CN104168641B - A kind of wireless sensor network time synchronization method based on temperature sensing - Google Patents

A kind of wireless sensor network time synchronization method based on temperature sensing Download PDF

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CN104168641B
CN104168641B CN201410341165.5A CN201410341165A CN104168641B CN 104168641 B CN104168641 B CN 104168641B CN 201410341165 A CN201410341165 A CN 201410341165A CN 104168641 B CN104168641 B CN 104168641B
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temperature
skew
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金梦
房鼎益
陈晓江
刘晨
徐丹
郭军
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Northwest University
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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
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    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention discloses a kind of wireless sensor network time synchronization method based on temperature sensing, this method comprises the step of：Sensitivity Factor determines, Sensitivity Factor interval determines, local zone time renewal.This algorithm take into account node current environmental temperature change influence to caused by node frequency deviation in offset estimation, improve the precision of offset estimation.Simultaneously as the algorithm relies primarily on local information during time synchronized, greatly reduce information transfer number, so as to largely reducing energy consumption, and reduce by information successively transmission belt Lai error accumulation.Finally, due to dependence of the algorithm to information transfer is relatively low, so as to solve the problems, such as under wild environment because communication caused by bad weather and node location dynamic change etc. is unstable.

Description

A kind of wireless sensor network time synchronization method based on temperature sensing
Technical field
The present invention relates to radio network technique field, and in particular to a kind of wireless sensor network based on temperature sensing Method for synchronizing time, this method are applied to the large-scale area monitoring wireless sensor network such as wild animal monitoring, earthen ruins monitoring Network application.
Background technology
As an important support technology of wireless sensor network, time synchronized is widely used, such as data Integration technology, dormancy dispatching technology, the location technology based on TOA and target tracking etc. are required for the whole network node retention time same Step.In large-scale sensor network, network node is numerous, and the energy of node, disposal ability, and bandwidth etc. is relatively limited, Network environment rather harsh, therefore, this requires sensor network time synchronized algorithm to have low communication expense, low calculating complicated The features such as degree, good autgmentability and robustness.
During carrying out monitoring (such as wild animal, earthen ruins etc.) on a large scale, the different pieces of information from different sensors (lteral data, voice data, video data etc.) needs to be combined to, and by a series of statistics and analysis, finally Obtain effective environmental information and deduce the event being likely to occur.During being merged to a variety of data, need The time synchronized of each node of gathered data is wanted, otherwise can obtain the temporal information of mistake, ultimately results in the analysis knot of mistake Fruit.In addition, the characteristics of being limited due to sensor network energy, node need to carry out periodic dormancy to reduce energy consumption. This just needs the node of the whole network to adjust the dormancy period of oneself according to a specific rule, so as to ensure the correct biography of data It is defeated.However, inter-node times it is asynchronous will cause node mistake time carry out dormancy, so as to influence data transfer into Power.In the prior art, in order to ensure the time synchronized between the whole network node, when having had many in wireless sensor network Between synchronization policy：
The first kind：Method for synchronizing time based on packet-switching
This method is exchanged to carry out the time synchronized between a pair of nodes by what inter-node times stabbed first, then passes through network The method of layering successively synchronously, be finally reached the time synchronized of the whole network.Tripartite's planar defect be present in this method：1) due to the party Method is exchanged using frequently timestamp to carry out time synchronized, therefore can introduce substantial amounts of communication overhead.In wireless sensing In device network, the communication overhead expense that proportion is far above computing cost in overhead and data acquisition is brought, therefore should Method can cause a large amount of losses of node energy.2) because timestamp successively transmits in a network, therefore error can be caused Accumulation, so as to influence time synchronization accuracy.3) due to using cheap crystal oscillator in sensor network, the crystal oscillator is vulnerable to temperature The influence of the working environments such as degree, voltage, vibrations, and this method does not consider this point.
