CN1889776A - Vertical switching control system and method based on fuzzy logic - Google Patents
Vertical switching control system and method based on fuzzy logic Download PDFInfo
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Abstract
一种基于模糊逻辑的垂直切换决策控制系统及控制方法，包括：模糊化模块、模糊逻辑推理模块、解模糊模块、知识库和配置管理模块5个部分通过模糊决策算法对移动节点(MN)的网络链路质量、带宽、价格、电池电量、移动速度及用户偏好等多方面因素进行综合的评价，选择出最优的网络进行切换。本发明所提供的方法解决了具备多种网络接入技术的移动设备在异构重叠覆盖的网络环境中垂直切换过程中最优网络的选择决策问题。
A fuzzy logic-based vertical handover decision-making control system and control method, including: a fuzzy module, a fuzzy logic reasoning module, a defuzzification module, a knowledge base and a configuration management module Comprehensive evaluation of network link quality, bandwidth, price, battery power, mobile speed and user preference, etc., to select the optimal network for switching. The method provided by the invention solves the optimal network selection and decision-making problem in the vertical switching process of mobile equipment with multiple network access technologies in a network environment with heterogeneous overlapping coverage.
Description
Technical field
The invention belongs to mobile IP field, specifically, be vertical handover decisions control system and the control method that has proposed based on fuzzy logic, many-sided factors such as network link quality, bandwidth, price, battery electric quantity, translational speed and user preference to mobile node MN are carried out comprehensive evaluation, select the optimum network that is fit to use and switch.
Background technology
Wireless, the mobile network is ubiquitous, for the user provide everywhere can and communication service.Existing wireless, mobile network is at coverage, access capability, address realm, there are differences the aspects such as support that move, provide for the user enrich the access means in, increased the isomerism of network.The mobile device of multiple network interface extensively exists, and the user can select to insert the network of " interested ".How being to use the bearer network of dynamically selecting " optimum ", is terminal use's service better, becomes the problem that is worth our concern.
The mobile IP v 6 technology can guarantee that mobile device can leave local network and still can keep in touch with the Internet pellucidly in mobile computing, just can continue communication without any network information of manual configuration, and can keep ongoing network connection not to be interrupted.Under the complex situations of the overlapping covering of multiple network, one of key issue that the continuation that decision problem in vertical the switching has just become solves.Traditional handover decisions all is to carry out handover decisions as with reference to standard yet the vertical switching between heterogeneous network will rely on more standard so that the AP signal is strong and weak, will make handover decisions become complicated more like this, also is difficult to carry out mathematical modeling.
The thought of fuzzy logic control method is the method for coming the system that can't set up Mathematical Modeling is realized control with the logical thinking of fuzzy logic apery, and, time non-linear in the real world for handling becomes and the system that can't define provides the mathematical framework of a robust.Vertical handover decisions will be applied to based on the control algolithm of fuzzy logic and handover decisions problem under many network coverages environment can be solved well.
Summary of the invention
The objective of the invention is to propose a kind of vertical handover decisions control system and control method based on fuzzy logic, many-sided factors such as network link quality, bandwidth, price, battery electric quantity, translational speed and user preference to MN are carried out comprehensive evaluation, select the optimum network that is fit to use and switch.
Technical solution of the present invention: a kind of vertical handover decisions control system based on fuzzy logic, its characteristics are to comprise: obfuscation module, fuzzy logic inference module, ambiguity solution module, knowledge base and 5 parts of Configuration Manager, the function of wherein obfuscation module is to measure the ratio mapping of input variable value (signal strength signal intensity, bandwidth, price, movement velocity, battery electric quantity etc.) to corresponding domain conversion, realize obfuscation, change input data dress the item of corresponding language variable into, and constitute fuzzy set; The fuzzy logic inference module is carried out comprehensive assessment according to the vertical switching fuzzy control rule in the knowledge base to the fuzzy set of input, to obtain an amount of using the language representation qualitatively, this result is certain output area of determining, promptly fuzzy output variable, obviously fuzzy output variable can not directly be done the control execution unit, in this output area of determining, must determine that also one artificially has most the value of role of delegate as real output controlled quentity controlled variable; The defuzzification module is exactly that fuzzy output variable is converted into real handover decisions result, and finishes handoff procedure to the switching executing module that the switching controls module sends to mobile IP v 6; The knowledge base of fuzzy logic algorithm, comprise the knowledge of application and the knowledge of corresponding controlled target, rule base is the control strategy that comes characterization control target and this domain expert by a series of language control laws, it is write as according to the behavioral trait of controlled system and expert's control experience, and database is to be used in the ambiguity in definition logic membership function of parameter to conciliate fuzzy algorithmic approach; Configuration Manager is responsible for renewal, the renewal of membership function and the control of algorithm state of rule in the whole decision making algorithm.
