CN107332631A - A kind of method of use multi-attribute group decision making theoretical evaluation link-quality assessment models - Google Patents
A kind of method of use multi-attribute group decision making theoretical evaluation link-quality assessment models Download PDFInfo
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- CN107332631A CN107332631A CN201710644671.5A CN201710644671A CN107332631A CN 107332631 A CN107332631 A CN 107332631A CN 201710644671 A CN201710644671 A CN 201710644671A CN 107332631 A CN107332631 A CN 107332631A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
- H04B17/318—Received signal strength
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
- H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/391—Modelling the propagation channel
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
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- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
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Abstract
The invention discloses a kind of method of use multi-attribute group decision making theoretical evaluation link-quality assessment models.Using packet reception rate as the stability criterion of assessment models, signal to noise ratio builds the assessment indicator system of link-quality assessment models as the agility standard of assessment models.Under different Link States, assessment models are evaluated respectively, influence degree of each Link State to assessment models performance is calculated.Influence degree of each evaluation index to link-quality assessment models performance is assessed, the weight size of each index is calculated.The optimal selection problem of link-quality assessment models is converted into multi-attribute group decision making problem, multiple evaluation indexes are merged using plus-minus ideal solutions method, and the performance of link-quality assessment models is quantified and preferred.The present invention establishes the assessment indicator system of link-quality assessment models, is quantified using the theoretical performance to link-quality assessment models of multi-attribute group decision making, and assessment models are sorted preferably according to quantized result.
Description
Technical field
The present invention relates to wireless network links quality evaluation field, and in particular to one kind is commented using multi-attribute group decision making theory
The method of valency wireless sensor network link-quality assessment models.
Background technology
Wireless sensor network is constituted by being deployed in substantial amounts of inexpensive sensor node in monitor area, passes through channel radio
The ad hoc network system for the multi-hop that the mode of letter is formed.Have in fields such as environmental monitoring, smart home, Intelligent logistics
Wide application prospect.
Node in wireless sensor network is typically a micro embedded system for carrying perception, and it calculates energy
Power, storage capacity, communication capacity are weaker, and require with the working time as long as possible.Sensor node is general by wireless
Radio frequency is communicated, and residing environment is complicated and changeable and there is random interference signal, and causing the link between node to be can not
Lean on, packet loss phenomenon occurs in data transfer.Overlying roaduay is obtained by consultation according to by the calculating of link-quality assessment models
Link-quality select preferable link to carry out data transmission, different link-quality assessment models change to Link State
Stability it is different with agility, cause node to carry out the data packet retransmission and Route Selection of different number of times, node caused
Energy expenditure is also different.Using the method for evaluating performance of rational wireless sensor network link-quality assessment models, Ke Yixuan
Effective link-quality assessment models are selected, to obtaining reliable Link State, extends the service life of network, improves application system
Stability seem very necessary.
The content of the invention
To solve the problem of above-mentioned wireless sensor network link Evaluation Model on Quality is preferred, the invention provides one kind
Using the method for multi-attribute group decision making theoretical evaluation link-quality assessment models.Referred to using stability and agility as evaluation
Mark, the evaluation index of link Evaluation Model on Quality is merged using plus-minus ideal solutions method, and presses close to degree to comprehensive using ideal
Link-quality assessment models are ranked up.
The thinking of the present invention is, the requirement according to wireless sensor network to link-quality assessment models, by stability and
Agility changes as link-quality assessment models evaluation index, wherein stability reflection assessment models to Link State
Blunt type level, the promptness level that agility reflection assessment models change to Link State.Assessment models are used as using PRR
Stability criterion, using SNR as assessment models agility standard, calculate respectively in same period with the mean square deviation of assessment result
It is used as evaluation index value；Because the performance of the link-quality assessment models under different Link States has otherness, collect multiple
Link quality parameter under Link State, obtains the decision matrix under each state, and final determine is fused to by weighted sum method
Plan matrix；Interference in order to avoid subjective factor to evaluation result, using the weight of entropy assessment Calculation Estimation index, sets up cum rights
The decision matrix of weight, the information of multiple evaluation indexes is merged using the method for plus-minus ideal solutions, and to link-quality assessment models
It is ranked up preferably.