Second class：Method for synchronizing time based on external cycles signal
In this approach, all nodes of the whole network all adjust the clock of oneself frequency according to a unified cyclical signal Rate.This cyclical signal includes：Wifi signals, broadcast singal, optical signal sent of daylight etc..This method is in synchronous mistake Local information is depended in journey, largely reduces the exchange of timestamp, reduces energy consumption, reduces error and tires out Product.The defects of this method is present has：1) there is certain limitation to environment, such method does not apply to what can not be reached with various signals Wild environment.And the method synchronized according to fluorescent lamp requires that sensor network must operate at indoor environment.2)WIFI Signal and broadcast singal need extra hardware device to be received, and this equipment not only increases economic expense, and needs High energy consumption supports, and is not suitable for large scale deployment.3) this method is also without the shadow in view of working environment to cheap crystal oscillator Ring.
The content of the invention
The sensor network time synchronization method being operated under Large scale field environment has with the method under usual environment It is significant different, the present situation of large scale network is not applied for for existing synchronous method, the present invention proposes that one kind is based on temperature The wireless sensor network time synchronization method of perception so that synchronizing process can still reach high under extensive environment in the wild Precision and the requirement of low energy consumption.
In order to realize above-mentioned task, the technical solution adopted by the present invention is：
A kind of wireless sensor network time synchronization method based on temperature sensing, comprises the following steps：
It is the reference mode in wireless sensor network to remember R, and N is any one sensor section in addition to reference mode Point, after netinit, node N repeats the following cycle, and the cycle includes step 1 to step 3：
Step 1, Sensitivity Factor determine
Step S10, node N send time synchronized request data package to reference mode R；
Step S11, node R return to four reply datas successively after time of receipt (T of R) synchronization request packet, to node N Bag：M0,M1,M2,M3, the local zone time of moment node R, respectively time (R) when record sends the packet in each packet0 ~time (R)3；M0With M1、M2With M3Interval time is 1s；M1With M2Interval time is 10min；
Step S12, node N are receiving packet M0~M3While, record the local zone time time of oneself0~time3 And the environment temperature temp that node N is presently in0~temp3；
Step S13, node N is to it in time1And time3Frequency deviation skew1And skew3Calculated：
Step S14, node N are calculated current Sensitivity Factor TSF values according to frequency deviation and temperature information：
In formula 2,Temp is normal temperature, and value is 25℃；
Step 2, Sensitivity Factor interval determine
Step S20, node N obtain local environment temperature T this moment1, the node N upper cycles, the moment local environment temperature was Tpre, then node N rate of temperature change DT be：
In formula 3, dpreFor the upper cycle step S22 Sensitivity Factor interval d obtained value；
Step S21, node N calculate current accumulated error value error：
Step S22, node N are set to Sensitivity Factor interval d, and method is：
In formula 5, the μ s of μ=150~900, λ=0.6~1.4 DEG C, dstd=20min；
It is skew that step S23, node N, which set current frequency offset value skew,3, step S31,100s ＜ Δs t is transferred to after Δ t durations ＜ 10000s；
Step 3, local zone time renewal
Step S30, node N obtain its local environment temperature T this moment2, according to the Sensitivity Factor TSF of step S14 calculating Node current frequency offset is calculated：
Skew=TSF (T-Temp)2(formula 6)
In above formula, T represents the time；
Step S31, node N calculate current skew：
In formula 7, skewpreThe current frequency offset value obtained for upper cycle step S23 or step S30, offsetpreTo be upper The current phase bias that one cycle step S31 is calculated；
Step S32, if node N current skew meets：
Then node N is updated to the own local time, and the local zone time clock after renewal is：
Clock=clockpre+ offset (formula 9)
In formula 8 and formula 9, ε is local clock cycles, clockpreFor the local zone time before renewal；Renewal finishes Afterwards, node N is by offsetpreReset；
Step S33, node N check timer, if duration d is not timed out, step S30 is gone to after dormancy Δ t durations；It is no Then, this cycle is completed, step S10 is transferred to and starts to perform next cycle.
The present invention has following technological merit compared with prior art：
1. reduce energy consumption；
Firstly, since node depended on during synchronizing local information carry out clock frequency deviation estimation with And the renewal of local clock, largely reduce communication overhead.
Secondly as node is to carry out time synchronized according to its ambient temperature information, and the acquisition of temperature need not By extra hardware device, it is only necessary to temperature sensor, therefore, reduce signal and receive energy consumption.