Vertical handover decisions control method based on fuzzy logic of the present invention, be by on the basis of structure based on the handover decisions Fuzzy control system of fuzzy logic algorithm on the MN, this system can carry out comprehensive evaluation for network quality according to the run time behaviour information of MN, instruct MN to switch in the optimum network, specifically comprise the steps:
(1) the state monitoring module monitoring network of MN and the real-time status of system, and trigger vertical handover procedure according to the change of state;
Whether (2) the handover decisions process at first detects user-defined mandatory rule, if there is the network of this rule-like and user's appointment to use, then directly switches according to user's rule, otherwise enters handover decisions process based on fuzzy logic;
(3) the system performance parameter measured value that will gather in real time of the state monitoring module of MN (factors such as, price slight, bandwidth) input obfuscation module as network signal, the accurate amount that the obfuscation device will be imported is converted into the value of the fuzzy variable of representing with membership function, and formation can be used for the fuzzy set that fuzzy control rule carries out reasoning;
(4) the fuzzy logic inference module is carried out comprehensive assessment according to the vertical switching fuzzy control rule in the knowledge base to the fuzzy set of input, and to obtain an amount of using the language representation qualitatively, this result is certain output area of determining, promptly fuzzy output variable;
(5) the defuzzification module is that fuzzy output variable is converted into real handover decisions result, and finishes handoff procedure to the switching executing module transmission switching command of mobile IP v 6;
(6) user can finish adjustment and the control of user to algorithm by the Policy Updates in the Configuration Manager, membership function renewal and real-time condition monitoring.
The present invention's advantage compared with prior art is: the present invention utilize fuzzy logic theory to attach most importance to the selection problem of optimal network has made up specific Fuzzy control system in the multi-mode networks environment of superimposition lid, coarse actual influence factors such as signal strength signal intensity, bandwidth are carried out the modeling assessment, solved the vertical handover decision algorithm problem of mobile device.
Description of drawings
Fig. 1 scene description figure that the sagging vertical cut of multi-mode networks environment of superimposition lid changes that attaches most importance to;
Fig. 2 is the structure chart that the present invention is based on the vertical handover control system of fuzzy logic;
Fig. 3 is the flow chart that the present invention is based on the vertical-switching control method of fuzzy logic;
Fig. 4 is the membership function figure of factor of influence of the present invention.
Embodiment
As shown in Figure 1, the scene description figure that the sagging vertical cut of multi-mode networks environment of the superimposition of attaching most importance to lid changes, MN is the mobile device that possesses multiple standard network interface, comprising 802.3,802.11, network formats such as GPRS, CDMA1X, 3G.MN finishes and selects optimum access network to switch in the multi-mode networks environment of overlapping covering in the process that moves.The present invention is applicable to the mobile node with multi-mode networks interface, and network interface is numbered 1-n, wherein network formats comprise 802.3,802.11, GPRS, CDMA1X, 3G etc.
As shown in Figure 2, vertical handover decisions control system based on fuzzy logic of the present invention comprises 5 elements: the obfuscation module, the fuzzy logic inference module, the ambiguity solution module, knowledge base and Configuration Manager, the function of wherein obfuscation module is to finish the value of test input variable (as signal strength signal intensity, bandwidth, price, movement velocity etc.), and the input variable of numeral form is converted into the common a certain ordinal number that limits sign indicating number with the language value representation, i.e. fuzzy set, the fuzzy subset that each limits in the representation domain is defined by its membership function.
The fuzzy logic inference module is carried out comprehensive assessment according to the vertical switching fuzzy control rule in the knowledge base to the fuzzy set of input, and to obtain an amount of using the language representation qualitatively, this result is certain output area of determining, promptly fuzzy output variable.
Obviously fuzzy output variable can not directly be done the control execution unit, in this output area of determining, must determine that also one artificially has most the value of role of delegate as real output controlled quentity controlled variable, the defuzzification module is exactly that fuzzy output variable is converted into real handover decisions result, and finishes handoff procedure to the switching executing module that the switching controls module sends to mobile IP v 6.
