CN110278611A - A kind of resource allocation methods in the mobile edge calculations system of wireless power - Google Patents
A kind of resource allocation methods in the mobile edge calculations system of wireless power Download PDFInfo
- Publication number
- CN110278611A CN110278611A CN201910517089.1A CN201910517089A CN110278611A CN 110278611 A CN110278611 A CN 110278611A CN 201910517089 A CN201910517089 A CN 201910517089A CN 110278611 A CN110278611 A CN 110278611A
- Authority
- CN
- China
- Prior art keywords
- wireless device
- wireless
- energy
- mobile edge
- edge calculations
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000013468 resource allocation Methods 0.000 title claims abstract description 22
- 238000012546 transfer Methods 0.000 claims abstract description 34
- 230000005540 biological transmission Effects 0.000 claims abstract description 23
- 238000012512 characterization method Methods 0.000 claims abstract description 18
- 230000008569 process Effects 0.000 claims abstract description 8
- 238000005516 engineering process Methods 0.000 claims description 11
- 238000005265 energy consumption Methods 0.000 claims description 7
- 230000006870 function Effects 0.000 description 44
- 238000010586 diagram Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- YBMRDBCBODYGJE-UHFFFAOYSA-N germanium dioxide Chemical compound O=[Ge]=O YBMRDBCBODYGJE-UHFFFAOYSA-N 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 description 1
- RZVAJINKPMORJF-UHFFFAOYSA-N Acetaminophen Chemical compound CC(=O)NC1=CC=C(O)C=C1 RZVAJINKPMORJF-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 235000015170 shellfish Nutrition 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B5/00—Near-field transmission systems, e.g. inductive or capacitive transmission systems
- H04B5/70—Near-field transmission systems, e.g. inductive or capacitive transmission systems specially adapted for specific purposes
- H04B5/79—Near-field transmission systems, e.g. inductive or capacitive transmission systems specially adapted for specific purposes for data transfer in combination with power transfer
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/04—Wireless resource allocation
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The present invention provides the resource allocation methods in a kind of mobile edge calculations system of wireless power, can be realized resource allocation optimal in the mobile edge calculations system of wireless power.The described method includes: the mobile edge calculations system of building wireless power；It in wireless energy transfer and calculates in uninstall process, determines the differential equation of the energy state variation of characterization AP and wireless device；The revenue function of AP and wireless device is determined according to Stackelberg game；According to the differential equation of the energy state variation of determining characterization AP and wireless device, the revenue function of AP and wireless device, using Bellman dynamic programming principle, determine that the optimal transmission power of AP wireless energy transfer and wireless device are unloaded to the optimal proportion of the calculating task of AP.The present invention relates to internet of things field.
Description
Technical field
The present invention relates to internet of things field, the resource allocation in a kind of mobile edge calculations system of wireless power is particularly related to
Method.
Background technique
Internet of Things (IOT) is a kind of physical interconnection net, is perceived using various information Perception equipment from the real-time of environment
Data communicate between equipment and personnel.The application of Internet of Things can effectively improve social intelligence level, to be greatly promoted
People's lives.The challenge that networked devices face is limitation energy problem.The fast development of technology of Internet of things results in nothing
The exponential growth of line equipment.Most of wireless devices in Internet of Things are all finite energy, the limited equipment of computing resource, it
Unstable energy supply.How to reduce energy consumption, reduce calculating task, provides sustainable energy for wireless device, have become
For urgent problem to be solved in Internet of Things road for development.
Summary of the invention
The technical problem to be solved in the present invention is to provide the resource allocations in a kind of mobile edge calculations system of wireless power
Method, to solve the problems, such as in Internet of Things present in the prior art that wireless device is faced with that calculating task is heavy, finite energy.
