CN107809764A - A kind of multiple affair detection method based on Markov chain - Google Patents
A kind of multiple affair detection method based on Markov chain Download PDFInfo
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- CN107809764A CN107809764A CN201710860491.0A CN201710860491A CN107809764A CN 107809764 A CN107809764 A CN 107809764A CN 201710860491 A CN201710860491 A CN 201710860491A CN 107809764 A CN107809764 A CN 107809764A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0209—Power saving arrangements in terminal devices
- H04W52/0225—Power saving arrangements in terminal devices using monitoring of external events, e.g. the presence of a signal
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0209—Power saving arrangements in terminal devices
- H04W52/0225—Power saving arrangements in terminal devices using monitoring of external events, e.g. the presence of a signal
- H04W52/0248—Power saving arrangements in terminal devices using monitoring of external events, e.g. the presence of a signal dependent on the time of the day, e.g. according to expected transmission activity
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The present invention relates to wireless sensor network technology field, discloses a kind of multiple affair detection method based on Markov chain, comprises the following steps：(1) parameter in wireless sensor network is obtained；(2) calculating single event recurs the expectation with the continuous time slot length not occurred respectively；It is determined that the energy consumed in the length expectation of each renewal process and each renewal process；Averagely detect that an event consumes electricity and it is expected to obtain the dormancy period of sensor every time by calculating；(3) exploration policy obtained according to step (2), calculate the event that whole system detects and quantity and the number occurred within total time occurs；Finally draw the detection efficient of whole system, the optimization of complete paired systems detection efficient.The present invention ensures that efficient scheduling sensor with the detectivity of multiple affair in raising system, reaches the purpose for reducing sensor and energy expenditure as far as possible in wireless sensor network using method of Lagrange multipliers.
Description
Technical field
The present invention relates to wireless sensor network technology field, is visited more particularly to a kind of multiple affair based on Markov chain
Survey method.
Background technology
Wireless sensor network (WSN) is a kind of emerging concept and technology for having started new opplication field.In the world today,
Sensor technology and sensor network are considered as a very promising research.In order to ensure the accuracy of whole network, just
It is required that the steady running of WSN node.The wireless sensing module research of wherein low-power consumption has very important study and research
Value, the realization of its function have extremely important theoretical and realistic meaning.
WSN main applications are exactly to be used for detecting event, it is assumed that the probability of happening of event obeys Markov chain, due to event
The randomness of generation, very big difficulty will be had by carrying out detecting event using the sensor network of energy constraint, therefore we should examine
Consider the energy level and dynamic event of sensor.The main test problems for paying attention to single event of most research in the past, are related to
Situation to multisensor and multiple affair is seldom.In the present invention, groundwork is examined in non-rechargeabel sensor network
Multiple case points interested are surveyed, target is to improve event detection rate to greatest extent.Due to the influence of geographical environment, each sensing
The investigative range of device is different, and some points interested are in the detection range of multiple sensors, and other are by one
Individual single sensor covering.Therefore, various sensors should coordinate their work, optimize the energy ratio of each point of interest
Example, and the efficiency of network is improved to greatest extent.In order to detect more events and save the energy, sensor as far as possible
A kind of dispatching method can be typically followed, is changed mutually between state of activation and resting state.Therefore one kind is needed in sensor
In the case of energy constraint, the method for the multiple affair detection based on Markov chain.
The content of the invention
The present invention is directed to deficiency of the prior art, there is provided a kind of multiple affair detection method based on Markov chain, this hair
Bright method considers the multiple affair detection problem based on Markov chain in wireless sensor network, it is ensured that in wireless senser
Efficient scheduling sensor is reached with the detectivity of multiple affair in raising system and is reduced sensor and energy as far as possible in network
The purpose of consumption, complete the multiple affair detection in wireless sensor network.
In order to solve the above-mentioned technical problem, the present invention is addressed by following technical proposals.
