CN105704666A - Internet of Things sensing node charging delay reducing method and system - Google Patents

Abstract

The invention relates to an Internet of Things sensing node charging delay reducing method and system. The method comprises the following steps: in a first step, total charging time is taken as an object function, that energy charged via each sensing node is not less than a threshold value is used as a constraint condition, and a linear optimization model for total charging time minimization is built so as to obtain the positions and the number of wireless charging devices; if the positions and the number of the wireless charging devices cannot be obtained, then a step two is carried out; otherwise, a step three is carried out. In the step two, the scope of the positions of the wireless charging devices is narrowed down, and an attempt to obtain the positions and the number of wireless charging devices is made via use of the linear optimization model. In the step three, the whether the number of the wireless charging devices surpass a preset number is determined; if yes, a step four is carried out; if no, operation is concluded. In the step four, the number of the wireless charging device is reduced to the preset number via adoption of an integrating manner. According to the Internet of Things sensing node charging delay reducing method and system, the total charging time can be reduced while the number of the wireless charging device does not surpass the preset number, and complexity of solving is greatly lowered.

Description

A kind of method and system reducing Internet of Things sensing node charging delay

Technical field

The present invention relates to Internet of Things art field, particularly to a kind of method and system reducing Internet of Things sensing node charging delay。

Background technology

The energy supply of internet of things equipment is one of key factor of consideration in Internet of Things design。The sensing node of existing many Internet of Things is all battery-powered, and the life-span of sensing node is that the energy entrained by battery determines。Propose many schemes obtaining the energy from bad border before, but it is too big and unrealistic relative to sensor node volume to be highly dependent on environment and charging device because of it。In wireless energy transmission technology field, Kurs et al. utilizes mr techniques to achieve important breakthrough, it is achieved that charging equipment is namely chargeable without being connected with charging device。

Improve charge efficiency, mainly from the viewpoint of internal microelectronic design and the charging interval two to wireless chargeable node。But present stage, how research reduces the charging interval to sensing node more gears to actual circumstances。In actual applications, it is usually the total charging time considering that all sensing nodes in Internet of Things are charged, and needs to ensure that the charged energy of each sensing node is not less than threshold value, to ensure that sensing node can realize perception, calculating and communication function。

Present stage Internet of Things sensing node is carried out wireless charging be usually employing RFID charging device sensing node is charged, be the lifting realizing whole Internet of Things performance by reducing the charging interval of the sensing node in whole network。In practice, the cost of RFID charging device is higher, and in order to save cost, being usually needs to carry RFID charging device with car-mounted device and go to be charged to wireless sensing node。Distance dependent between charge power and RFID charging device and sensing node。The position of RFID charging device and the number used can affect charging interval and the cost of whole Internet of Things。

Therefore, relate in the Internet of things system that sensing node is charged at one, position and the minimum use number of seeking wireless charging device become very meaningful, and cost and charging interval on reducing Internet of things system have important impact, affect performance and the application of Internet of Things。

Summary of the invention

It is an object of the present invention to provide a kind of method and system reducing Internet of Things sensing node charging delay, solve the above-mentioned problems in the prior art。

The technical scheme is that

A kind of method reducing Internet of Things sensing node charging delay, comprises the steps:

Step 1, with in Internet of Things all sensing nodes charge total charging time for object function, it is not less than threshold value for constraints with the energy that each sensing node is charged, builds position and the number of the linear optimization model solution wireless charging device that total charging time minimizes；If without solution, then perform step 2；Otherwise, then step 3 is performed；

Step 2, the change changing the charge power to sensing node according to the position of wireless charging device, reduce the scope residing for the position of wireless charging device, and again solve position and the number of wireless charging device in conjunction with described linear optimization model；

Step 3, it is judged that whether the number of wireless charging device exceedes predetermined number；It is then perform step 4；No, then end operation；

Step 4, adopts the mode merged, and reduces the number of wireless charging device to predetermined number。