In order to solve the above technical problems, the embodiment of the present invention provides the money in a kind of mobile edge calculations system of wireless power
Source distribution method, comprising:
Construct the mobile edge calculations system of wireless power, wherein the mobile edge calculations system of the wireless power includes: 1
It is described wireless that a AP and multiple wireless devices for being integrated with mobile edge calculations server, AP, which are based on wireless power transfer technology,
Equipment charge, wireless device utilize the energy that obtains from AP to execute and unloading calculating task, and AP is also used to execute from wirelessly setting
The calculating task of standby unloading, AP indicate access point；
It in wireless energy transfer and calculates in uninstall process, determines the micro- of the energy state variation of characterization AP and wireless device
Divide equation；
The revenue function of AP and wireless device is determined according to Stackelberg game；
According to the income of the differential equation of the energy state variation of determining characterization AP and wireless device, AP and wireless device
Function determines that the optimal transmission power of AP wireless energy transfer and wireless device are unloaded to using Bellman dynamic programming principle
The optimal proportion of the calculating task of AP.
Further, the differential equation of the energy state variation of AP is characterized are as follows:
Wherein, xap(t) indicate AP in the energy state of t moment；pg(t) the energy supply amount of power grid is indicated；pap(t) it indicates
The transimission power of AP wireless energy transfer；The number of N expression wireless device；ri(t) indicate that wireless device i is unloaded to the calculating of AP
The ratio of task；ε indicates the energy expenditure rate of the mobile edge calculations system of wireless power；μ indicates to calculate unloading bring unit
Energy consumption.
Further, the differential equation of the energy state variation of wireless device is characterized are as follows:
dxi(t)=[ηihipap(t)-μ[qi(t)-ri(t)]-εxi(t)]dt
Wherein, xi(t) indicate wireless device i in the energy state of t moment；hiIt indicates to swear from AP to the channel of wireless device i
Amount；ηiIndicate the efficiency of energy collection of wireless device i.
Further, the revenue function for determining AP according to Stackelberg game includes:
In the case where given interval, according to Stackelberg game, AP, which passes through, determines wireless energy transfer
Optimal transmission power, so that the income of AP is minimum:
Wherein, Jap(t) income of AP is indicated；The upper limit of T expression time interval；Indicate the energy threshold of AP；αap、βap、
γapRespectively indicate pap 2(t)、Weight coefficient.
Further, the revenue function for determining wireless device according to Stackelberg game includes:
In the case where given interval, according to Stackelberg game, wireless device i is unloaded to AP by determination
Calculating task optimal proportion so that the income of wireless device i is minimum:
Wherein, Ji(t) income of wireless device i is indicated；Indicate the energy threshold of wireless device i；αi、βi、γiTable respectively
Show [ηihipap(t)]2、μ2[qi(t)-ri(t)]2、Weight coefficient.
Further, according to the receipts of the differential equation of the energy state variation of determining characterization wireless device, wireless device
Beneficial function determines that wireless device is unloaded to the optimal proportion of the calculating task of AP and includes: using Bellman dynamic programming principle
According to the differential equation of the energy state variation of determining characterization wireless device, the revenue function of wireless device, build
The Hamiltonian function of vertical wireless device i；
The Hamiltonian function that wireless device i is solved using Bellman dynamic programming principle, is obtained wireless device and is unloaded to AP
Calculating task optimal proportion.
Further, the Hamiltonian function of the wireless device i of foundation indicates are as follows:
Wherein, Hi(t) Hamiltonian function of wireless device i, Λ are indicatedi(t) the energy state phase with wireless device i is indicated
Associated cost function；
Wireless device is unloaded to the optimal proportion r of the calculating task of APi *(t) it indicates are as follows:
Wherein,c1、c2All indicate constant parameter.
Further, according to the differential equation of the energy state variation of determining characterization AP, the revenue function of AP, shellfish is utilized
Germania dynamic programming principle determines that the optimal transmission power of AP wireless energy transfer includes:
According to the differential equation of the energy state variation of determining characterization AP, the revenue function of AP, the Hamilton of AP is established
Function；
The Hamiltonian function that AP is solved using Bellman dynamic programming principle, obtains the best transmission of AP wireless energy transfer
Power.