2. improve synchronization accuracy；
First, node take into account influence of the working environment (temperature) to node crystal oscillator during synchronizing, and This influence is compensated, therefore can be avoided because frequency deviation caused by temperature changes, so as to reduce the tired of clock skew Product.
Secondly as the method for synchronizing time does not need the successively transmission of timestamp substantially, therefore reduce synchronous error Accumulation.
3. improve robustness
Similarly, since node relies primarily on local information, rather than the friendship of timestamp during time synchronized is carried out Change, therefore, requirement of this method to communication condition is relatively low.It can not be worked when exception occurs in the communication equipment of node, or in net Network node location dynamic change, it can not be kept with reference mode in the case of communicating, node can be according to the information of voltage of local Time synchronized is carried out, therefore improves robustness.
Brief description of the drawings
Fig. 1 is the flow chart of the inventive method；
Fig. 2 is " temperature-frequency deviation " relation schematic diagram；
Fig. 3 is frequency deviation skew estimation procedure and temperature susceplibility factor TSF estimation procedure period-luminosity relation schematic diagrames；
Fig. 4 is emulation experiment analog temperature change schematic diagram；
Fig. 5 is Accuracy Controlling Parameter μ true to the influence of λ sync intervals and timestamp exchange times again and μ optimal value Determine experimental result picture；
Fig. 6 is that temperature adjustment factor lambda estimates that interval and the influence of timestamp exchange times and λ optimal value are true to TSF Determine experimental result picture；
Fig. 7 is that cycle dynamicses TSFB algorithms, fixed cycle TSFB algorithm and the contrast of EACS algorithms frequency offset estimation accuracy are real Test result figure；
Fig. 8 (a) is TSFB algorithms and FTSP algorithm experiment of energy consumption result figures under different accuracy control parameter μ values；
Fig. 8 (b) is TSFB algorithms and FTSP algorithm experiment of energy consumption result figures under different temperatures regulatory factor λ values；
Fig. 9 is TSFB algorithms and FTSP algorithm robustness contrast and experiment figures；
Embodiment
Applicant is in the extensive monitorings such as wild animal monitoring, earthen ruins monitoring, in order to ensure dormancy dispatching process Be smoothed out, and ensure the correctness of data fusion phase data result, it is necessary to establish high accuracy and low energy consumption when Between synchronization policy.And Large scale field environment has two compared with general network environment：1) network size is big, causes to save Point communication energy consumption and time synchronized accumulated error increase rapidly；2) environment dynamic change, the signal intelligence between node is caused It is unstable, it is impossible to keep lasting proper communication.
The present situation of Large scale field environment is not suitable for for existing method for synchronizing time, the present invention proposes a kind of based on temperature The method for synchronizing time of the sensor network perceived is spent, using the high correlation of nodal clock frequency deviation and temperature (such as Fig. 2 institutes Show) carry out time synchronized so that and Time synchronization algorithm remains able to accomplish high accuracy, low energy under this special network condition Consumption and high robust.
The present invention needs periodically to enter its Sensitivity Factor TSF during sensor node carries out time synchronized Row estimation and renewal.Here Sensitivity Factor TSF represents sensitivity of the node to its local environment temperature change.Every The interval period of TSF estimations twice, node carry out the estimation of frequency deviation according to its local environment temperature value and current TS F estimates And compensation.Here each node that frequency deviation refers to relative to same reference mode frequency deviation.Meanwhile node misses according to estimation The accumulation of difference and temperature variations, the regulation at TSF estimations interval can be performed to node, energy expenditure and estimation are reached with this The balance of precision.