The object of the present invention is achieved like this.One kind assesses mould using multi-attribute group decision making theoretical evaluation link-quality
The method of type, it is characterised in that：The foundation of link-quality assessment models assessment indicator system, using entropy assessment and plus-minus ideal solutions
Method quantifies to comprehensive link-quality assessment models performance, and assessment models are sorted preferably according to quantized result, including
Following steps：
(1) foundation of link-quality assessment models assessment indicator system, is comprised the following steps that：
A aggregation nodes receive the packet that is sent by sending node, record the link-quality basic parameter that receives when
Between sequence data, including：Packet reception rate (PRR, Packet Reception Ratio), signal to noise ratio (SNR, Signal Noise
Ratio), link-quality indicate (LQI, Link Quality Indicator) and received signal strength indicator (RSSI,
Received Signal Strength Indicator), and be standardized；
B calculates the corresponding link-quality of each comprehensive link-quality assessment models, and is standardized；
C is usedCalculate and assess mould
The stability of type；Wherein：LQE is the link-quality after standardization, Di(PRR) be i-th of cycle PRR variances, Di
(LQE) be i-th of cycle LQE variances；
D is usedCalculate and assess mould
The agility of type；Wherein：LQE is the link-quality after standardization, Di(SNR) be i-th of cycle SNR variances, Di
(LQE) be i-th of cycle LQE variances；
F records the stability and agility of each assessment models under T Link State, and uses the method for weighted sum to multiple
Decision matrix under Link State is merged；
(2) weight of evaluation index is calculated using entropy assessment, comprised the following steps that：
Property value under same evaluation index is normalized a respectively, sets up standardization decision matrix D；
B according to standardization decision matrix, Calculation Estimation index j entropy,Wherein, m represents to be evaluated
The number of the link-quality assessment models of valency；K calculation is k=1/lnm；dijIt is that assessment models i returns to evaluation index j
Property value after one change；
C calculates the corresponding weight of each evaluation index according to the entropy of all evaluation indexes,N is represented
The number of evaluation index；
(3) performance of assessment models is ranked up preferably using plus-minus ideal solutions method, comprised the following steps that：
A utilizes the corresponding weights omega of each row for standardizing decision matrix DjIt is multiplied, obtains weighting standard decision-making
Matrix V；
B determines positive ideal solutionAnd minus ideal resultAnd calculate link-quality
Assessment models i evaluation vector and Euclid distance of the positive Negative ideal point in n-dimensional spaceWithN represents evaluation index
Number；
C calculates link-quality assessment models i and ideal solution relative proximity
To press close to degree relatively as according to preferred link Evaluation Model on Quality.
Step 1) in c) in, build estimation of stability index when, variance yields and assessment using PRR in N number of cycle
As a result the mean square deviation of variance yields.
Step 1) in d) in, build agility Indexes when, variance yields and assessment using SNR in N number of cycle
As a result the mean square deviation of variance yields.
Between 10 and 20, the data packet number in a cycle is controlled between 30-50 for N quantity control.
Step 1) in e) in, T quantity is controlled between 4-6.
It is an advantage of the invention that：The present invention establishes the assessment indicator system of link-quality assessment models, using many attributes
Group Decision Theory quantifies to the performance of link-quality assessment models, and assessment models are sorted preferably according to quantized result.
Brief description of the drawings
Fig. 1 and Fig. 2 is the variance comparison diagram of each link-quality assessment models and PRR under different transimission powers.
Fig. 3 and Fig. 4 is the variance comparison diagram of each link-quality assessment models and SNR under different distance.
Fig. 5 to Figure 10 is the Evaluated effect figure of each link quality parameter and link-quality assessment models to same link.
Embodiment
Hereinafter with reference to accompanying drawing, the preferred embodiment of the present invention is described in detail.