A kind of multiple affair detection method based on Markov chain, comprises the following steps：
(1) systematic parameter in wireless sensor network is obtained, including：Sensor SiBattery capacity B；Event IjOccur general
Rate Pj；Event IjOccur to continue probability of happening a to t+1 time slots from t time slots1, do not occur to continue not occur to t+1 time slots from t time slots
Probability a2；OrderWith
Work as Sensor Events I when being illustrated respectively in j time slotkFrom generation to the possibility for not occurring and never occurring to generation；
In time T, all sensors are to IkThe energy consumed is
(2) according to formulaBy a1And a2Substitute into and calculate single event company respectively
Expectation E [the X of the time slot length of supervention life1] and the continuous time slot length not occurred expectation E [X2]；According to formulaIt is determined that the length of renewal process it is expected T every timee；According to formula
It is determined that each TeThe energy consumedAccording to formulaCalculate and detect an event consumption electricity every time
Amount it is expected ak；Finally makeThe dormancy period SI of sensor is drawn, whereinRepresent T
The probability of stability that event occurs during → ∞；
(3) exploration policy is obtained according to step (2), the I that whole system detects can be calculatedkGeneration quantityIkThe number occurred within total time TFinally draw the detection efficient of whole systemFinally, the complete paired systems detection efficient U of method of Lagrange multipliers optimization is utilized.
Preferably, in step (1), event IjThe probability of generation obeys Markov Chain, and a1＞ 0.5, a2＞ 0.5.
Preferably, in step (2), Te=t2-t1, wherein t1And t2Represent that adjacent sensor twice enters resting state
Time slot.
Preferably, in step (3), exploration policy includes：(1) if occurring in sensor run time events I, sensor
The event is detected；(2) if event I does not occur in previous time slot, then the sensor in running status, which enters, stops
Dormancy state；(3) whether the SI automatic runnings detecting at regular intervals of the sensor in dormancy event I occurs.
The present invention has significant technique effect as a result of above technical scheme：
The inventive method obtains the parameter in wireless sensor network first；Then respectively calculate single event recur and
The expectation of the continuous time slot length not occurred；Then determine that the length of each renewal process it is expected and each updated respectively
The energy consumed in journey；It is all by calculating the average dormancy for detecting that an event consumption electricity it is expected to obtain sensor every time
Phase；According to obtained exploration policy, time that the event that whole system detects occurs quantity and occurred within total time is calculated
Number；Finally draw the detection efficient of whole system, the optimization of complete paired systems detection efficient.The present invention utilizes Lagrange multiplier
Method ensures that efficient scheduling sensor with the detectivity of multiple affair in raising system, reaches and to the greatest extent may be used in wireless sensor network
The purpose of sensor and energy expenditure can be reduced.
Brief description of the drawings
Fig. 1 is that sensor network system model is illustrated in a kind of multiple affair detection method based on Markov chain of the present invention
Figure；
Fig. 2 is workflow schematic diagram in a kind of multiple affair detection method based on Markov chain of the present invention；
Fig. 3 is system simulation model figure in a kind of multiple affair detection method based on Markov chain of the present invention；
Fig. 4 is a typical update cycle signal in a kind of multiple affair detection method based on Markov chain of the present invention
Figure；
Fig. 5 is each event occurrence rate explanation figure in a kind of multiple affair detection method based on Markov chain of the present invention；
Fig. 6 is that the detectivity of each event before optimizing in a kind of multiple affair detection method based on Markov chain of the present invention is said
Bright figure；
Fig. 7 is the energy that sensor in performance methodology is estimated in a kind of multiple affair detection method based on Markov chain of the present invention
Amount distribution explanation figure；
Fig. 8 is that the detectivity of each event after optimizing in a kind of multiple affair detection method based on Markov chain of the present invention is said
Bright figure.
Embodiment
The present invention is described in further detail with embodiment below in conjunction with the accompanying drawings.
Embodiment 1
As shown in Figures 1 to 8, a kind of multiple affair detection method based on Markov chain, comprises the following steps：
(1) parameter in wireless sensor network is obtained：Sensor SiBattery capacity B；Event IjThe probability P of generationj；
Event IjOccur to t+1 time slots to continue the probability a of generation from t time slots1；Event IjDo not occur to t+1 time slots to continue not from t time slots
The probability a of generation2；
(2) calculating single event recurs the expectation E [X with the continuous time slot length not occurred respectively1] and E [X2]；
It is determined that the length of renewal process it is expected T every timee；Each TeThe energy consumed isCalculate and averagely detect a thing every time
Part consumption electricity it is expected ak；Finally draw the dormancy period SI of sensor；
(3) exploration policy obtained according to step (2), the I that whole system detects is calculatedkGeneration quantity Sd；IkTotal
The number S occurred in time T0；Finally draw the detection efficient of whole systemCompleted using method of Lagrange multipliers
Optimization to system detection efficient U.