First, the inventive method detailed step
The present invention proposes a kind of method for synchronizing time of the wireless sensor network based on temperature sensing, and this method is in synchronization During the clock frequency deviation of node is constantly corrected according to local temperature value and Sensitivity Factor TSF, and clock is mutually biased Row compensation, meanwhile, according to the accumulation situation of error and temperature change situation periodically carry out Sensitivity Factor TSF estimations and Renewal.As shown in figure 1, this method comprises the following steps：
A kind of wireless sensor network time synchronization method based on temperature sensing, the party utilize the temperature of wireless senser Relation between frequency deviation carries out time synchronized, comprises the following steps：
It is the reference mode in wireless sensor network to remember R, and N is any one sensor section in addition to reference mode Point, after netinit, node N repeats the following cycle, i.e., all nodes constantly repeat to perform according to the cycle；Time is same Step process is accompanied by the operation of whole network and carried out, as long as network lifecycle is not over, time synchronization process is just Ceaselessly can periodically it go on；Loop cycle process as shown in figure 3, the cycle include step 1 to step 3：
Step 1, Sensitivity Factor determine
In order that node can compensate according to Current Temperatures to time frequency deviation in time in synchronizing process, in nothing Line sensor network nodes carry out time synchronized during need periodically to estimate its Sensitivity Factor TSF and Renewal.TSF estimation depends on the variable quantity and corresponding frequency deviation variable quantity in estimation procedure interior joint temperature.Node In order to obtain its frequency deviation information, it is necessary to be exchanged by carrying out timestamp with reference mode R；Here reference mode is a standard Node, determined before deployment, can be an ordinary node, or a base station；The whole network node with reference mode when Between for mark carry out time synchronized：Here by taking any one node N in sensor network in addition to standard nodes as an example：
Step S10, node N send time synchronized request data package to reference mode R, inform that reference mode needs to carry out together Step process；
Step S11, node R return to four reply datas successively after time of receipt (T of R) synchronization request packet, to node N Bag：M0,M1,M2,M3, the local zone time of moment node R, respectively time (R) when record sends the packet in each packet0 ~time (R)3；(for example, M0In comprising node R send M0Time：time(R)0)M0With M1、M2With M3Interval time is 1s； M1With M2Interval time is 10min；
Step S12, to obtain the time difference between node its temporal and reference mode R, node N is receiving packet M0~M3While, record the local zone time time of oneself0~time3And the environment temperature temp that node N is presently in0~ temp3(i.e. a corresponding time value of packet and a temperature value, such as receive packet M0When, record local now Time time0With environment temperature temp0)；Here temperature information is obtained by temperature sensor, is mainly used in Sensitivity Factor and is estimated Count the measurement of temperature variation in the cycle；
Step S13, node N is according to packet M0~M3In information and the local time information time of oneself0~ time3To it in time1And time3Frequency deviation skew1And skew3Calculated, computational methods are：
Step S14, node N are calculated its current Sensitivity Factor TSF value according to frequency deviation and temperature information, are calculated public Formula is：
In formula 2, due to temp0And temp1, temp2And temp3Acquisition time be closer to (interval 1s), therefore use Mean temperature Temp in this periodaAnd TempbSensitivity Factor TSF estimation is carried out, i.e.,
Temp is normal temperature, and value is 25 DEG C；
Step 2, Sensitivity Factor interval determine
Because the situation of change of node frequency deviation can be different with the rate of change of temperature, when temperature change is obvious Wait, the change of the frequency deviation of node also can be more obvious, now in order to ensure synchronous precision, it is necessary to shorten Sensitivity Factor TSF's Cycle estimator, so as to ensure higher synchronization accuracy.And when temperature is more steady, the frequency deviation of node is hardly Become, now in order to reduce communication overhead, it is necessary to extend Sensitivity Factor TSF cycle estimator.Therefore, Sensitivity Factor interval It is determined that it need to rely on the rate of change of temperature and the accumulation situation of error：
Step S20, calculate rate of temperature change DT：Node N obtains it and is presently in environment temperature T1, the node N upper cycles The moment local environment temperature is Tpre, then node N rate of temperature change DT be：
In formula 3, dpreFor the upper cycle step S22 Sensitivity Factor interval d obtained value；Note：Because this programme exists It is that continuous circulating repetition performs after netinit, and the parameter of a cycle calculates the parameter that depend on upper a cycle Value, during as calculated rate of temperature change DT in formula 3, it is necessary to the environment temperature of upper a cycle and Sensitivity Factor interval.That is, It is T to be presently in environment temperature such as this cycle1, then T1With regard to calculating T during DT parameters as next cyclepre, this cycle it is quick Ds of the sensitivity factor interval d as next cyclepre, other specification is by that analogy；And ginseng is calculated after netinit for the first time Number is randomly provided a upper cycle parameter value, calculated for parameter current, it is necessary to during the parameter value of upper a cycle, and with Cycle afterwards constantly can be modified to the parameter of preceding cycle.