The link evaluation model that this preferred embodiment is chosen has Triangle assessment models, FLQE assessment models and FourBit
Three kinds of assessment models, are designated as A={ a1,a2,a3}.Using the evaluation index stability and agility of link-quality assessment models as
The property set of link-quality, is designated as C={ c1,c2}.Choose six Link States to evaluate link instructions assessment models, remember
For T={ t1,t2,t3,t4,t5,t6}。
1) foundation of link-quality assessment models assessment indicator system, is comprised the following steps that：
A) aggregation node receives the packet sent by sending node, and records the link-quality basic parameter received
Time series data, including PRR, SNR, LQI and RSSI, and be standardized；
B) chain under different distance is calculated respectively using tri- link-quality assessment models of FourBit, Triangle, FLQE
Road quality；
C) link-quality under each link-quality assessment models is standardized；
D) using packet reception rate PRR in 10 cycles variance yields and assessment result variance yields mean square deviation, as commenting
Estimate the stability indicator of model, the data packet number in each cycle is 30；
E) mean square deviation of the variance yields of signal to noise ratio snr and the variance yields of assessment result in 10 cycles is used, assessment is used as
The data packet number in agility index each cycle of model is 30；Obtain multi-attribute group decision making matrix as shown in table 1；
The multi-attribute group decision making matrix of table 1
F) consider that the probability that each Link State occurs in the scene is identical, each Link State is selected to assign
Identical weight, i.e. η (t1)=η (t2)=η (t3)=η (t4)=η (t5)=η (t6)=1/6；To be many by the method for weighted sum
Decision matrix under individual state is fused to multiple attribute decision making (MADM) matrix；
2) weight of evaluation index is calculated using entropy assessment, comprised the following steps that：
A) property value under all evaluation indexes is normalized respectively, sets up normalization decision matrix D；
B) obtained evaluation criterion weight is calculated using the entropy assessment in claims 1 is respectively：ω1=
0.454891919556 and ω2=0.54510808444；
3) combination property of assessment models is ranked up preferably using plus-minus ideal solutions method, comprised the following steps that：
A) the corresponding weights omega of each row for standardizing decision matrix D is utilizedjIt is multiplied, obtains weighting standard decision-making
Matrix V；
B) positive ideal solution V is determined+={ 0,0 }, minus ideal result V-={ 0.33639681881,0.34870997113 }, and count
Calculate the evaluation vector and Euclid distance of the positive Negative ideal point in two-dimensional space of each link-quality assessment models；
C) using the computational methods of relative proximity in claims 1, each link matter in this preferred embodiment is obtained
Amount assessment models it is corresponding it is relative press close to degree be：c(a1)=0.49945972776, c (a2)=0.361473599869, c
(a3)=0.292680026820.
Therefore link-quality assessment models by assessment performance it is good and bad from high to low for Triangle, FLQE,
FourBit, i.e. Triangle link-qualities assessment models are performance preferably assessment models relatively under the scene.
So link-quality assessment models evaluation method of the invention can utilize the stability of link-quality assessment models
Assessment indicator system is set up with agility, passes through the property of Multiple Attribute Group Decision comprehensively assessing link quality assessment models
Energy.
Claims (5)
1. a kind of method of use multi-attribute group decision making theoretical evaluation link-quality assessment models, it is characterised in that：Link-quality
The foundation of assessment models assessment indicator system, using entropy assessment and plus-minus ideal solutions method to comprehensive link-quality assessment models
It can be quantified, and assessment models are sorted preferably according to quantized result, be comprised the following steps：
1) foundation of link-quality assessment models assessment indicator system, is comprised the following steps that：
A) aggregation node receives the packet sent by sending node, records the time sequence of the link-quality basic parameter received
Column data, including：Packet reception rate PRR, signal to noise ratio snr, link-quality indicate LQI and received signal strength indicator RSSI, go forward side by side
Row standardization；
B) the corresponding link-quality of each comprehensive link-quality assessment models is calculated, and is standardized；
C) useCalculate assessment models
Stability；Wherein：LQE is the link-quality after standardization, Di(PRR) be i-th of cycle PRR variances, Di(LQE) it is
The LQE variances in i-th of cycle；
D) useCalculate assessment models
Agility；Wherein：LQE is the link-quality after standardization, Di(SNR) be i-th of cycle SNR variances, Di(LQE) it is
The LQE variances in i-th of cycle；
E) stability and agility of each assessment models under T Link State are recorded, and uses the method for weighted sum to multiple chains
Decision matrix under line state is merged；
2) weight of evaluation index is calculated using entropy assessment, comprised the following steps that：
A) property value under same evaluation index is normalized respectively, sets up standardization decision matrix D；
B) according to standardization decision matrix, Calculation Estimation index j entropy,Wherein, m represents to be evaluated
The number of link-quality assessment models；K calculation is k=1/lnm；dijIt is normalization of the assessment models i to evaluation index j
Property value afterwards；
C) according to the entropy of all evaluation indexes, the corresponding weight of each evaluation index is calculated,N represents to evaluate
The number of index；
3) performance of assessment models is ranked up preferably using plus-minus ideal solutions method, comprised the following steps that：
A) the corresponding weights omega of each row for standardizing decision matrix D is utilizedjIt is multiplied, obtains weighting standard decision matrix
V；
B) positive ideal solution is determinedAnd minus ideal resultAnd calculate link-quality and comment
Estimate model i evaluation vector and Euclid distance of the positive Negative ideal point in n-dimensional spaceWithN represents of evaluation index
Number；
C) link-quality assessment models i and ideal solution relative proximity are calculatedWith phase
It is according to preferred link Evaluation Model on Quality to pressing close to degree.