Further, the Hamiltonian function of the AP of foundation indicates are as follows:
Wherein, Hap(t) Hamiltonian function of AP, λ are indicated0(t) cost function associated with the energy state of AP is indicated；
λi(t) indicate that wireless device is unloaded to affecting parameters of the calculating task to AP transimission power of AP；
The optimal transmission power of AP wireless energy transferIt indicates are as follows:
Wherein,c3、c4All indicate constant
Parameter.
The advantageous effects of the above technical solutions of the present invention are as follows:
In above scheme, core technology of the unloading as mobile edge calculations is calculated, resource-constrained can wirelessly be set
What standby calculating task moved to Internet of Things network edge is integrated with single access point of mobile edge calculations server, to improve calculating matter
Amount reduces delay, to efficiently solve the limited computing resource problem of wireless device under environment of internet of things, and by wireless power
Transmission technology and mobile edge calculations technology combine, using access point and the variation of wireless device dynamic power to wireless power
The influence of edge calculations system is moved, and the revenue function of the AP and wireless device determined based on Stackelberg game,
Using Bellman dynamic programming principle, resource allocation optimal in the mobile edge calculations system of wireless power is obtained: AP is wireless energy
The optimal transmission power and wireless device of measuring transmission are unloaded to the optimal proportion of the calculating task of AP.
Detailed description of the invention
Fig. 1 is the process of the resource allocation methods in the mobile edge calculations system of wireless power provided in an embodiment of the present invention
Schematic diagram；
Fig. 2 is the structural schematic diagram of the mobile edge calculations system of wireless power provided in an embodiment of the present invention；
Fig. 3 is the solution procedure schematic diagram of the open loop optimal solution of wireless device provided in an embodiment of the present invention；
Fig. 4 is the solution procedure schematic diagram of the open loop optimal solution of AP provided in an embodiment of the present invention.
Specific embodiment
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and tool
Body embodiment is described in detail.
The present invention mentions aiming at the problem that wireless device is faced with heavy calculating task, finite energy in existing Internet of Things
For the resource allocation methods in a kind of mobile edge calculations system of wireless power.
As shown in Figure 1, the resource allocation methods in the mobile edge calculations system of wireless power provided in an embodiment of the present invention,
Include:
S101, the mobile edge calculations system of building wireless power, wherein the mobile edge calculations system packet of the wireless power
Include: 1 is integrated with the AP and multiple wireless devices of mobile edge calculations (MEC) server, and AP is based on wireless power transfer
((WPT)) technology is wireless device charging, and wireless device utilizes the energy obtained from AP to execute and unload calculating task,
AP is also used to execute the calculating task unloaded from wireless device, and AP indicates access point；
S102 in wireless energy transfer and is calculated in uninstall process, determines that the energy state of characterization AP and wireless device becomes
The differential equation of change；
S103 determines the revenue function of AP and wireless device according to Stackelberg (Stackelberg) game；
S104, according to the differential equation, AP and the wireless device of the energy state variation of determining characterization AP and wireless device
Revenue function determine the optimal transmission power and wireless device of AP wireless energy transfer using Bellman dynamic programming principle
It is unloaded to the optimal proportion of the calculating task of AP.
Resource allocation methods in the mobile edge calculations system of wireless power described in the embodiment of the present invention, calculate unloading and make
For the core technology of mobile edge calculations, the calculating task of resource-constrained wireless device can be moved to Internet of Things network edge
It is integrated with single access point of mobile edge calculations server, to improve calculating quality, delay is reduced, to efficiently solve Internet of Things
The limited computing resource problem of wireless device under net environment, and wireless power transfer technology and mobile edge calculations technology are combined
Get up, the influence using access point and the variation of wireless device dynamic power to the mobile edge calculations system of wireless power, Yi Jiji
Nothing is obtained using Bellman dynamic programming principle in the revenue function of AP and wireless device that Stackelberg game determines
Line is for resource allocation optimal in electric moveable edge calculations system: the optimal transmission power and wireless device of AP wireless energy transfer
It is unloaded to the optimal proportion of the calculating task of AP.
