阅读说明：本技术 Mec系统安全卸载方法、设备及mec系统 (MEC system safety unloading method, equipment and MEC system ) 是由 李保罡 武文静 项洪印 侯思祖 于 2021-08-24 设计创作，主要内容包括：本发明提供了一种MEC系统安全卸载方法、设备及MEC系统,该方法包括：建立用户终端在总卸载时间内的本地能耗模型和卸载能耗模型；根据本地能耗模型和卸载能耗模型,确定安全能耗目标函数和约束条件；获取设定的基站的通信参数、用户终端的运算能力参数以及总卸载时间作为输入参数；以目标函数的函数值最小为优化目标,根据优化算法、输入参数和约束条件进行优化,得到输出参数的目标值；输出参数的目标值用于对MEC系统进行安全卸载；其中输出参数包括IRS的反射相位、BS的接收波束赋形向量、AN向量、用户终端的发射功率、本地计算任务量。通过将IRS应用到MEC系统中,并优化IRS的反射相位,以增强用户终端的信号,减弱窃听者的接收信号,从而提高安全性。(The invention provides an MEC system safety unloading method, an MEC system safety unloading device and an MEC system, wherein the method comprises the following steps: establishing a local energy consumption model and an unloading energy consumption model of the user terminal in the total unloading time; determining a safe energy consumption objective function and a constraint condition according to the local energy consumption model and the unloading energy consumption model; acquiring set communication parameters of a base station, operational capability parameters of a user terminal and total unloading time as input parameters; optimizing according to an optimization algorithm, input parameters and constraint conditions by taking the minimum function value of the objective function as an optimization target to obtain a target value of the output parameters; the target value of the output parameter is used for safely unloading the MEC system; the output parameters comprise the reflection phase of the IRS, the receiving beam forming vector of the BS, the AN vector, the transmitting power of the user terminal and the local calculation task amount. By applying the IRS to the MEC system and optimizing the reflection phase of the IRS, the signal of the user terminal is enhanced, and the signal received by an eavesdropper is weakened, so that the security is improved.)

1. An MEC system safety unloading method, wherein an intelligent reflective surface IRS is deployed in the MEC system, the method comprising:

establishing a local energy consumption model and an unloading energy consumption model of the user terminal in the total unloading time;

determining a safe energy consumption objective function and a constraint condition according to the local energy consumption model and the unloading energy consumption model;

acquiring set communication parameters of a base station, operational capability parameters of a user terminal and total unloading time as input parameters;

optimizing according to an optimization algorithm, the input parameters and the constraint conditions by taking the minimum function value of the safe energy consumption objective function as an optimization target to obtain a target value of an output parameter; the target value of the output parameter is used for safely unloading the MEC system;

the output parameters comprise the reflection phase of the IRS, a receiving beam forming vector of the base station BS, AN artificial noise AN vector, the transmitting power of the user terminal and the local calculation task amount.

2. The MEC system secure offloading method of claim 1 wherein the optimization algorithm comprises a first algorithm and a second algorithm; the optimizing the minimum function value of the safety energy consumption objective function as an optimization objective according to an optimization algorithm, the input parameters and the constraint conditions to obtain the target value of the output parameters, and the optimizing the minimum function value of the safety energy consumption objective function comprises the following steps:

s1: optimizing the reflection phase, the received beam forming vector and the AN vector according to the constraint condition, the first algorithm, the initial value of the transmitting power and the initial value of the local task calculation amount to obtain AN updated reflection phase, AN updated received beam forming vector and AN updated AN vector;

s2: optimizing the transmitting power and the local task calculated amount according to the updated reflection phase, the updated received beam forming vector, the updated AN vector and a second algorithm to obtain updated transmitting power and updated local task calculated amount;

s3: judging whether the updated parameter value meets a preset condition or not according to the safe energy consumption objective function; if the preset condition is not met, jumping to S1, and iterating the updated parameter value; and if the preset conditions are met, taking the updated parameter values as the target values, wherein the updated parameter values comprise updated reflection phases, updated received beam forming vectors, updated AN vectors, updated transmitting power and updated local task calculation amount.