2. a kind of method of use multi-attribute group decision making theoretical evaluation link-quality assessment models according to claim 1,
It is characterized in that：Step 1) in c) in, build estimation of stability index when, using the variance yields of PRR in N number of cycle with commenting
Estimate the mean square deviation of the variance yields of result.
3. a kind of method of use multi-attribute group decision making theoretical evaluation link-quality assessment models according to claim 1,
It is characterized in that：Step 1) in d) in, build agility Indexes when, using the variance yields of SNR in N number of cycle with commenting
Estimate the mean square deviation of the variance yields of result.
4. according to claim 1, one kind described in 2,3 any one assesses mould using multi-attribute group decision making theoretical evaluation link-quality
The method of type, it is characterised in that：Between 10 and 20, the data packet number in a cycle is controlled in 30-50 for N quantity control
Between.
5. a kind of method of use multi-attribute group decision making theoretical evaluation link-quality assessment models according to claim 1,
It is characterized in that：Step 1) in e) in, T quantity is controlled between 4-6.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108966270A (en) * | 2018-07-19 | 2018-12-07 | 南昌航空大学 | Wireless sensor network link-quality-evaluating method |
| CN109672483A (en) * | 2018-11-15 | 2019-04-23 | 天津大学青岛海洋技术研究院 | A kind of chromatography type channel quality assessment method |
| CN110519787A (en) * | 2018-05-22 | 2019-11-29 | 中国移动通信有限公司研究院 | Determination method, terminal and the network side equipment of Radio Link monitoring and evaluation time delay |
| CN113037412A (en) * | 2021-02-26 | 2021-06-25 | 中国科学院微小卫星创新研究院 | Satellite data transmission link fault evaluation system |
| CN114726777A (en) * | 2022-03-14 | 2022-07-08 | 江苏大学 | SDN routing selection method based on TOPSIS decision |
| CN114996897A (en) * | 2022-04-06 | 2022-09-02 | 武昌首义学院 | Multi-attribute group decision method based on cloud model joint coefficient |
| CN115914080A (en) * | 2022-08-09 | 2023-04-04 | 中国移动粤港澳大湾区(广东)创新研究院有限公司 | Entropy weight method-based SRv6-TE calculation path optimization method and device |
| WO2024140149A1 (en) * | 2022-12-30 | 2024-07-04 | 汉熵通信有限公司 | Method and apparatus for intelligently switching and operating security system, and system and medium |
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110519787A (en) * | 2018-05-22 | 2019-11-29 | 中国移动通信有限公司研究院 | Determination method, terminal and the network side equipment of Radio Link monitoring and evaluation time delay |
| CN108966270A (en) * | 2018-07-19 | 2018-12-07 | 南昌航空大学 | Wireless sensor network link-quality-evaluating method |
| CN108966270B (en) * | 2018-07-19 | 2021-08-10 | 南昌航空大学 | Wireless sensor network link quality evaluation method |
| CN109672483A (en) * | 2018-11-15 | 2019-04-23 | 天津大学青岛海洋技术研究院 | A kind of chromatography type channel quality assessment method |
| CN113037412A (en) * | 2021-02-26 | 2021-06-25 | 中国科学院微小卫星创新研究院 | Satellite data transmission link fault evaluation system |
| CN114726777A (en) * | 2022-03-14 | 2022-07-08 | 江苏大学 | SDN routing selection method based on TOPSIS decision |
| CN114726777B (en) * | 2022-03-14 | 2024-08-09 | 江苏大学 | SDN route selection method based on TOPSIS decision |
| CN114996897A (en) * | 2022-04-06 | 2022-09-02 | 武昌首义学院 | Multi-attribute group decision method based on cloud model joint coefficient |
| CN114996897B (en) * | 2022-04-06 | 2023-03-07 | 武昌首义学院 | Multi-attribute group ship anti-settling capacity evaluation decision method based on cloud model joint coefficient |
| CN115914080A (en) * | 2022-08-09 | 2023-04-04 | 中国移动粤港澳大湾区(广东)创新研究院有限公司 | Entropy weight method-based SRv6-TE calculation path optimization method and device |
| WO2024140149A1 (en) * | 2022-12-30 | 2024-07-04 | 汉熵通信有限公司 | Method and apparatus for intelligently switching and operating security system, and system and medium |
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