Resource allocation in the mobile edge calculations system of wireless power described in embodiment for a better understanding of the present invention
Method is described in detail, and can specifically include following steps:
S101, the mobile edge calculations system of building wireless power.
In the present embodiment, the mobile edge calculations system of the wireless power is by an access point (AP) and multiple wireless devices
Composition, as shown in Figure 2.AP is wireless power source, is wireless device charging based on wireless power transfer technology.In order to provide MEC clothes
Business, AP are also integrated with MEC server, can execute the calculating task unloaded from wireless device.Wireless device can obtain from AP
Energy execute and unload calculating task.The purpose of the present embodiment is: AP will find the best transmission of wireless energy transfer
Power, wireless device will determine the optimal proportion for being unloaded to the calculating task of AP.
In the present embodiment, since wireless device uses the energy obtained from AP to carry out calculating task processing and calculates unloading,
Therefore relationship between AP and wireless device can be abstracted as to stackelberg game, Stackelberg game is a neck
The game of the numerous followers of the person of leading, wherein AP is leader, and wireless device is follower.The function of AP decision wireless energy transfer
Rate grade, then wireless device is unloaded to the calculating task of AP according to the energy hole obtained from AP.In wireless energy transfer and meter
It calculates in uninstall process, since the energy of the mobile edge calculations system of wireless power is dynamic change, this will affect energy biography
Strategy that is defeated and calculating unloading, therefore can use access point and the variation of wireless device dynamic power to the mobile edge of wireless power
The influence of computing system, by dynamic game (that is: using dynamic power variation as system mode) and Stackelberg game knot
Altogether, the optimal solution of AP and wireless device are found.
S102 establishes dynamic game: in wireless energy transfer and calculating in uninstall process, determines characterization AP and wireless device
Energy state variation the differential equation.
In the present embodiment, the energy state of AP and wireless device can be obtained by the following differential equation:
dxi(t)=[ηihipap(t)-μ[qi(t)-ri(t)]-εxi(t)]dt (2)
Wherein, xap(t) indicate AP in the energy state of t moment；pg(t) the energy supply amount of power grid is indicated；pap(t) it indicates
The transimission power of AP wireless energy transfer；The number of N expression wireless device；ri(t) indicate that wireless device i is unloaded to the calculating of AP
The ratio of task；ε indicates the energy expenditure rate of the mobile edge calculations system of wireless power；xi(t) indicate wireless device i in t
The energy state at quarter；hiIt indicates from AP to the channel vector of wireless device i；ηiIndicate the efficiency of energy collection of wireless device i；μ table
Show calculating unloading bring specific energy consumption.
In the present embodiment, the energy consumption for calculating unloading can obtain μ r by the energy consumption of unloading each in MEC server positioni(t),
The energy consumption of the calculating task of wireless device processes μ [qi(t)-ri(t)] it indicates.
S103 determines the revenue function of AP and wireless device according to Stackelberg game.
In the present embodiment, in Stackelberg game, the revenue function of AP is related with following three parts:
1) income of wireless energy transfer, it is undertaken by wireless device, by variable pap(t) it controls；AP can pass through energy
The main reason for transmission earns a profit, this is wireless energy transfer.
2) energy cost needed for unloading calculating task from wireless device, this depends primarily on the ratio for calculating unloading；
AP should handle the calculating task from all wireless devices.
3) guarantee that energy state is not less than corresponding energy thresholdTrial cost, serviced by MEC server each
Kind wireless device provides the edge calculations service of least energy.