Detecting event requires the expenditure of energy, and has Bij={ b sensor i → event j }.Understand to sense according to step (2)
The actual electricity for often detecting the every time slot consumption of an event is a when device worksk, so in whole region, whole sensor network
Network can calculate for the detection efficient of event, to event IkStudied：
In time T, all sensors are to IkThe energy consumed is
Event IkThe probability of generation is
The I that whole system detectskGeneration quantity is：
IkThe number occurred within total time T is：
πonThe probability of stability occurred for T → ∞ events；
For event IkThe detection efficient of system is：
The detection efficient of whole system is：
The present invention needs to optimize whole system, and target is to obtain U maximum.
Fig. 1 represents sensor network system model.As illustrated, there is the region of 6 sensors and 12 case points.Event
I1S can be passed through1, S2And S4Detection.That isSo S1, S2And S4It should coordinate to match somebody with somebody
Close.Our target is that the energy of all the sensors can play a role to greatest extent.
Fig. 2 gives workflow schematic diagram in the multiple affair detection method based on Markov chain.Specifically, can describe
It is as follows：
A kind of multiple affair detection method based on Markov chain, this method comprise the following steps：
(1) parameter in wireless sensor network is obtained：Sensor SiBattery capacity B；Event IjThe probability P of generationj；
Event IjOccur to t+1 time slots to continue the probability a of generation from t time slots1；Event IjDo not occur to t+1 time slots to continue not from t time slots
The probability a of generation2；
(2) calculating single event recurs the expectation E [X with the continuous time slot length not occurred respectively1] and E [X2]；
It is determined that the length of renewal process it is expected T every timee；Each TeThe energy consumed isCalculate and averagely detect a thing every time
Part consumption electricity it is expected ak；Finally draw the dormancy period SI of sensor；
(3) exploration policy obtained according to step (2), the I that whole system detects is calculatedkGeneration quantity Sd；IkTotal
The number S occurred in time T0；Finally draw the detection efficient of whole systemCompleted using method of Lagrange multipliers
Optimization to system detection efficient U.
The system detection efficient U obtained in step (3) can ensure that efficient scheduling senses in wireless sensor network
The detectivity of multiple affair in device and raising system, reach the purpose for reducing sensor and energy expenditure as far as possible.
Technical scheme is further elaborated below by instantiation.In experiment, it is assumed that
Specifically, using following experiment parameter：
Total time T=10000slot, battery capacity B=10000 are wherein set, sensor consumes energy b=2/ when running
slot.The probability of happening of 4 events is respectively：
By method of Lagrange multipliers：
It can solve：a1=2.25, a2=2.30, a3=2.30, a4=3.20
Markov chain event occur the probability of stability beIt can solve：Maximum probe rate can be obtained by above-mentioned each formula.
Fig. 3 gives system simulation model figure in the multiple affair detection method based on Markov chain.
Fig. 4 gives typical a update cycle schematic diagram, wherein A in the multiple affair detection method based on Markov chain
Sensor operation is represented, I represents sensor dormancy, and Y represents event, and N represents that event does not occur, t1, t2Expression event is from hair
Nonevent time slot, t are arrived in life1~t2Illustrate a typical update cycle.
Fig. 5,6,7,8 are the simulation results figure to designed method by Matlab systems.
Fig. 5 gives 4 probability of happening and obeys markovian event stable state probability of happening figure, wherein visible event 1
Probability of happening highest, therefore for lifting system detectivity, more energy is carried out to the detection of event 1.The generation of event 4
Probability is minimum, therefore less energy is carried out to the detection of event 4.
Fig. 6 gives and gives carry out system optimization to the detectivity figure of each event, Fig. 7 before system optimization, to sensing
The energy of device redistribute figure, and Fig. 8 is given after system optimization to the detectivity figure of each event.