The knowledge base of fuzzy logic algorithm comprises the knowledge of application and the knowledge of corresponding controlled target.Rule base is the control strategy that comes characterization control target and this domain expert by a series of language control laws, and it is write as according to the behavioral trait of controlled system and expert's control experience, adopts the rule format of " IF...THEN... " usually; And database mainly comprises selection, quantification manner, scale factor and the fuzzy subset's of quantification gradation membership function, and these notions all are to be based upon on experience and the engineering judgement basis, and definition has subjectivity.
Configuration Manager is responsible for renewal, the renewal of membership function and the control of algorithm state of rule in the whole decision making algorithm.
As shown in Figure 3, the vertical handover decisions control method based on fuzzy logic of the present invention specifically comprises the steps:
(1) the state monitoring module monitoring network of MN and the real-time status of system, real-time status parameters such as bandwidth, signal strength signal intensity, system battery electric weight and mobile node movement velocity as each access network, and when relevant parameter changes, trigger vertical handover procedure, as the rapid situation such as decay or battery electric quantity deficiency of the signal of finding new access network, current use network;
Whether (2) the handover decisions process at first detects user-defined mandatory rule, if there is the network of this rule-like and user's appointment to use, then directly switches according to user's rule, otherwise enters handover decisions process based on fuzzy logic;
(3) the system performance parameter measured value that will gather in real time of the state monitoring module of MN (factors such as, price slight, bandwidth) input obfuscation module as network signal, the accurate measured value that the obfuscation device will be imported is done standardization, promptly its excursion is mapped in the corresponding domain by corresponding membership function, again this input data transaction in this domain is become the term of corresponding linguistic variable, and formation can be used for the fuzzy set that fuzzy control rule carries out reasoning.Such as signal strength signal intensity may corresponding " height " and " in " two kinds limit sign indicating number different degrees of membership arranged, and these the two groups set that limit sign indicating number and corresponding degree of membership formation are exactly the fuzzy set that obtains;
(4) the fuzzy logic inference module is carried out computing according to the vertical switching fuzzy control rule in the knowledge base to the fuzzy set substitution control law of importing, what the present invention adopted is the Mamdani rationalistic method, to obtain an amount of using the language representation qualitatively, this result is certain output area of determining, promptly fuzzy output variable, this fuzzy output variable is not an accurate value, but "Yes", "No", " may be ", " can " corresponding possibility numerical value;
(5) the defuzzification module is to utilize the ambiguity solution function to be converted into real handover decisions result fuzzy output variable, and this result is an accurate numerical value.The algorithm of ambiguity solution is a lot, and what this patent adopted is weighted mean method.Each network will calculate an accurate numerical value, just can determine that by the final result that compares different access networks which network is optimum network, sends switching command to switching executing module afterwards and finishes handoff procedure;
(6) user can finish adjustment and the control of user to algorithm by Policy Updates, membership function renewal and real-time condition monitoring.
Figure 4 shows that the membership function (unlisted saturation model is basic identical) of the factor of influence that part is relevant with service quality.With the signal strength signal intensity is example, different with traditional Mathematical Modeling, and when measured signal strengths r was between R1 and R2, the functional value that obtains not was unique, and the degree of membership of corresponding low signal is 0.25 and the degree of membership of corresponding msp signal intensity is 0.75.By the coupling of membership function, all decision-making factors will be converted into a fuzzy set, use for the fuzzy logic inference module.For example, if mobile node is chosen listed 4 the factor of influence signal strength signal intensities (R) of Fig. 4, bandwidth (B), movement velocity (V), battery electric quantity (E), accurate measured value (r, v, b, e) for every group of input, the value of every kind of factor be divided into 3 grade height (H), in (M), low (L), will obtain similar following fuzzy set by the obfuscation module after fuzzy
Signal strength signal intensity (=r): (L, 0.25) (M, 0.75);
Movement velocity (=v): (M, 0.25) (H, 0.75);
Bandwidth (=b): (L, 0.7) (M, 0.3);
Battery electric quantity (=e): (M, 0.2) (H, 0.8);
The fuzzy logic inference module is based on that the rule of series of rules IF-THEN pattern constitutes, and the conclusion of decision-making is divided into 4 classes, promptly be (Y), not (N), may be (PY), can (PN).The rule of decision-making can have 34=81 bar rule at most, and the 81st, Gui Ze maximum in this case, but can not define 81 rules in the reality usually.Following example is listed several rules:
IF?R＝H?and?B＝H?and?V＝L?and?E＝H?THEN?Handover＝Y；
IF?R＝L?and?B＝L?and?V＝H?and?E＝L?THEN?Handover＝N；
IF?R＝H?and?B＝H?and?V＝H?and?E＝H?THEN?Handover＝PY；
…
Fuzzy inference engine will utilize Mamdani minimax rationalistic method, carry out computing according to the regular matrix of definition and the fuzzy set of input, and system will obtain one group of fuzzy decision output F, and for example (Y=0.3, PY=0.35, PN=0.2, N=0.25).