In the case where given interval, according to Stackelberg game, AP is by finding wireless energy transfer
Optimal transmission power, so that the income of AP is minimum:
Wherein, Jap(t) income of AP is indicated；The upper limit of T expression time interval；Indicate the energy threshold of AP；αap、βap、
γapRespectively indicate pap 2(t)、Weight coefficient.
In the present embodiment, in Stackelberg dynamic game, wireless device is considered as follower, it should undertake AP
Collection of energy, and the energy being collected into is used for local computing task.Since wireless device is the equipment of finite energy, should use up
Best endeavors make its energy not less than threshold valueTo deal with various unexpected calculating demands.
In the case where given interval, according to Stackelberg game, wireless device i is unloaded to AP by determination
Calculating task optimal proportion so that the income of wireless device i is minimum:
Wherein, Ji(t) income of wireless device i is indicated；Indicate the energy threshold of wireless device i；αi、βi、γiTable respectively
Show [ηihipap(t)]2、μ2[qi(t)-ri(t)]2、Weight coefficient.
S104, according to the differential equation, AP and the wireless device of the energy state variation of determining characterization AP and wireless device
Revenue function determine AP and wireless device open loop optimal solution, wherein open loop optimal solution using Bellman dynamic programming principle
The step of being divided into AP and the solution of wireless device two parts, respectively corresponding Fig. 3 and Fig. 4.
As shown in figure 3, Fig. 3 is the solution procedure of the open loop optimal solution of wireless device, specifically includes the following steps:
A1, the opened loop control solution of follower and leader for Stackelberg dynamic game, is being opened
Before the optimal solution of ring control, first have to provide wireless device following two definition:
1 is defined for wireless device i, if inequalityIt sets up, then calculates and unload
Carry ri *It (t) is optimal.
Wherein, ri *(t) indicate that wireless device is unloaded to the optimal proportion of the calculating task of AP,It is ri *(t) corresponding
Energy state track；
Define 2 one groups of control { ri *(t) } the balance side open loop Stackelberg of the problems in peer-to-peer (2) and (4) is constituted
Journey, there are a costate function Λi(t) meet following relationship:
Wherein, Hi(t) Hamiltonian function of wireless device i is indicated,Indicate Λi(t) to the first derivative of t, Λi(t)
It is a cost function associated with the energy state provided in formula (2).
In the present embodiment, using costate function, the revenue function of wireless device and energy state variation can be contacted
Get up, constructs Hamiltonian function Hi(t):
Optimal open loop solution in order to obtainIt needs to be solved in definition according to Bellman dynamic programming principle and provide
Hamiltonian function, obtain the optimal proportion r that the calculating task of AP is unloaded to from wireless device ii *(t):
Optimal proportion r in order to obtaini *(t) next explicit expression needs to find costate function Λi(t) table
Up to formula.
A2 determines the optimal energy state equation and its costate function Λ of wireless devicei(t):
Wherein,c1、c2All indicate constant parameter, c1、c2
It is to solve forConstant after ODE needs to be asked based on experience value.
A3, obtain the open loop optimal solution of each wireless device: wireless device i is unloaded to the best ratio of the calculating task of AP
Example.
In the present embodiment, formula (9) are substituted into formula (2), available:
It is available according to formula (7):
The quantity of parameter is reduced by introducing following replacement again:
It brings a ', b ', c ', d ' into formula (10), (11), obtains formula (15) (16):
As shown in figure 4, Fig. 4 is the solution procedure of the open loop optimal solution of AP, it can specifically include following steps:
B1 is unloaded to the optimal proportion r of the calculating task of AP in acquisition wireless devicei *(t) it after, finds AP wireless energy and passes
Defeated optimal transmission powerEqually, following two definition is provided to AP:
3 are defined for AP, if set up with lower inequality,For optimum value:
Define 4 one groups of controlsThe open loop Stackelberg balance of the problems in peer-to-peer (1) and (3) is constituted, and
AndIt isIt is corresponding can state trajectory, there are costate function lambdas0(t) and λi(t) meet following relationship:
Wherein, Hap(t) Hamiltonian function of AP is indicated；Indicate λ0(t) to the first derivative of t；Indicate λi(t)
To the first derivative of t；λ0It (t) is a cost function associated with the energy state provided in formula (1)；λi(t) indicate wireless
Device uninstallation to AP calculating task to the affecting parameters of AP transimission power.