Step S21, node N calculate current accumulated error value error：
In formula 4, node N with the timestamp of reference mode according to finally exchanging result time twice3With time (R)3It Difference and time2With time (R)2The average of difference error current is estimated；
Step S22, node N are set according to step S21 and step S20 result to Sensitivity Factor interval d, and Timing from this moment on, d calculation formula are as follows：
In formula 5, μ and λ are respectively the control errors factor and the temperature adjustment factor, value are：μ=150~900 μ s, λ =0.6~1.4 DEG C；According to the result of experiment one, experiment two, as μ=300us, λ=1 DEG C, this method best performance；dstdFor Normal space, generally take dstd=20min；
From formula 5 as can be seen that when the increase of node ambient temperature variable quantity or node synchronous error raise, TSF Estimation interval can shorten to ensure synchronization accuracy accordingly, conversely, interval can increase to reduce communication overhead；
Step 23, the skew estimation procedure for convenience of after, it is skew that node N, which sets current frequency offset value skew,3, during Δ t Step S31 is transferred to after length, Δ t is time Estimate interval here；When Δ t meets 100s ＜ Δ t ＜ 10000s, i.e. network settings, As long as a Δ t is selected to be satisfied by this programme requirement within this range；
Step 3, local zone time renewal
Node N to its temperature sensitive factor TSF and Sensitivity Factor interval d after being updated, when being transferred to local Between renewal process, should during clock frequency deviation estimation depend on the temperature susceplibility factor TSF that is obtained in step 1 with And node current environmental temperature, when a length of d of time renewal process.
Step S30, in order to which (because the moment is different, the skew and step S23 of the step skew are not to clock frequency deviation skew It is same value, but two values under different situations) estimated, node N obtains its environment temperature T this moment first2, Secondly node current frequency offset is estimated according to this cycle step S14 Sensitivity Factor TSF calculated：
Skew=TSF (T-Temp)2(formula 6)
In above formula, T represents the time；
Step S31, node N calculate current skew：
In formula 7, skewpreThe current frequency offset value obtained for upper cycle step S23 or step S30, i.e., if from step S23 skips to step S31, then skewpreValue be upper cycle step S23 in frequency deviation value skew；If performed from step S30 To step S31, then skewpreValue be upper cycle step S30 in frequency deviation value skew；offsetpreFor a upper cycle step The current phase bias that S31 is calculated；
Step S32, if node N current skew offset meets formula 8, then it is assumed that node N skew is excessive and can be right Network application impacts, and now, node N needs to be updated oneself local zone time, otherwise without renewal：
ε is local clock cycles in formula 8, can also suitably increase ε's in the case of not strict to synchronization accuracy requirement Value；Local zone time clock after renewal is：
Clock=clockpre+ offset (formula 9)
In formula 9, clockpreFor the local zone time before renewal；After renewal, node N is by offsetpreReset；Frequency deviation It is as shown in Figure 3 with skew period-luminosity relation；
Step S33, node N check timer, if since step S22 timing, duration d is not timed out, then dormancy Δ t durations After go to step S30；Otherwise, this cycle is completed, step S10 is transferred to and starts to perform next cycle.
2nd, in the inventive method each relevant parameter determination：
Experiment one：Influence and μ of the control errors factor mu to packet-switching interval and packet-switching number it is optimal Value determines：
Step 1：Emulation experiment scene initialization
Applicant has simulated 12000 temperature datas according to the temperature variations under true field scene, represents The temperature value of each second in 200 minutes, the temperature obtained according to the data press change curve as shown in Figure 4.In order to prove we Net synchronization capability of the method under temperature variations, the track mainly replace between two kinds of temperature regimes：Temperature is gentle and warm Spend climb mode.Range of temperature is 25 DEG C~43 DEG C, according to temperature and the relation of frequency deviation, its corresponding 12000 frequency deviation The excursion of data is 20ppm~60ppm.