These group data will be imported the defuzzification module, obtain the final decision-making numerical value (FHD) between 0-1.The method of defuzzification can have a variety of, and the formula of the defuzzification that this patent adopts is:
Wherein Wi is the weighted value set of F, and as (1.0,0.8,0.5,0.2), value is according to user's setting.
The FHD that compares the heterogeneous networks interface is with regard to the passable network interface to optimum, and the transmission instruction, makes MN switch to the interface of optimum, thereby realizes the selection of optimal network.
What may be obvious that for the person of ordinary skill of the art draws other advantages and modification.Therefore, the present invention with wider aspect is not limited to shown and described specifying and exemplary embodiment here.Therefore, under situation about not breaking away from, can make various modifications to it by the spirit and scope of claim and the defined general inventive concept of equivalents thereof subsequently.
Claims (7)
1, a kind of vertical handover decisions control system based on fuzzy logic, it is characterized in that comprising: obfuscation module, fuzzy logic inference module, ambiguity solution module, knowledge base and 5 parts of Configuration Manager, the function of wherein obfuscation module is to measure the ratio mapping of input variable value to corresponding domain conversion, realize obfuscation, change input data dress the item of corresponding language variable into, and constitute fuzzy set; The fuzzy logic inference module is carried out comprehensive assessment according to the vertical switching fuzzy control rule in the knowledge base to the fuzzy set of input, and to obtain an amount of using the language representation qualitatively, this result is certain output area of determining, promptly fuzzy output variable; The defuzzification module is exactly that fuzzy output variable is converted into real handover decisions result, and finishes handoff procedure to the switching executing module that the switching controls module sends to mobile IP v 6; The knowledge base of fuzzy logic algorithm comprises the knowledge of application and the knowledge of corresponding controlled target; Configuration Manager is responsible for renewal, the renewal of membership function and the control of algorithm state of rule in the whole decision making algorithm.
2, the vertical handover decisions control system based on fuzzy logic according to claim 1, it is characterized in that: described obfuscation module is mainly finished the value of test input variable, and the input variable of numeral form is converted into the common a certain ordinal number that limits sign indicating number with the language value representation, i.e. fuzzy set, the fuzzy subset that each limits in the representation domain is defined by its membership function.
3, the vertical handover decisions control system based on fuzzy logic according to claim 1, it is characterized in that: described fuzzy logic inference module is to utilize the information simulation mankind's of knowledge base reasoning decision process, provides suitable controlled quentity controlled variable.
4, the vertical handover decisions control system based on fuzzy logic according to claim 1, it is characterized in that: described ambiguity solution module is to get the best process of representing the exact value of this fuzzy reasoning the possibility of result of an energy in the fuzzy set that will obtain in reasoning, and what method the present invention of accurate Calculation adopted is weighted-average method.
5, the vertical handover decisions control system based on fuzzy logic according to claim 1, it is characterized in that: described knowledge base comprises rule base and database, wherein rule base is the control strategy that characterizes target and this domain expert by a series of language control laws, and it is write as according to the behavioural characteristic of controlled system and expert's control experience; Database is used for the ambiguity in definition data manipulation.
6, the vertical handover decisions control system based on fuzzy logic according to claim 1, it is characterized in that: described Configuration Manager comprises that Policy Updates, membership function upgrade and the state of a control display module, and wherein the Policy Updates module is responsible for the control law in the update rule storehouse; The membership function of fuzzy data in the responsible more new database of membership function update module; The state of a control display module is responsible for showing current state of a control.
7, a kind of vertical handover decisions control method based on fuzzy logic is characterized in that realizing as follows:
(1) the state monitoring module monitoring network of MN and the real-time status of system, and trigger vertical handover procedure according to the change of state;
Whether (2) the handover decisions process at first detects user-defined mandatory rule, if there is the network of this rule-like and user's appointment to use, then directly switches according to user's rule, otherwise enters handover decisions process based on fuzzy logic;
(3) the system performance parameter measured value input obfuscation module that will gather in real time of the state monitoring module of MN, the accurate amount that the obfuscation device will be imported is converted into the value of the fuzzy variable of representing with membership function, and formation can be used for the fuzzy set that fuzzy control rule carries out reasoning;
(4) the fuzzy logic inference module is carried out comprehensive assessment according to the vertical switching fuzzy control rule in the knowledge base to the fuzzy set of input, and to obtain an amount of using the language representation qualitatively, this result is certain output area of determining, promptly fuzzy output variable;
(5) the defuzzification module is that fuzzy output variable is converted into real handover decisions result, and finishes handoff procedure to the switching executing module that the switching controls module sends to mobile IP v 6;
(6) user can finish adjustment and the control of user to algorithm by Policy Updates, membership function renewal and real-time condition monitoring.