In the present embodiment, using costate function, the revenue function of AP and energy state variation can be connected,
Construct the Hamiltonian function H of APap(t):
Optimal open loop solution in order to obtainIt needs to be solved in definition according to Bellman dynamic programming principle and provide
Hamiltonian function Hap(t), the optimal transmission power of AP wireless energy transfer is obtained
Optimal transmission power in order to obtainExplicit expression, next need to find costate function lambda0(t)
Expression formula.
B2 determines the optimal energy state equation and its costate function lambda of access point AP0(t)。
Wherein,c3、c4All indicate constant
Parameter, c3、c4It is to solve forConstant after ODE needs to be asked based on experience value.
B3 obtains AP wireless energy transfer optimal solution: the optimal transmission power of AP wireless energy transfer.
In the present embodiment, calculated according to formula (19)It is calculated according to formula (20)It is available:
It willIt brings (1) into, obtains:
The quantity of parameter is reduced by introducing following replacement again:
By a*、b*、c*、d*Bring formula (23), (24) into:
The above is a preferred embodiment of the present invention, it is noted that for those skilled in the art
For, without departing from the principles of the present invention, several improvements and modifications can also be made, these improvements and modifications
It should be regarded as protection scope of the present invention.
Claims (9)
1. the resource allocation methods in a kind of mobile edge calculations system of wireless power characterized by comprising
Construct the mobile edge calculations system of wireless power, wherein the mobile edge calculations system of the wireless power includes: 1 collection
Being based on wireless power transfer technology at the AP and multiple wireless devices of mobile edge calculations server, AP is the wireless device
Charging, wireless device utilize the energy obtained from AP to execute and unload calculating task, and AP is also used to execute and unload from wireless device
The calculating task of load, AP indicate access point；
It in wireless energy transfer and calculates in uninstall process, determines the differential side of the energy state variation of characterization AP and wireless device
Journey；
The revenue function of AP and wireless device is determined according to Stackelberg game；
According to the differential equation of the energy state variation of determining characterization AP and wireless device, the income letter of AP and wireless device
Number, using Bellman dynamic programming principle, determines that the optimal transmission power of AP wireless energy transfer and wireless device are unloaded to AP
Calculating task optimal proportion.
2. the resource allocation methods in the mobile edge calculations system of wireless power according to claim 1, which is characterized in that
Characterize the differential equation of the energy state variation of AP are as follows:
Wherein, xap(t) indicate AP in the energy state of t moment；pg(t) the energy supply amount of power grid is indicated；pap(t) indicate AP without
The transimission power of heat input transmission；The number of N expression wireless device；ri(t) indicate that wireless device i is unloaded to the calculating task of AP
Ratio；ε indicates the energy expenditure rate of the mobile edge calculations system of wireless power；μ indicates to calculate unloading bring unit energy
Consumption.
3. the resource allocation methods in the mobile edge calculations system of wireless power according to claim 2, which is characterized in that
Characterize the differential equation of the energy state variation of wireless device are as follows:
dxi(t)=[ηihipap(t)-μ[qi(t)-ri(t)]-εxi(t)]dt
Wherein, xi(t) indicate wireless device i in the energy state of t moment；hiIt indicates from AP to the channel vector of wireless device i；
ηiIndicate the efficiency of energy collection of wireless device i.
4. the resource allocation methods in the mobile edge calculations system of wireless power according to claim 3, which is characterized in that
The revenue function for determining AP according to Stackelberg game includes:
In the case where given interval, according to Stackelberg game, AP, which passes through, determines the best of wireless energy transfer
Transimission power, so that the income of AP is minimum:
Wherein, Jap(t) income of AP is indicated；The upper limit of T expression time interval；Indicate the energy threshold of AP；αap、βap、γap
Respectively indicate pap 2(t)、Weight coefficient.