Step 2：Take Accuracy Controlling Parameter μ=150,300,450,750,900 (units：μs).In every kind of control parameter μ Value under, 12000 frequency deviation data are synchronized according to the time synchronized step of the foregoing description, altogether carry out five realities Test.The exchange times of each experimental record timestamp in synchronizing process, and the interval time exchanged per timestamp twice, see Examine influences of the μ to this two parameters.
Step 3：Analysis and processing experimental data
Fig. 5 shows temperature susceplibility factor TSF estimations interval and timestamp exchange times with Accuracy Controlling Parameter μ's Variation tendency.As can be seen that when parameter μ changes to 300 μ s from 150 μ s, the exchange times of timestamp significantly reduce, meanwhile, Average TSF estimations interval significantly increases.And after parameter μ changes to 300 μ s, the change of this two parameters tends towards stability.Cause This is for the precision of guarantee time synchronized while energy consumption is reduced, performance of this method in Accuracy Controlling Parameter μ=300 μ s Most preferably.
Experiment two：Influences and λ of the temperature coordinating factor λ to packet-switching interval and packet-switching number it is optimal Value determines：
Step 1：Emulation experiment scene initialization
Applicant has simulated 12000 temperature datas according to the temperature variations under true field scene, represents The temperature value of each second in 200 minutes.The temperature pressure change curve obtained according to the data is as shown in Figure 4.In order to prove we Net synchronization capability of the method under temperature variations, the track mainly replace between two kinds of temperature regimes：Temperature is gentle and warm Spend climb mode.Range of temperature is 25 DEG C~43 DEG C, according to temperature and the relation of frequency deviation, its corresponding 12000 frequency deviation The excursion of data is 20ppm~60ppm.
Step 2：Take temperature coordinating factor λ=0.6,0.8,1.0,1.2,1.4 (units：℃).In every kind of coordinating factor λ Value under, 12000 frequency deviation data are synchronized according to the time synchronized step of the foregoing description, altogether carry out five realities Test.The exchange times of each experimental record timestamp in synchronizing process, and the interval time exchanged per timestamp twice, see Examine influences of the λ to this two parameters；
Step 3：Analysis and processing experimental data
Fig. 6 shows temperature susceplibility factor TSF estimations interval and timestamp exchange times with Accuracy Controlling Parameter μ's Variation tendency.As can be seen that when parameter lambda is from when changing to 1.0 DEG C for 0.8 DEG C, the exchange times of timestamp significantly reduce, meanwhile, Average TSF estimations interval significantly increases；And after parameter lambda changes to 1.0 DEG C, the change of this two parameters tends towards stability.Cause This is for the precision of guarantee time synchronized while energy consumption is reduced, performance of this method at Accuracy Controlling Parameter λ=1.0 DEG C Most preferably.
3rd, the inventive method performance test and the contrast experiment with other algorithms
We verify the performance of synchronous method of the present invention and relative to the excellent of other method by one group of experiment below Gesture, experiment are mainly compared to the performance of following four algorithm：
(1) the inventive method (being denoted as TSFB methods)；
(2) situation (be denoted as fixed cycle TSFB) of this method when using the fixed cycle；
(3) FTSP algorithms：The algorithm is the Time synchronization algorithm exchanged based on timestamp.This method is first by between node The exchange of timestamp is carried out successively synchronously, finally to carry out the time synchronized between a pair of nodes, then by the method for network hierarchy Reach the time synchronized of the whole network.And this method is it is not intended that influence of the working environment to its frequency deviation of node.
(4) EACS algorithms：The algorithm is equally the algorithm that time synchronized is carried out using temperature, but this method is in node The relation between node frequency deviation and temperature is obtained before deployment, and the relation is stored in node in table form.In synchronization During, this method assume relation between frequency deviation and temperature will not over time and temperature change and change, this is not Meet actual frequency deviation changing pattern, therefore synchronous error can be brought.
Test mainly proves the advantage of the present invention from following several respects：
1. frequency offset estimation accuracy；2. energy consumption (i.e. resynchronisation interval)；3. algorithm robustness；
Artificial network initializes：
Applicant has simulated 12000 temperature datas according to the temperature variations under true field scene, represents The temperature value of each second in 200 minutes.The temperature pressure change curve obtained according to the data is as shown in Figure 4.In order to prove we Net synchronization capability of the method under temperature variations, the track mainly replace between two kinds of temperature regimes：Temperature is gentle and warm Spend climb mode.Range of temperature is 225 DEG C~43 DEG C, according to temperature and the relation of frequency deviation, its corresponding 12000 frequency deviation The excursion of data is 20ppm~60ppm.