3. The MEC system secure offloading method of claim 2, wherein the first algorithm comprises a semi-deterministic planning algorithm and a semi-deterministic relaxation algorithm; the S1 includes:

converting the safe energy consumption objective function into a first concave function according to AN initial value of transmitting power, AN initial value of local task calculated quantity, AN initial value of a reflection phase and AN initial value of AN AN vector;

processing the constraint condition according to a semi-definite relaxation algorithm to obtain a convex constraint condition;

solving the first concave function according to the convex constraint condition and the semi-definite programming algorithm, and processing the obtained solution through a characteristic value decomposition algorithm or a Gaussian random algorithm to determine an updated received beam forming vector;

converting the safe energy consumption target function into a second concave function according to the updated receiving beam forming vector, the initial value of the transmitting power, the initial value of the local task calculation amount and the initial value of the reflection phase;

solving the second concave function according to the constraint condition and the semi-definite programming algorithm to obtain AN updated AN vector;

converting the safe energy consumption target function into a third concave function according to the updated received beam forming vector, the updated AN vector, the initial value of the transmitting power and the initial value of the local task calculation amount;

and solving the third concave function according to the convex constraint condition and the semi-definite programming algorithm, and processing the obtained solution through a characteristic value decomposition algorithm or a Gaussian random algorithm to obtain an updated reflection phase.

4. The MEC system secure offload method of claim 3 wherein the second algorithm is a Dinkelbach algorithm; the S2 includes:

determining updated transmitting power according to the constraint condition, the updated reflection phase, the updated received beam forming vector, the updated AN vector, the initial value of the local task calculation amount, the first preset parameter and the Dinkelbach algorithm;

and determining updated local task calculation amount according to the constraint condition, the updated reflection phase, the updated received beam forming vector, the updated AN vector and the updated transmitting power.

5. The MEC system safety unloading method of claim 2, wherein the determining whether the value of the output parameter meets a preset condition comprises:

calculating a function value of a safe energy consumption objective function corresponding to the output parameter obtained by each iteration after each iteration;

if the difference value between the function value of the current iteration and the function value of the last iteration does not exceed the preset fault-tolerant error, judging that the value of the output parameter meets the preset condition; otherwise, judging that the value of the output parameter does not meet the preset condition.

6. The MEC system security offload method of claim 1, wherein the expression of the security energy consumption objective function is:

the constraints include at least one of:

||q_k||²＝1

the expression of the local energy consumption model is as follows:

the expression of the unloading energy consumption model is as follows:

wherein E is a function value of the safety energy consumption objective function, K is a serial number of the user terminal, K is the total number of the user terminal, and xi_kIs the effective capacitance parameter of the kth subscriber terminal, c_kThe number of CPU cycles, l, required to calculate the 1bit task volume for the kth user terminal_kThe local task computation for the kth user terminal, T being the total offload time, p_kFor the transmission power of the kth user terminal, L_kFor the total task computation of the kth user terminal, B is the channel bandwidth, R_s，kFor the safe offload rate, p, of the kth user terminal_k ^maxAnd p_k ^minRespectively the maximum and minimum of the transmission power of the kth user terminal, l_k ^maxMaximum value of the calculation quantity for said local task, q_kFor said receive beamforming vector, W_kIs the AN vector, p_B ^maxIs the maximum transmission power of the base station, phi_k，nAmplitude and phase of the nth reflection unit of said IRS to the kth user, E_k ^locFor local energy consumption, E_k ^offTo unload energy consumption, t_kFor the unloading time, R, of the kth user terminal_s，kFrom q_k、W_k、φ_k，nAnd (4) determining.

7. The MEC system security offload method of any one of claims 1-6 wherein the communication parameters of the base station comprise at least one of: the maximum transmitting power of the base station, the variance of additive white Gaussian noise in the channel of the base station and the channel of an eavesdropper, and the parameters of a self-interference channel of the base station;

the calculation capability parameter of the user terminal comprises at least one of the following parameters: the local calculation task amount, the total task calculation amount, the effective capacitance parameter and the CPU cycle number;

before the minimum function value of the safe energy consumption objective function is taken as an optimization objective and the parameters of the safe energy consumption objective function are optimized according to an optimization algorithm, the input parameters and the constraint conditions, the method further comprises the following steps:

initializing the first preset parameter and the output parameter;

the unloading protocol of the user terminal is a TDMA protocol of equal time slot.