The invention has the beneficial effects as follows: build the linear optimization model that minimizes of total charging time, in conjunction with the mode of the scope reduced residing for the position of wireless charging device and fusion, it is thus achieved that the position of wireless charging device and number；While the number of wireless charging device is less than predetermined number, make total charging time minimum；And greatly reduce the complexity solved。

On the basis of technique scheme, the present invention can also do following improvement。

Further, described linear optimization model is as follows:

$\left\{\begin{array}{c}\begin{array}{cc}\min & T=\underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{t}_j\end{array}\\ s.t.\underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{P}_{ij}{t}_j\≥\mathrm{\δ},\\ P_{ij}=\frac{\mathrm{\α}}{{(\sqrt{{(W_x^i-R_x^j)}^2+{(W_y^i-R_y^j)}^2}+\mathrm{\β})}^2},\\ i\∈\{1,2,3...N\},j\∈\{1,2,3...\mathrm{\∞}\}\end{array}\right.$

Wherein, described T is described total charging time, described t_jFor the charging interval of arbitrary wireless charging device, described P_ijFor the described arbitrary wireless charging device charge power to arbitrary sensing node, described δ is described threshold value, and described N is the sum of sensing node,For the position coordinates of described arbitrary sensing node,Position coordinates for described arbitrary wireless charging device, described α is the described arbitrary wireless charging device computational constant to the charge power of described arbitrary sensing node, and described β is the correction constant of described arbitrary wireless charging device and described arbitrary sensing node distance。

Further, implementing of described step 2 comprises the steps:

Step 21, builds the least radius circle including all sensing nodes；

Step 22, in described least radius circle, with each sensing node for the center of circle, draw circular arc with different radii, and make wireless charging device, on the adjacent circular arc of arbitrary sensing node, the charge power of described arbitrary sensing node be differed preset value, obtain the overlapping region that charge power scope is identical；

Step 23, by the range shorter residing for the position of wireless charging device to described overlapping region, and again solves position and the number of wireless charging device in conjunction with described linear optimization model。

Adopt above-mentioned further scheme to provide the benefit that, by overlapping region identical for the range shorter residing for the position of wireless charging device to charge power scope, reduce the prolongation to total charging time of the scope residing for the position of wireless charging device。

Further, implementing of described step 21 comprises the steps:

Step 211, chooses not on the same line and be positioned at any four sensing node on border；

Step 212, chooses any three sensing nodes from described any four sensing node and draws circle, and make described circle comprise a remaining sensing node in described any four sensing node；

Step 213, chooses any one sensing node that is unselected and that be positioned at border, is combined into four sensing nodes with described any three sensing nodes；

Step 214, using described four sensing nodes as described any four sensing node, return circulation and perform step 212 and step 213, until all sensing nodes being positioned at border are all contained in a circle, end loop, then final drawn circle is described least radius circle。

Further, implementing of described step 4 comprises the steps:

Step 41, the position according to wireless charging device, adopt K means Method that whole wireless charging devices are divided into K class；Wherein, described K is equal to described predetermined number；

Step 42, chooses the charge power position closest to the wireless charging device of this type of average charge power as the position of final wireless charging device from each apoplexy due to endogenous wind。

Adopt above-mentioned further scheme to provide the benefit that, adopt K means Method to classify, improve classification accuracy；Choose the charge power position closest to the wireless charging device of this type of average charge power as the position of final wireless charging device from each apoplexy due to endogenous wind, reduce the prolongation merged total charging time。

Another technical scheme of the present invention is as follows:

A kind of system reducing Internet of Things sensing node charging delay, including first solving module, second solving module, judge module and Fusion Module；

Described first solves module, it is used for the total charging time that all sensing nodes in Internet of Things are charged for object function, it is not less than threshold value for constraints with the energy that each sensing node is charged, builds position and the number of the linear optimization model solution wireless charging device that total charging time minimizes；If without solution, then second is driven to solve module work；Otherwise, then judge module work is driven；