5. the resource allocation methods in the mobile edge calculations system of wireless power according to claim 4, which is characterized in that
The revenue function for determining wireless device according to Stackelberg game includes:
In the case where given interval, according to Stackelberg game, wireless device i is unloaded to the meter of AP by determining
The optimal proportion of calculation task, so that the income of wireless device i is minimum:
Wherein, Ji(t) income of wireless device i is indicated；Indicate the energy threshold of wireless device i；αi、βi、γiIt respectively indicates
[ηihipap(t)]2、μ2[qi(t)-ri(t)]2、Weight coefficient.
6. the resource allocation methods in the mobile edge calculations system of wireless power according to claim 5, which is characterized in that
It is graceful using Bell according to the differential equation of the energy state variation of determining characterization wireless device, the revenue function of wireless device
Dynamic programming principle determines that wireless device is unloaded to the optimal proportion of the calculating task of AP and includes:
According to the differential equation of the energy state variation of determining characterization wireless device, the revenue function of wireless device, nothing is established
The Hamiltonian function of line equipment i；
The Hamiltonian function that wireless device i is solved using Bellman dynamic programming principle, obtains the meter that wireless device is unloaded to AP
The optimal proportion of calculation task.
7. the resource allocation methods in the mobile edge calculations system of wireless power according to claim 6, which is characterized in that
The Hamiltonian function of the wireless device i of foundation indicates are as follows:
Wherein, Hi(t) Hamiltonian function of wireless device i, Λ are indicatedi(t) indicate associated with the energy state of wireless device i
Cost function；
Wireless device is unloaded to the optimal proportion of the calculating task of APIt indicates are as follows:
Wherein,c1、c2All indicate constant parameter.
8. the resource allocation methods in the mobile edge calculations system of wireless power according to claim 7, which is characterized in that
According to the differential equation of the energy state variation of determining characterization AP, the revenue function of AP, using Bellman dynamic programming principle,
The optimal transmission power for determining AP wireless energy transfer includes:
According to the differential equation of the energy state variation of determining characterization AP, the revenue function of AP, the Hamiltonian function of AP is established；
The Hamiltonian function that AP is solved using Bellman dynamic programming principle, obtains the best transmission function of AP wireless energy transfer
Rate.
9. the resource allocation methods in the mobile edge calculations system of wireless power according to claim 8, which is characterized in that
The Hamiltonian function of the AP of foundation indicates are as follows:
Wherein, Hap(t) Hamiltonian function of AP, λ are indicated0(t) cost function associated with the energy state of AP is indicated；λi(t)
Indicate that wireless device is unloaded to affecting parameters of the calculating task to AP transimission power of AP；
The optimal transmission power of AP wireless energy transferIt indicates are as follows:
Wherein,C3, c4 indicate that constant is joined
Number.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910517089.1A CN110278611A (en) | 2019-06-14 | 2019-06-14 | A kind of resource allocation methods in the mobile edge calculations system of wireless power |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910517089.1A CN110278611A (en) | 2019-06-14 | 2019-06-14 | A kind of resource allocation methods in the mobile edge calculations system of wireless power |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110278611A true CN110278611A (en) | 2019-09-24 |
Family
ID=67960870
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910517089.1A Pending CN110278611A (en) | 2019-06-14 | 2019-06-14 | A kind of resource allocation methods in the mobile edge calculations system of wireless power |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110278611A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111464208A (en) * | 2020-03-09 | 2020-07-28 | 深圳大学 | Passive edge computing system based on spread spectrum communication, task unloading method and storage medium |