8. A base station comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor when executing the computer program implements the steps of the MEC system secure offloading method of any of the preceding claims 1 to 8.

9. An MEC system, comprising the base station of claim 8, an intelligent reflective surface IRS, and an IRS controller;

the IRS controller is used for adjusting the reflection phase of the IRS and controlling the working state of the IRS; the operating state includes a receiving state and a reflecting state.

10. MEC-system according to claim 9, wherein the base station BS in the MES-system transmits the artificial noise AN while receiving the user's offloaded data in full duplex mode.

Technical Field

The application belongs to the technical field of mobile edge computing, and particularly relates to an MEC system safety unloading method, an MEC system safety unloading device and an MEC system.

Background

Mobile Edge Computing (MEC) is considered as a promising technology in next generation wireless communication networks and internet of things, however, due to the broadcast characteristic of wireless transmission, users are easily attacked by malicious eavesdroppers when offloading Computing tasks to servers in the MEC system through a wireless channel, resulting in information leakage problem.

In the prior art, base station beamforming and NOMA cooperative interference technology is generally adopted to help a user terminal in an MEC system to achieve privacy security offloading, but the security requirements cannot be met, and the security is low.

Disclosure of Invention

In view of this, the invention provides a method and a device for safely uninstalling an MEC system, and aims to solve the problem of low security of the MEC system.

A first aspect of an embodiment of the present invention provides a method for safely unloading an MEC system, where an intelligent reflective surface IRS is deployed in the MEC system, and the method includes:

establishing a local energy consumption model and an unloading energy consumption model of the user terminal in the total unloading time;

determining a safe energy consumption objective function and a constraint condition according to the local energy consumption model and the unloading energy consumption model;

acquiring set communication parameters of a base station, operational capability parameters of a user terminal and total unloading time as input parameters;

optimizing according to an optimization algorithm, the input parameters and the constraint conditions by taking the minimum function value of the safe energy consumption objective function as an optimization target to obtain a target value of an output parameter; the target value of the output parameter is used for safely unloading the MEC system;

the output parameters comprise the reflection phase of the IRS, a receiving beam forming vector of the base station BS, AN artificial noise AN vector, the transmitting power of the user terminal and the local calculation task amount.

A second aspect of an embodiment of the present invention provides an MEC system security uninstalling apparatus, including:

the model establishing module is used for establishing a local energy consumption model and an unloading energy consumption model of the user terminal in the total unloading time;

the optimization preparation module is used for determining a safe energy consumption objective function and a constraint condition according to the local energy consumption model and the unloading energy consumption model;

the parameter input module is used for acquiring the set communication parameters of the base station, the operational capability parameters of the user terminal and the total unloading time as input parameters;

the parameter optimization module is used for optimizing according to an optimization algorithm, the input parameters and the constraint conditions by taking the minimum function value of the safe energy consumption objective function as an optimization target to obtain a target value of the output parameters; the target value of the output parameter is used for safely unloading the MEC system;

the output parameters comprise a reflection phase of AN intelligent reflection surface IRS, a receiving beam forming vector of a base station BS, AN artificial noise AN vector, the transmitting power of a user terminal and a local calculation task amount.

A third aspect of the embodiments of the present invention provides a base station, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the MEC system security offload method according to the first aspect.

A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, which stores a computer program, where the computer program, when executed by a processor, implements the steps of the MEC system security offload described in the first aspect above.

A fifth aspect of an embodiment of the present invention provides an MEC system, including the base station, the intelligent reflective surface IRS, and the IRS controller according to the third aspect; the IRS controller is used for adjusting the reflection phase of the IRS and controlling the working state of the IRS; the operating state includes a receiving state and a reflecting state.