A. algorithm frequency offset estimation accuracy is assessed
Emulation experiment process：
The offset estimation of experiment main contrast cycle dynamicses TSFB algorithms, fixed cycle TSFB algorithm and EACS algorithms Precision.In this experiment, the TSFB algorithms of cycle dynamicses are emulated first, in order to verify the algorithm under different cycles Can, when testing initial, we take standard TSF cycle estimator length dstdRespectively 1500s, 1800s, 2000s, 2300s and 2500s, experiment obtain average packet switch interval and are respectively after terminating：1050s, 1190s, 1380s, 1450s and 1950s.So Afterwards, the temperature susceplibility factor TSF of EACS algorithms estimations interval is set and fixed according to obtained average packet switch interval The TSF estimations interval of cycle T SFB algorithms, repeats to test.Finally, by the frequency offset estimation result and initialization procedure of three kinds of methods The true frequency deviation data of middle generation are contrasted, and count the maximum and average value of three kinds of offset estimation errors.
Experimental result：
As shown in Figure 7, it is evident that can be with by the contrast of fixed and dynamic interval TSFB algorithms and EACS algorithms Find out, due to TSFB algorithms can be between dynamic estimation temperature and frequency deviation sensitivity TSF, therefore can avoid due to environment Current " temperature-frequency deviation " corresponding relation brought is not inconsistent caused offset estimation error with priori, same so as to improve Walk precision.In addition, by contrasting dynamic and fixed TSFB algorithms, it can be seen that the introducing of cycle dynamicses regulation mechanism Cycle dynamicses TSFB algorithms are enabled to correct TSF values in time in the case of node variation of ambient temperature, compared to fixed week The TSFB algorithms of phase can reduce offset estimation error to a certain extent.
B. algorithm energy consumption assessment
Emulation experiment process：
The algorithm energy consumption of experiment main contrast TSFB algorithms and FTSP algorithms.
Accuracy Controlling Parameter μ=150,300,450,750,900 (units are taken first：μs).For TSFB algorithms every kind of Under control parameter μ value, 12000 frequency deviation data are synchronized according to the time synchronized step of the foregoing description, altogether Carry out five experiments.The interval time that each experimental record exchanges in synchronizing process per timestamp twice.And calculated for FTSP Method, the resynchronisation cycle of the algorithm is fixed (150s).
Next takes temperature coordinating factor λ=0.6,0.8,1.0,1.2,1.4 (units：℃).For TSFB algorithms every kind of Under coordinating factor λ value, 12000 frequency deviation data are synchronized according to the time synchronized step of the foregoing description, altogether Carry out five experiments.The interval time that each experimental record exchanges in synchronizing process per timestamp twice.And calculated for FTSP Method, the resynchronisation cycle of the algorithm is fixed (150s).
Experimental result：
In Fig. 8 (a) and Fig. 8 (b), it will be apparent that for TSFB algorithms, the interval time exchanged per timestamp twice Increase with Accuracy Controlling Parameter μ and degree coordinating factor λ increase.However, even in control errors factor mu and temperature In the case of coordinating factor λ values very low (the μ s of μ=150, λ=0.6 DEG C), node can still keep timestamp friendship twice The Mean Time Between Replacement changed is more than 900s, and this is significantly larger than FTSP 150s.And the exchange of timestamp can bring huge communication Expense, and communication overhead accounts for significant proportion in sensor network total energy consumption.Therefore, it was demonstrated that TSFB algorithms can ensure precision On the premise of reduce energy consumption.It is very suitable for the wireless sensor network of finite energy.
C. algorithm robustness is assessed
Emulation experiment process：
The experimental process simulation causes the situation that nodal information transmission can not be carried out under adverse circumstances in the wild.For TSFB algorithms, 12000 frequency deviation data are synchronized according further to the synchronizing step of the foregoing description, but opened from 1000s Begin, without the step of the foregoing description one, i.e. TSF estimation procedures (because the process is dependent on timestamp exchange).FTSP algorithms The exchange of timestamp can not equally be carried out.