| CN111949409A (en) * | 2020-08-20 | 2020-11-17 | 全球能源互联网研究院有限公司 | Method and system for unloading calculation tasks in electric wireless heterogeneous network |
| CN112104693A (en) * | 2020-07-22 | 2020-12-18 | 北京邮电大学 | Task unloading method and device for non-uniform mobile edge computing network |
| CN112188560A (en) * | 2020-09-08 | 2021-01-05 | 北京科技大学 | Edge collaborative computing resource allocation method |
-
2019
- 2019-06-14 CN CN201910517089.1A patent/CN110278611A/en active Pending
Non-Patent Citations (1)
| Title |
|---|
| BINGJIE LIU等: "Resource Allocation in Wireless-Powered Mobile Edge Computing Systems for Internet of Things Applications", 《ELECTRONICS》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111464208A (en) * | 2020-03-09 | 2020-07-28 | 深圳大学 | Passive edge computing system based on spread spectrum communication, task unloading method and storage medium |
| CN112104693A (en) * | 2020-07-22 | 2020-12-18 | 北京邮电大学 | Task unloading method and device for non-uniform mobile edge computing network |
| CN111949409A (en) * | 2020-08-20 | 2020-11-17 | 全球能源互联网研究院有限公司 | Method and system for unloading calculation tasks in electric wireless heterogeneous network |
| CN111949409B (en) * | 2020-08-20 | 2024-03-29 | 全球能源互联网研究院有限公司 | Method and system for unloading computing task in power wireless heterogeneous network |
| CN112188560A (en) * | 2020-09-08 | 2021-01-05 | 北京科技大学 | Edge collaborative computing resource allocation method |
| CN112188560B (en) * | 2020-09-08 | 2021-11-30 | 北京科技大学 | Edge collaborative computing resource allocation method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110278611A (en) | A kind of resource allocation methods in the mobile edge calculations system of wireless power | |
| CN105225017B (en) | A kind of GROUP OF HYDROPOWER STATIONS Short-term Optimal Operation method of multi-Agent | |
| CN105574238B (en) | A kind of section real power control analysis of strategies method for the assessment of online stability margin | |
| CN109240818A (en) | Task discharging method based on user experience in a kind of edge calculations network | |
| CN113810233B (en) | Distributed computation unloading method based on computation network cooperation in random network | |
| CN108416465B (en) | Workflow optimization method in mobile cloud environment | |
| CN112367109A (en) | Incentive method for digital twin-driven federal learning in air-ground network | |
| CN109710336A (en) | The mobile edge calculations method for scheduling task of joint energy and delay optimization | |
| CN107450982A (en) | A kind of method for scheduling task based on system mode | |
| CN102664814A (en) | Grey-prediction-based adaptive dynamic resource allocation method for virtual network | |
| CN109829332A (en) | A kind of combined calculation discharging method and device based on energy collection technology | |
| Xiao et al. | System delay optimization for mobile edge computing | |
| CN109767117A (en) | The power distribution method of Joint Task scheduling in mobile edge calculations | |
| CN105760213B (en) | The early warning system and method for resources of virtual machine utilization rate under cloud environment | |
| CN106934497A (en) | Wisdom cell power consumption real-time predicting method and device based on deep learning | |
| CN109041130A (en) | Resource allocation methods based on mobile edge calculations | |
| CN110234127A (en) | A kind of mist network task discharging method based on SDN | |
| CN107092991A (en) | A kind of adaptive economic load dispatching distribution method of intelligent grid | |
| CN103268069A (en) | Adaptive prediction control method based on Hammerstein model | |
| CN108092322B (en) | AGC control method based on frequency modulation market environment | |
| CN109067583A (en) | A kind of resource prediction method and system based on edge calculations | |
| CN104219319A (en) | Method for distributed network flow self-organizing scheduling | |
| CN110109800A (en) | A kind of management method and device of server cluster system | |
| CN109787240A (en) | Distributed Power Flow optimization method and relevant device are coordinated in a kind of main distribution | |
| CN103178534A (en) | Calculating method for prevention and control strategy of small interference stabilization |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190924 |