The inventive method obtains the parameter in wireless sensor network first；Then respectively calculate single event recur and
The expectation of the continuous time slot length not occurred；Then determine that the length of each renewal process it is expected and each updated respectively
The energy consumed in journey；It is all by calculating the average dormancy for detecting that an event consumption electricity it is expected to obtain sensor every time
Phase；According to obtained exploration policy, time that the event that whole system detects occurs quantity and occurred within total time is calculated
Number；Finally draw the detection efficient of whole system, the optimization of complete paired systems detection efficient.The present invention utilizes Lagrange multiplier
Method ensures that efficient scheduling sensor with the detectivity of multiple affair in raising system, reaches and to the greatest extent may be used in wireless sensor network
The purpose of sensor and energy expenditure can be reduced.
In a word, presently preferred embodiments of the present invention, all equalizations made according to scope of the present invention patent be the foregoing is only
Change and modification, it should all belong to the covering scope of patent of the present invention.
Claims (4)
1. a kind of multiple affair detection method based on Markov chain, it is characterised in that comprise the following steps：
(1) systematic parameter in wireless sensor network is obtained, including：Sensor SiBattery capacity B；Event IjProbability of happening Pj；
Event IjOccur to continue probability of happening a to t+1 time slots from t time slots1, do not occur to continue not probability of happening to t+1 time slots from t time slots
a2；OrderWith
Work as Sensor Events I when being illustrated respectively in j time slotkFrom generation to the possibility for not occurring and never occurring to generation；
In time T, all sensors are to IkThe energy consumed is
(2) according to formulaBy a1And a2Calculating single event respectively is substituted into recur
Time slot length expectation E [X1] and the continuous time slot length not occurred expectation E [X2]；According to formulaIt is determined that the length of renewal process it is expected T every timee；According to formula
It is determined that each TeThe energy consumedAccording to formulaCalculate and detect an event consumption electricity every time
Amount it is expected ak；Finally makeThe dormancy period SI of sensor is drawn, whereinRepresent T
The probability of stability that event occurs during → ∞；
(3) exploration policy is obtained according to step (2), the Ik that whole system detects can be calculated quantity occursIkThe number occurred within total time TFinally draw the detection efficient of whole systemFinally, the complete paired systems detection efficient U of method of Lagrange multipliers optimization is utilized.
A kind of 2. multiple affair detection method based on Markov chain according to claim 1, it is characterised in that：Step (1)
In, event IjThe probability of generation obeys Markov Chain, and a1＞ 0.5, a2＞ 0.5.
A kind of 3. multiple affair detection method based on Markov chain according to claim 1, it is characterised in that：Step (2)
Middle Te=t2-t1, wherein t1And t2Represent that adjacent sensor twice enters the time slot of resting state.
A kind of 4. multiple affair detection method based on Markov chain according to claim 1, it is characterised in that：Step (3)
In, exploration policy includes：(1) if occurring in sensor run time events I, sensor is detected to the event；(2) it is if preceding
Event I does not occur in one time slot, then the sensor in running status enters resting state；(3) sensor in dormancy
Whether the event I of SI automatic runnings detecting at regular intervals occurs.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110087293A (en) * | 2019-05-13 | 2019-08-02 | 深圳职业技术学院 | A kind of low energy consumption distributed event detection wireless sensor network construction method |
| CN111741531A (en) * | 2020-08-12 | 2020-10-02 | 浙江工商大学 | Optimization method for optimal operation state of communication equipment under 5G base station |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110087293A (en) * | 2019-05-13 | 2019-08-02 | 深圳职业技术学院 | A kind of low energy consumption distributed event detection wireless sensor network construction method |
| CN110087293B (en) * | 2019-05-13 | 2022-07-01 | 深圳职业技术学院 | Low-energy-consumption distributed event detection wireless sensor network construction method |
| CN111741531A (en) * | 2020-08-12 | 2020-10-02 | 浙江工商大学 | Optimization method for optimal operation state of communication equipment under 5G base station |
| CN111741531B (en) * | 2020-08-12 | 2020-11-24 | 浙江工商大学 | Optimization method for optimal operation state of communication equipment under 5G base station |
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