Described second solves module, it is for the change changing the charge power to sensing node of the position according to wireless charging device, reduce the scope residing for the position of wireless charging device, and again solve position and the number of wireless charging device in conjunction with described linear optimization model；

Described judge module, it is for judging whether the number of wireless charging device exceedes predetermined number；It is then drive Fusion Module work；No, then end operation；

Described Fusion Module, the number of wireless charging device, for adopting the mode of fusion, is reduced to predetermined number by it。

On the basis of technique scheme, the present invention can also do following improvement。

Further, described linear optimization model is as follows:

$\left\{\begin{array}{c}\begin{array}{cc}\min & T=\underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{t}_j\end{array}\\ s.t.\underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{P}_{ij}{t}_j\≥\mathrm{\δ},\\ P_{ij}=\frac{\mathrm{\α}}{{(\sqrt{{(W_x^i-R_x^j)}^2+{(W_y^i-R_y^j)}^2}+\mathrm{\β})}^2},\\ i\∈\{1,2,3...N\},j\∈\{1,2,3...\mathrm{\∞}\}\end{array}\right.$

Wherein, described T is described total charging time, described t_jFor the charging interval of arbitrary wireless charging device, described P_ijFor the described arbitrary wireless charging device charge power to arbitrary sensing node, described δ is described threshold value, and described N is the sum of sensing node,For the position coordinates of described arbitrary sensing node,Position coordinates for described arbitrary wireless charging device, described α is the described arbitrary wireless charging device computational constant to the charge power of described arbitrary sensing node, and described β is the correction constant of described arbitrary wireless charging device and described arbitrary sensing node distance。

Further, described second solve that module includes least radius circle construction unit, overlapping region generates unit and solve unit；

Described least radius circle construction unit, it is for building the least radius circle including all sensing nodes；

Described overlapping region generates unit, it is in described least radius circle, with each sensing node for the center of circle, circular arc is drawn with different radii, and make wireless charging device, on the adjacent circular arc of arbitrary sensing node, the charge power of described arbitrary sensing node be differed preset value, obtain the overlapping region that charge power scope is identical；

Described solving unit, it is for by the range shorter residing for the position of wireless charging device to described overlapping region, and again solves position and the number of wireless charging device in conjunction with described linear optimization model。

Further, described least radius circle construction unit include 4 choose subelement, four strokes and dots dumpling made of glutinous rice flour unit, 4 choose again subelement and circulation drive subelement；

Choosing subelement at described 4, it is for choosing not on the same line and be positioned at any four sensing node on border；

Described four strokes and dots dumpling made of glutinous rice flour unit, it draws circle for choosing any three sensing nodes from described any four sensing node, and makes described circle comprise a remaining sensing node in described any four sensing node；

Choosing subelement again at described 4, it, for choosing any one sensing node that is unselected and that be positioned at border, is combined into four sensing nodes with described any three sensing nodes；

Described circulation driver element, its for using described four sensing nodes as described any four sensing node, return circulation drive four strokes and dots dumpling made of glutinous rice flour unit and 4 choose again subelement work, until all sensing nodes being positioned at border are all contained in a circle, end loop, then final drawn circle is described least radius circle。

Further, described Fusion Module includes taxon and integrated unit；

Described taxon, it is for the position according to wireless charging device, adopts K means Method that whole wireless charging devices are divided into K class；Wherein, described K is equal to described predetermined number；

Described integrated unit, it is for choosing the charge power position closest to the wireless charging device of this type of average charge power as the position of final wireless charging device from each apoplexy due to endogenous wind。

Accompanying drawing explanation

Fig. 1 is the method flow diagram of a kind of method reducing Internet of Things sensing node charging delay of the present invention；

Fig. 2 is the system principle diagram of a kind of system reducing Internet of Things sensing node charging delay of the present invention。

Detailed description of the invention

Below in conjunction with accompanying drawing, principles of the invention and feature being described, example is served only for explaining the present invention, is not intended to limit the scope of the present invention。

As it is shown in figure 1, a kind of method reducing Internet of Things sensing node charging delay, comprise the steps:

Step 1, with in Internet of Things all sensing nodes charge total charging time for object function, it is not less than threshold value for constraints with the energy that each sensing node is charged, builds position and the number of the linear optimization model solution wireless charging device that total charging time minimizes；If without solution, then perform step 2；Otherwise, then step 3 is performed。

Described wireless charging device is RFID charging device。

Described linear optimization model is as follows:

$\left\{\begin{array}{c}\begin{array}{cc}\min & T=\underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{t}_j\end{array}\\ s.t.\underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{P}_{ij}{t}_j\≥\mathrm{\δ},\\ P_{ij}=\frac{\mathrm{\α}}{{(\sqrt{{(W_x^i-R_x^j)}^2+{(W_y^i-R_y^j)}^2}+\mathrm{\β})}^2},\\ i\∈\{1,2,3...N\},j\∈\{1,2,3...\mathrm{\∞}\}\end{array}\right.$

Wherein, described T is described total charging time, described t_jFor the charging interval of arbitrary wireless charging device, described P_ijFor the described arbitrary wireless charging device charge power to arbitrary sensing node, described δ is described threshold value, and described N is the sum of sensing node,For the position coordinates of described arbitrary sensing node,Position coordinates for described arbitrary wireless charging device；Described α is the described arbitrary wireless charging device computational constant to the charge power of described arbitrary sensing node, and it is determined by the wavelength of the transmit power of described arbitrary wireless charging device transmitting terminal, antenna gain, attenuation quotient and radio wave and the antenna gain of described arbitrary sensing node receiving terminal；Described β is the correction constant of described arbitrary wireless charging device and described arbitrary sensing node distance, and it is by the structures shape of described arbitrary wireless charging device and described arbitrary sensing node。

Step 2, the change changing the charge power to sensing node according to the position of wireless charging device, reduce the scope residing for the position of wireless charging device, and again solve position and the number of wireless charging device in conjunction with described linear optimization model。

Implementing of described step 2 comprises the steps:

Step 21, builds the least radius circle including all sensing nodes；

Implementing of described step 21 comprises the steps:

Step 211, chooses not on the same line and be positioned at any four sensing node on border；

Step 212, chooses any three sensing nodes from described any four sensing node and draws circle, and make described circle comprise a remaining sensing node in described any four sensing node；

Step 213, chooses any one sensing node that is unselected and that be positioned at border, is combined into four sensing nodes with described any three sensing nodes；

Step 214, using described four sensing nodes as described any four sensing node, return circulation and perform step 212 and step 213, until all sensing nodes being positioned at border are all contained in a circle, end loop, then final drawn circle is described least radius circle；

Step 22, in described least radius circle, with each sensing node for the center of circle, draw circular arc with different radii, and make wireless charging device, on the adjacent circular arc of arbitrary sensing node, the charge power of described arbitrary sensing node be differed preset value, obtain the overlapping region that charge power scope is identical；

Step 23, by the range shorter residing for the position of wireless charging device to described overlapping region, and again solves position and the number of wireless charging device in conjunction with described linear optimization model。

Step 3, it is judged that whether the number of wireless charging device exceedes predetermined number；It is then perform step 4；No, then end operation。

Step 4, adopts the mode merged, and reduces the number of wireless charging device to predetermined number。

Implementing of described step 4 comprises the steps:

Step 41, the position according to wireless charging device, adopt K means Method that whole wireless charging devices are divided into K class；Wherein, described K is equal to described predetermined number；

Step 42, chooses the charge power position closest to the wireless charging device of this type of average charge power as the position of final wireless charging device from each apoplexy due to endogenous wind。

As in figure 2 it is shown, a kind of system reducing Internet of Things sensing node charging delay, including first solving module, second solving module, judge module and Fusion Module。

Described first solves module, it is used for the total charging time that all sensing nodes in Internet of Things are charged for object function, it is not less than threshold value for constraints with the energy that each sensing node is charged, builds position and the number of the linear optimization model solution wireless charging device that total charging time minimizes；If without solution, then second is driven to solve module work；Otherwise, then judge module work is driven。