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| CN101442835B (en) * | 2008-12-19 | 2010-06-09 | 无锡矽鼎科技有限公司 | Method for optimizing mobile internet terminal based on fuzzy controller |
| CN101998381A (en) * | 2009-08-13 | 2011-03-30 | 香港理工大学 | A fingerprint-type intelligent handover decision method and system based on fuzzy logic |
| CN102045720A (en) * | 2010-12-28 | 2011-05-04 | 北京交通大学 | Fuzzy rule-based wireless local area network switching method |
| CN102802223A (en) * | 2012-08-10 | 2012-11-28 | 迈普通信技术股份有限公司 | Vertical switching method of wireless heterogeneous networks and user terminal |
| CN104113887A (en) * | 2013-04-18 | 2014-10-22 | 南京邮电大学 | Vertical switching method in heterogeneous network environment |
| CN104125112A (en) * | 2014-07-29 | 2014-10-29 | 西安交通大学 | Physical-information fuzzy inference based smart power grid attack detection method |
| WO2016037321A1 (en) * | 2014-09-09 | 2016-03-17 | 重庆邮电大学 | Vertical switching method in 5g/wlan network based on fuzzy logic control |
| CN105873153A (en) * | 2016-06-02 | 2016-08-17 | 重庆邮电大学 | Stream switching method based on fuzzy logic in heterogeneous network |
| CN108388121A (en) * | 2018-03-06 | 2018-08-10 | 辽宁天安科技有限公司 | A kind of fuzzy logic control methodology of mechanical movable-sieve jig |
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| CN101998381B (en) * | 2009-08-13 | 2013-05-15 | 香港理工大学 | Fingerprint type intelligent switching judgment method and system based on fuzzy logic |
| CN101998381A (en) * | 2009-08-13 | 2011-03-30 | 香港理工大学 | A fingerprint-type intelligent handover decision method and system based on fuzzy logic |
| CN102045720B (en) * | 2010-12-28 | 2015-04-15 | 北京交通大学 | Fuzzy rule-based wireless local area network switching method |
| US8855085B2 (en) | 2010-12-28 | 2014-10-07 | Beijing Jiaotong University | Wireless local area network handover method based on fuzzy rules |
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| CN102802223A (en) * | 2012-08-10 | 2012-11-28 | 迈普通信技术股份有限公司 | Vertical switching method of wireless heterogeneous networks and user terminal |
| CN104113887A (en) * | 2013-04-18 | 2014-10-22 | 南京邮电大学 | Vertical switching method in heterogeneous network environment |
| CN104125112B (en) * | 2014-07-29 | 2017-04-19 | 西安交通大学 | Physical-information fuzzy inference based smart power grid attack detection method |
| CN104125112A (en) * | 2014-07-29 | 2014-10-29 | 西安交通大学 | Physical-information fuzzy inference based smart power grid attack detection method |
| WO2016037321A1 (en) * | 2014-09-09 | 2016-03-17 | 重庆邮电大学 | Vertical switching method in 5g/wlan network based on fuzzy logic control |
| CN105873153A (en) * | 2016-06-02 | 2016-08-17 | 重庆邮电大学 | Stream switching method based on fuzzy logic in heterogeneous network |
| CN105873153B (en) * | 2016-06-02 | 2019-07-16 | 重庆邮电大学 | Stream switching method based on fuzzy logic in a kind of heterogeneous network |
| CN108388121A (en) * | 2018-03-06 | 2018-08-10 | 辽宁天安科技有限公司 | A kind of fuzzy logic control methodology of mechanical movable-sieve jig |
| CN108388121B (en) * | 2018-03-06 | 2020-11-10 | 辽宁天安科技有限公司 | Fuzzy logic control method of mechanical movable sieve jig |
| CN109286958A (en) * | 2018-10-30 | 2019-01-29 | 西安交通大学 | A wireless network handover management method and system |
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| CN110868740A (en) * | 2019-11-12 | 2020-03-06 | 普联技术有限公司 | Roaming switching control method and device and electronic equipment |
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