Experimental result：
As shown in figure 9, in the incipient stage (i.e. 0~1000s) of experiment, the gap of TSFB algorithms and FTSP algorithms not ten It is clearly demarcated aobvious.However, as environment temperature starts to change, frequency deviation constantly changes also with temperature.Now FTSP algorithms can only be according to The offset estimation value of most initial is relied to estimate and compensate time skew, therefore error is constantly accumulated.And can also from Fig. 9 Go out, node ambient temperature value constantly rises since 3000s, and this causes the frequency deviation rate of change of node to raise, and now FTSP Algorithm can not catch the change.Therefore the ever-increasing offset estimation errors of FTSP have ultimately resulted in the constantly tired of its synchronous error Product.Compared to FTSP algorithms, TSFB algorithms are maintained to relatively low synchronous error in the case of communication failure.This Be because communication failure only causes TSF and can not normally updated, and node can according to the last TSF estimated results and The temperature information that sensor node collects is updated to frequency deviation, largely reduces the frequency as caused by voltage change Inclined evaluated error.Therefore, there is higher robustness compared to FTSP algorithms, TSFB algorithms.

Claims (1)

  1. A kind of 1. wireless sensor network time synchronization method based on temperature sensing, it is characterised in that：
    Remember that R is the reference mode in wireless sensor network, N is any one sensor node in addition to reference mode, net After network initialization, node N repeats the following cycle, and the cycle includes step 1 to step 3：
    Step 1, Sensitivity Factor determine
    Step S10, node N send time synchronized request data package to reference mode R；
    Step S11, node R return to four reply data bags successively after time of receipt (T of R) synchronization request packet, to node N：M0, M1,M2,M3, the local zone time of moment node R, respectively time (R) when record sends the packet in each packet0~ time(R)3；M0With M1、M2With M3Interval time is 1s；M1With M2Interval time is 10min；
    Step S12, node N are receiving packet M0~M3While, record the local zone time time of oneself0~time3And The environment temperature temp that node N is presently in0~temp3；
    Step S13, node N is to it in time1And time3Frequency deviation skew1And skew3Calculated：
    Step S14, node N are calculated current Sensitivity Factor TSF values according to frequency deviation and temperature information：
    In formula 2,Temp is normal temperature, value 25 ℃；
    Step 2, Sensitivity Factor interval determine
    Step S20, node N obtain local environment temperature T this moment1, the node N upper cycles, the moment local environment temperature was Tpre, Then node N rate of temperature change DT is：
    In formula 3, dpreFor the upper cycle step S22 Sensitivity Factor interval d obtained value；
    Step S21, node N calculate current accumulated error value error：
    Step S22, node N are set to Sensitivity Factor interval d, and method is：
    In formula 5, the μ s of μ=150~900, λ=0.6~1.4 DEG C, dstd=20min；
    It is skew that step S23, node N, which set current frequency offset value skew,3, step S31,100s ＜ Δ t ＜ are transferred to after Δ t durations 10000s；
    Step 3, local zone time renewal
    Step S30, node N obtain its local environment temperature T this moment2, the Sensitivity Factor TSF calculated according to step S14 is to node Current frequency offset is calculated：
    Skew=TSF (T-Temp)2(formula 6)
    In above formula, T represents the time；
    Step S31, node N calculate current skew：
    In formula 7, skewpreThe current frequency offset value obtained for upper cycle step S23 or step S30, offsetpreFor upper one week The current phase bias that phase step S31 is calculated；
    Step S32, if node N current skew meets：
    Then node N is updated to the own local time, and the local zone time clock after renewal is：
    Clock=clockpre+ offset (formula 9)
    In formula 8 and formula 9, ε is local clock cycles, clockpreFor the local zone time before renewal；After renewal, section Point N is by offsetpreReset；
    Step S33, node N check timer, if duration d is not timed out, step S30 is gone to after dormancy Δ t durations；Otherwise, it is complete In the cost cycle, it is transferred to step S10 and starts to perform next cycle.
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