Described linear optimization model is as follows:

$\left\{\begin{array}{c}\begin{array}{cc}\min & T=\underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{t}_j\end{array}\\ s.t.\underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{P}_{ij}{t}_j\≥\mathrm{\δ},\\ P_{ij}=\frac{\mathrm{\α}}{{(\sqrt{{(W_x^i-R_x^j)}^2+{(W_y^i-R_y^j)}^2}+\mathrm{\β})}^2},\\ i\∈\{1,2,3...N\},j\∈\{1,2,3...\mathrm{\∞}\}\end{array}\right.$

Wherein, described T is described total charging time, described t_jFor the charging interval of arbitrary wireless charging device, described P_ijFor the described arbitrary wireless charging device charge power to arbitrary sensing node, described δ is described threshold value, and described N is the sum of sensing node,For the position coordinates of described arbitrary sensing node,Position coordinates for described arbitrary wireless charging device, described α is the described arbitrary wireless charging device computational constant to the charge power of described arbitrary sensing node, and described β is the correction constant of described arbitrary wireless charging device and described arbitrary sensing node distance。

Described second solves module, it is for the change changing the charge power to sensing node of the position according to wireless charging device, reduce the scope residing for the position of wireless charging device, and again solve position and the number of wireless charging device in conjunction with described linear optimization model。

Described second solves module includes least radius circle construction unit, overlapping region generation unit and solves unit。

Described least radius circle construction unit, it is for building the least radius circle including all sensing nodes。

Described least radius circle construction unit include 4 choose subelement, four strokes and dots dumpling made of glutinous rice flour unit, 4 choose again subelement and circulation drive subelement。

Choosing subelement at described 4, it is for choosing not on the same line and be positioned at any four sensing node on border。

Described four strokes and dots dumpling made of glutinous rice flour unit, it draws circle for choosing any three sensing nodes from described any four sensing node, and makes described circle comprise a remaining sensing node in described any four sensing node。

Choosing subelement again at described 4, it, for choosing any one sensing node that is unselected and that be positioned at border, is combined into four sensing nodes with described any three sensing nodes。

Described circulation driver element, its for using described four sensing nodes as described any four sensing node, return circulation drive four strokes and dots dumpling made of glutinous rice flour unit and 4 choose again subelement work, until all sensing nodes being positioned at border are all contained in a circle, end loop, then final drawn circle is described least radius circle。

Described overlapping region generates unit, it is in described least radius circle, with each sensing node for the center of circle, circular arc is drawn with different radii, and make wireless charging device, on the adjacent circular arc of arbitrary sensing node, the charge power of described arbitrary sensing node be differed preset value, obtain the overlapping region that charge power scope is identical。

Described solving unit, it is for by the range shorter residing for the position of wireless charging device to described overlapping region, and again solves position and the number of wireless charging device in conjunction with described linear optimization model。

Described judge module, it is for judging whether the number of wireless charging device exceedes predetermined number；It is then drive Fusion Module work；No, then end operation。

Described Fusion Module, the number of wireless charging device, for adopting the mode of fusion, is reduced to predetermined number by it。

Described Fusion Module includes taxon and integrated unit。

Described taxon, it is for the position according to wireless charging device, adopts K means Method that whole wireless charging devices are divided into K class；Wherein, described K is equal to described predetermined number。

Described integrated unit, it is for choosing the charge power position closest to the wireless charging device of this type of average charge power as the position of final wireless charging device from each apoplexy due to endogenous wind。

The foregoing is only presently preferred embodiments of the present invention, not in order to limit the present invention, all within the spirit and principles in the present invention, any amendment of making, equivalent replacement, improvement etc., should be included within protection scope of the present invention。

Claims (10)

1. the method reducing Internet of Things sensing node charging delay, it is characterised in that comprise the steps:

Step 1, with in Internet of Things all sensing nodes charge total charging time for object function, it is not less than threshold value for constraints with the energy that each sensing node is charged, builds position and the number of the linear optimization model solution wireless charging device that total charging time minimizes；If without solution, then perform step 2；Otherwise, then step 3 is performed；

Step 2, the change changing the charge power to sensing node according to the position of wireless charging device, reduce the scope residing for the position of wireless charging device, and again solve position and the number of wireless charging device in conjunction with described linear optimization model；

Step 3, it is judged that whether the number of wireless charging device exceedes predetermined number；It is then perform step 4；No, then end operation；

Step 4, adopts the mode merged, and reduces the number of wireless charging device to predetermined number。

2. a kind of method reducing Internet of Things sensing node charging delay according to claim 1, it is characterised in that described linear optimization model is as follows:

$\left\{\begin{array}{c}\begin{array}{cc}\min & T=\underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{t}_j\\ s.t.& \underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{P}_{ij}{t}_j\≥\mathrm{\δ},\end{array}\\ P_{ij}=\frac{\mathrm{\α}}{{(\sqrt{{(W_x^i-R_x^j)}^2+{(W_y^i-R_y^j)}^2}+\mathrm{\β})}^2},\\ i\∈\{1,2,3...N\},j\∈\{1,2,3...\mathrm{\∞}\}\end{array}\right.$

Wherein, described T is described total charging time, described t_jFor the charging interval of arbitrary wireless charging device, described P_ijFor the described arbitrary wireless charging device charge power to arbitrary sensing node, described δ is described threshold value, and described N is the sum of sensing node,For the position coordinates of described arbitrary sensing node,Position coordinates for described arbitrary wireless charging device, described α is the described arbitrary wireless charging device computational constant to the charge power of described arbitrary sensing node, and described β is the correction constant of described arbitrary wireless charging device and described arbitrary sensing node distance。

3. a kind of method reducing Internet of Things sensing node charging delay according to claim 1, it is characterised in that implementing of described step 2 comprises the steps:

Step 21, builds the least radius circle including all sensing nodes；

Step 22, in described least radius circle, with each sensing node for the center of circle, draw circular arc with different radii, and make wireless charging device, on the adjacent circular arc of arbitrary sensing node, the charge power of described arbitrary sensing node be differed preset value, obtain the overlapping region that charge power scope is identical；

Step 23, by the range shorter residing for the position of wireless charging device to described overlapping region, and again solves position and the number of wireless charging device in conjunction with described linear optimization model。

4. a kind of method reducing Internet of Things sensing node charging delay according to claim 3, it is characterised in that implementing of described step 21 comprises the steps:

Step 211, chooses not on the same line and be positioned at any four sensing node on border；

Step 212, chooses any three sensing nodes from described any four sensing node and draws circle, and make described circle comprise a remaining sensing node in described any four sensing node；

Step 213, chooses any one sensing node that is unselected and that be positioned at border, is combined into four sensing nodes with described any three sensing nodes；

Step 214, using described four sensing nodes as described any four sensing node, return circulation and perform step 212 and step 213, until all sensing nodes being positioned at border are all contained in a circle, end loop, then final drawn circle is described least radius circle。

5. a kind of method reducing Internet of Things sensing node charging delay according to claim 1, it is characterised in that implementing of described step 4 comprises the steps:

Step 41, the position according to wireless charging device, adopt K means Method that whole wireless charging devices are divided into K class；Wherein, described K is equal to described predetermined number；

Step 42, chooses the charge power position closest to the wireless charging device of this type of average charge power as the position of final wireless charging device from each apoplexy due to endogenous wind。

6. the system reducing Internet of Things sensing node charging delay, it is characterised in that include first solving module, second solving module, judge module and Fusion Module；

Described first solves module, it is used for the total charging time that all sensing nodes in Internet of Things are charged for object function, it is not less than threshold value for constraints with the energy that each sensing node is charged, builds position and the number of the linear optimization model solution wireless charging device that total charging time minimizes；If without solution, then second is driven to solve module work；Otherwise, then judge module work is driven；