According to the MEC system safety unloading method, the MEC system safety unloading equipment and the MEC system provided by the embodiment of the invention, a local energy consumption model and an unloading energy consumption model of a user terminal in total unloading time are established; determining a safe energy consumption objective function and a constraint condition according to the local energy consumption model and the unloading energy consumption model; acquiring set communication parameters of a base station, operational capability parameters of a user terminal and total unloading time as input parameters; the minimum function value of the safe energy consumption objective function is taken as an optimization target, and optimization is carried out according to an optimization algorithm, input parameters and constraint conditions to obtain a target value of an output parameter; the target value of the output parameter is used for safely unloading the MEC system; the output parameters comprise the reflection phase of the intelligent reflection surface IRS, the receiving beam forming vector of the base station BS, the artificial noise AN vector, the transmitting power of the user terminal and the local calculation task amount. The advantages of the IRS that the physical layer security can be improved are fully utilized, the method is applied to an MEC system, the reflection phase of the IRS is optimized, signals of a user terminal are enhanced, signals received by an eavesdropper are weakened, and therefore the security is improved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.

Fig. 1 is a schematic view of an application scenario of an MEC system according to an embodiment of the present invention;

fig. 2 is a flowchart illustrating an implementation of a security uninstalling method for an MEC system according to an embodiment of the present invention;

fig. 3 is a flowchart of an implementation of a security uninstalling method of an MEC system according to another embodiment of the present invention;

fig. 4 is a schematic structural diagram of a MEC system safety unloading device according to an embodiment of the present invention;

fig. 5 is a schematic diagram of a base station provided by an embodiment of the present invention;

fig. 6 is a schematic structural diagram of an MEC system according to an embodiment of the present invention.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

Mobile edge computing is considered as a promising technology in next generation wireless communication networks and Internet of Things (IoT), and can extend cloud computing services to the edge of the network, allowing a resource-limited terminal device to offload all or part of computation-intensive and delay-sensitive applications to an MEC server deployed on a Base Station (BS) or an Access Point (AP) for processing, thereby reducing the computation delay of the device, reducing the energy consumption of the device, prolonging the battery life of the device, and the like.

However, due to the broadcast characteristic of wireless transmission, when a user unloads a computing task to the MEC server through a wireless channel, the user is easily attacked by a malicious eavesdropper, and the information leakage problem is caused. The physical layer security technique is an effective method for improving the security of a wireless communication system, achieves the purpose of secure transmission by using the physical characteristics of a wireless channel, and has been widely studied in the wireless communication system. The total energy consumption of the MEC user can be minimized by jointly optimizing the calculation and communication resource allocation of the user, and the constraints of the safety unloading rate and the calculation delay are met. AN Artificial Noise (AN) method is also AN effective method for improving the security of the system, and AN signal is transmitted through a base station full duplex technology, so that the MEC user can be helped to realize privacy security unloading.

Intelligent Reflective Surfaces (IRS) are made up of a large number of low-cost passive reflective elements. In the prior art, the IRS is usually used to improve the physical layer security performance (such as MISO system) during downstream communication, or the IRS is only applied to the MEC system to improve the offloading performance of users. Technologies for improving the security of the MEC system include AN (integrated access network) technology, full-duplex technology, beam forming, and NOMA cooperative interference technology, which are relatively complex and difficult to implement, and additionally increase the energy consumption of the system.

The invention can change the incident signal according to the purpose of the receiving end by properly adjusting the amplitude and the phase of the IRS, thereby intelligently and controllably reconfiguring the wireless transmission environment, enhancing the strength of the received signal, reducing the transmitting power, improving the system energy and the spectrum efficiency, weakening the interference, improving the safety of a physical layer and the like. And the IRS is formed by passive reflection elements, so that the cost is low, the energy consumption is not additionally increased, and in addition, the base station also adopts the full-duplex technology to transmit AN while receiving signals, so that the safety of the MEC system is further improved.

The MEC system safety unloading method provided by the embodiment of the invention is applied to an MEC system with an IRS and is optimized. Fig. 1 is a schematic view of an application scenario of an MEC system according to an embodiment of the present invention. The MEC system provided by the embodiment of the invention can be applied to the scene without limitation. The scene comprises the following steps: base station 11, IRS12, IRS controller 13, at least one user terminal 14, eavesdropping device 15.

