optimization model of the light path roundabout route by using the minimization of the weighted result as an optimization objective, which specifically comprises the following steps:
Target:min(η1Lx,i,j+η2Ex,i,j+η3Wx,i,j+η4totalx,i,j)
in step 4, the genetic algorithm solves the optimal route in all the circuitous routes of each light path, and specifically comprises the following steps:
through genetic algorithm inQ between originating site i to terminating site ji,jOptimizing in a roundabout route, taking target as an optimization target, and combining the historical data of power communication obtained by the 10G network management system in the step 1 to obtain the optimal route from the starting station i to the ending station j as pathx*,i,j。
It should be understood that parts of the specification not set forth in detail are well within the prior art.
It should be understood that the above description of the preferred embodiments is given for clarity and not for any purpose of limitation, and that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (4)
1. A multi-objective optimization method for service-classified light path roundabout routing is characterized by comprising the following steps:
step 1: obtaining electric power communication standing book data through field characteristic analysis and field characteristic extraction according to the electric power communication standing book text, and establishing a field path relation by combining the electric power communication standing book data so as to construct an optical transmission topological graph;
step 2: analyzing and associating the service resources borne by the optical transmission topological graph by combining with the electric power communication standing book data;
and step 3: sequentially searching all circuitous routes of each light path in the optical transmission topological graph through a depth-first traversal algorithm;
and 4, step 4: constructing a multi-objective optimization model of the light path roundabout routes, and solving an optimal route in all the roundabout routes of each light path through a genetic algorithm;
in step 1, the power communication standing book text comprises:
the method comprises the following steps of starting site name text, terminating site name text, service importance level text, site alarm quantity text, light path length text and light path historical failure rate text;
the field characteristic analysis in the step 1 is as follows:
respectively carrying out field characteristic analysis on a starting site name text, a terminating site name text, a service importance level text, a site alarm quantity text, a light path length text and a light path historical fault rate text, namely counting key prompt symbols appearing in each power communication ledger text;
the field feature extraction in the step 1 is as follows:
according to the content behind the key prompt, obtaining corresponding electric power communication ledger data in each electric power communication ledger text by a character extraction method, namely initial site name data, termination site name data, service importance level data, site alarm quantity data, optical path length data and site historical fault rate data;
the field path relationship establishment in the step 1 is as follows:
establishing a field path relation according to the initial station name data and the termination station name data, specifically a light path from the initial station name data to the termination station name data;
the step 1 of constructing the optical transmission topological graph comprises the following steps:
and establishing a field path relation according to all initial site name data and ending site name data of the electric power communication ledger data in sequence, thereby obtaining an optical transmission topological graph.
2. The method for multi-objective optimization of light path roundabout routing for traffic classification as claimed in claim 1, wherein: in step 2, the service resources associated with the analysis of the power communication ledger data are:
constructing different types of business key fields, and classifying the business name data by combining the business key fields with a field identification method so as to obtain different types of business data;
and traversing the path relation of each field in the step 1 in sequence, and counting the number of different types of services borne on each light path in the optical transmission topological graph.
3. The method for multi-objective optimization of light path roundabout routing for traffic classification as claimed in claim 1, wherein: in step 3, sequentially finding all detour routes of each optical path in the optical transmission topological graph through the depth-first traversal algorithm is as follows:
through the relationship of each field path in step 1, all detours between the start site name data and the end site name data in the relationship of each field path, that is, all detours of each optical path in the optical transmission topology map, are obtained through a depth-first traversal algorithm.
4. The method for multi-objective optimization of light path roundabout routing for traffic classification as claimed in claim 1, wherein: the step 4 of constructing the multi-objective optimization model of the light path roundabout route comprises the following steps:
calculating the transmission distance of the optical path according to the optical path length data in all the circuitous routes of each optical path;
calculating the comprehensive historical fault rate of the stations in each roundabout route according to the historical fault rate data of the stations;
calculating the comprehensive station alarm quantity in each roundabout route according to the station alarm quantity;
calculating the comprehensive load importance rate of each optical path by combining the service importance level data in the step 1 and the number of services bearing different types on each optical path in the step 2, and further calculating the comprehensive load importance rate in each roundabout route by combining the comprehensive load rate of each optical path;
weighting the optical path transmission distance, the comprehensive station historical fault rate, the comprehensive station alarm quantity and the comprehensive load importance rate, and establishing an optical path roundabout route multi-target optimization model by using the minimization of a weighting result as an optimization target;
in step 4, the genetic algorithm solves the optimal route in all the detour routes of each light path as follows:
and according to the multi-objective optimization model of the light path roundabout route, optimizing by using a genetic algorithm to minimize the weighted result as an optimization objective to obtain the optimal route.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911217794.6A CN111083578B (en) | 2019-12-03 | 2019-12-03 | Multi-objective optimization method for service classification light path roundabout route |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911217794.6A CN111083578B (en) | 2019-12-03 | 2019-12-03 | Multi-objective optimization method for service classification light path roundabout route |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111083578A CN111083578A (en) | 2020-04-28 |
| CN111083578B true CN111083578B (en) | 2021-11-16 |
Family
ID=70312515
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911217794.6A Active CN111083578B (en) | 2019-12-03 | 2019-12-03 | Multi-objective optimization method for service classification light path roundabout route |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111083578B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102231647A (en) * | 2011-06-21 | 2011-11-02 | 中国电力科学研究院 | Fiber communication network service route configuration method used in electric power |
| CN105553843A (en) * | 2015-12-15 | 2016-05-04 | 国网冀北电力有限公司信息通信分公司 | Transmission line relay protection control service channel route configuration method and device |
| CN106209618A (en) * | 2016-07-27 | 2016-12-07 | 国网辽宁省电力有限公司 | A kind of communication mixed networking method and system improving intelligence adapted electric energy effect |
| CN106549779A (en) * | 2015-09-18 | 2017-03-29 | 中国电力科学研究院 | A kind of maximum non-intersect double route collocation method of multiple constraint energy communication service |
| CN106656805A (en) * | 2017-02-17 | 2017-05-10 | 华北电力大学（保定） | Multiservice QoS route selection method of power wide-area communication network |
| CN106656598A (en) * | 2016-12-22 | 2017-05-10 | 云南电网有限责任公司 | Method and system for configuring alternative route of key service of electric power communication network |
| CN110417664A (en) * | 2019-07-31 | 2019-11-05 | 国家电网有限公司信息通信分公司 | Business route distribution method and device based on power telecom network |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8923328B2 (en) * | 2007-11-07 | 2014-12-30 | Brocade Communications Systems, Inc. | Method and system for facilitating application-oriented quality of service in a fibre channel network |
-
2019
- 2019-12-03 CN CN201911217794.6A patent/CN111083578B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102231647A (en) * | 2011-06-21 | 2011-11-02 | 中国电力科学研究院 | Fiber communication network service route configuration method used in electric power |
| CN106549779A (en) * | 2015-09-18 | 2017-03-29 | 中国电力科学研究院 | A kind of maximum non-intersect double route collocation method of multiple constraint energy communication service |
| CN105553843A (en) * | 2015-12-15 | 2016-05-04 | 国网冀北电力有限公司信息通信分公司 | Transmission line relay protection control service channel route configuration method and device |
| CN106209618A (en) * | 2016-07-27 | 2016-12-07 | 国网辽宁省电力有限公司 | A kind of communication mixed networking method and system improving intelligence adapted electric energy effect |
| CN106656598A (en) * | 2016-12-22 | 2017-05-10 | 云南电网有限责任公司 | Method and system for configuring alternative route of key service of electric power communication network |
| CN106656805A (en) * | 2017-02-17 | 2017-05-10 | 华北电力大学（保定） | Multiservice QoS route selection method of power wide-area communication network |
| CN110417664A (en) * | 2019-07-31 | 2019-11-05 | 国家电网有限公司信息通信分公司 | Business route distribution method and device based on power telecom network |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111083578A (en) | 2020-04-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101473605B (en) | Method for determining anticipation peer-to-peer collaborator of Internet service supplier | |
| Shakkottai et al. | The price of simplicity | |
| CN105335816A (en) | Electric power communication operation trend and business risk analyzing method based on deep learning | |
| CN113705959B (en) | Network resource allocation method and electronic equipment | |
| CN101572623A (en) | Method for comprehensively evaluating network performance based on subjective and objective combination evaluation | |
| CN110971525B (en) | Service routing and addressing method for service operation of power communication network | |
| Thanh et al. | An effective representation scheme in multifactorial evolutionary algorithm for solving cluster shortest-path tree problem | |
| CN111988796A (en) | Dual-mode communication-based platform area information acquisition service bandwidth optimization system and method | |
| CN103824127B (en) | Service self-adaptive combinatorial optimization method under cloud computing environment | |
| CN109919532A (en) | Logistics node determination method and device | |
| CN110084630A (en) | The user's tourism trip intention and type prediction method of decision tree are promoted based on gradient | |
| CN112819659A (en) | Tourist attraction development and evaluation method | |
| CN113316038B (en) | Optical access network ODN intelligent clustering planning method facing sparse user distribution | |
| CN111083578B (en) | Multi-objective optimization method for service classification light path roundabout route | |
| CN101026655A (en) | End-to-end business circuit resource intelligent query and identifying system for telecommunication field | |
| Hebal et al. | Aco-based distributed energy routing protocol in smart grid | |
| CN107248926B (en) | Multi-objective-oriented EPON planning method | |
| CN111083577A (en) | Power communication topological structure optimization method | |
| CN103051537B (en) | IP Circuit Service transmission dispatching method and system | |
| CN112488343B (en) | Smart city intelligent perception terminal address selection method based on hyper-heuristic algorithm | |
| CN101741749A (en) | Method for optimizing multi-object multicast routing based on immune clone | |
| CN107911763A (en) | A kind of intelligent adapted telecommunication net EPON network plan methods based on QoS | |
| CN103096380A (en) | Wireless access point load balancing load balancing | |
| CN109462861B (en) | Layered heterogeneous network access collaborative selection method for electric power wireless private network | |
| CN113315173B (en) | Distribution network planning method, equipment, system and storage medium based on big data analysis and supply and demand double-side collaborative optimization |
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 |