Described second solves module, it is for the change changing the charge power to sensing node of the position according to wireless charging device, reduce the scope residing for the position of wireless charging device, and again solve position and the number of wireless charging device in conjunction with described linear optimization model；

Described judge module, it is for judging whether the number of wireless charging device exceedes predetermined number；It is then drive Fusion Module work；No, then end operation；

Described Fusion Module, the number of wireless charging device, for adopting the mode of fusion, is reduced to predetermined number by it。

7. a kind of system reducing Internet of Things sensing node charging delay according to claim 6, it is characterised in that described linear optimization model is as follows:

$\left\{\begin{array}{c}\begin{array}{cc}\min & T=\underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{t}_j\\ s.t.& \underset{j=1}{\overset{\mathrm{\∞}}{\mathrm{\Σ}}}{P}_{ij}{t}_j\≥\mathrm{\δ},\end{array}\\ P_{ij}=\frac{\mathrm{\α}}{{(\sqrt{{(W_x^i-R_x^j)}^2+{(W_y^i-R_y^j)}^2}+\mathrm{\β})}^2},\\ i\∈\{1,2,3...N\},j\∈\{1,2,3...\mathrm{\∞}\}\end{array}\right.$

Wherein, described T is described total charging time, described t_jFor the charging interval of arbitrary wireless charging device, described P_ijFor the described arbitrary wireless charging device charge power to arbitrary sensing node, described δ is described threshold value, and described N is the sum of sensing node,For the position coordinates of described arbitrary sensing node,Position coordinates for described arbitrary wireless charging device, described α is the described arbitrary wireless charging device computational constant to the charge power of described arbitrary sensing node, and described β is the correction constant of described arbitrary wireless charging device and described arbitrary sensing node distance。

8. a kind of system reducing Internet of Things sensing node charging delay according to claim 6, it is characterised in that described second solves that module includes least radius circle construction unit, overlapping region generates unit and solves unit；

Described least radius circle construction unit, it is for building the least radius circle including all sensing nodes；

Described overlapping region generates unit, it is in described least radius circle, with each sensing node for the center of circle, circular arc is drawn with different radii, and make wireless charging device, on the adjacent circular arc of arbitrary sensing node, the charge power of described arbitrary sensing node be differed preset value, obtain the overlapping region that charge power scope is identical；

Described solving unit, it is for by the range shorter residing for the position of wireless charging device to described overlapping region, and again solves position and the number of wireless charging device in conjunction with described linear optimization model。

9. a kind of system reducing Internet of Things sensing node charging delay according to claim 8, it is characterised in that described least radius circle construction unit include 4 choose subelement, four strokes and dots dumpling made of glutinous rice flour unit, 4 choose subelement again and circulation drives subelement；

Choosing subelement at described 4, it is for choosing not on the same line and be positioned at any four sensing node on border；

Described four strokes and dots dumpling made of glutinous rice flour unit, it draws circle for choosing any three sensing nodes from described any four sensing node, and makes described circle comprise a remaining sensing node in described any four sensing node；

Choosing subelement again at described 4, it, for choosing any one sensing node that is unselected and that be positioned at border, is combined into four sensing nodes with described any three sensing nodes；

Described circulation driver element, its for using described four sensing nodes as described any four sensing node, return circulation drive four strokes and dots dumpling made of glutinous rice flour unit and 4 choose again subelement work, until all sensing nodes being positioned at border are all contained in a circle, end loop, then final drawn circle is described least radius circle。

10. a kind of system reducing Internet of Things sensing node charging delay according to claim 6, it is characterised in that described Fusion Module includes taxon and integrated unit；

Described taxon, it is for the position according to wireless charging device, adopts K means Method that whole wireless charging devices are divided into K class；Wherein, described K is equal to described predetermined number；

Described integrated unit, it is for choosing the charge power position closest to the wireless charging device of this type of average charge power as the position of final wireless charging device from each apoplexy due to endogenous wind。