User terminal 14 may transmit data directly to base station 11 via the primary channel and may also transmit signals to base station 11 via the primary channel reflected via IRS 12. The eavesdropping device 15 can eavesdrop the data transmitted by the user terminal to the base station 11 from the user terminal 14 and the IRS, respectively, through the eavesdropping channel. The base station 11 may transmit AN to the interception device 15 directly through the artificial noise channel and may also transmit noise to the interception device 15 through the artificial noise channel reflected by the IRS. The IRS controller is used to control the reflection phase and amplitude of the IRS.

In this embodiment, the amplitude and phase of the IRS are appropriately adjusted, and the incident signal can be changed according to the purpose of the receiving end, so that the wireless transmission environment can be intelligently and controllably reconfigured to enhance the strength of the received signal, reduce the transmission power, improve the system energy and spectral efficiency, reduce interference, improve the physical layer security, and the like. And the IRS is composed of passive reflection elements, so that the cost is low, the additional energy consumption is not increased, and in addition, the base station adopts the full-duplex technology to transmit AN while receiving signals, so that the safety of the MEC system is further improved.

Fig. 2 is a flowchart of an implementation of a method for safely uninstalling an MEC system according to an embodiment of the present invention. Wherein, the MEC system is deployed with an intelligent reflective surface IRS, as shown in fig. 2, the method includes:

s201, establishing a local energy consumption model and an unloading energy consumption model of the user terminal in the total unloading time.

S202, determining a safe energy consumption objective function and constraint conditions according to the local energy consumption model and the unloading energy consumption model.

S203, acquiring the set communication parameters of the base station, the calculation capability parameters of the user terminal and the total unloading time as input parameters.

S204, optimizing according to an optimization algorithm, input parameters and constraint conditions by taking the minimum function value of the safe energy consumption objective function as an optimization target to obtain a target value of an output parameter; the target values of the output parameters are used for safe offloading of the MEC system.

The output parameters comprise the reflection phase of the IRS, a receiving beam forming vector of the base station BS, AN artificial noise AN vector, the transmitting power of the user terminal and the local calculation task amount.

In this embodiment, the number of the user terminals is K (K is greater than or equal to 1), the total offloading time is T, and the maximum offloading time of each user is T/K. The K users can unload the respective task amount in a TDMA mode. The local energy consumption model represents a relationship between local energy consumption and parameters of the MEC system. The unloading energy consumption model represents the relationship between the unloading energy consumption and the parameters of the MEC system. The optimization algorithm may be a gradient descent method, a particle swarm algorithm, an optimal iterative algorithm including a Semi-Definite Programming (SDP) algorithm, a Semi-Definite Relaxation (SDR) algorithm, a Dinkelbach method, and the like, which are not limited herein.

In the embodiment, a local energy consumption model and an unloading energy consumption model of the user terminal in the total unloading time are established; determining a safe energy consumption objective function and a constraint condition according to the local energy consumption model and the unloading energy consumption model; acquiring set communication parameters of a base station, operational capability parameters of a user terminal and total unloading time as input parameters; the minimum function value of the safe energy consumption objective function is taken as an optimization target, and optimization is carried out according to an optimization algorithm, input parameters and constraint conditions to obtain a target value of an output parameter; the target value of the output parameter is used for safely unloading the MEC system; the output parameters comprise the reflection phase of the intelligent reflection surface IRS, the receiving beam forming vector of the base station BS, the artificial noise AN vector, the transmitting power of the user terminal and the local calculation task amount. The advantages of the IRS that the physical layer security can be improved are fully utilized, the method is applied to an MEC system, the reflection phase of the IRS is optimized, signals of a user terminal are enhanced, signals received by an eavesdropper are weakened, and therefore the security is improved.

In some embodiments, the expression of the safe energy consumption objective function is:

constraints may include, but are not limited to, at least one of:

||q_k||²＝1 (4)

the expression of the local energy consumption model is as follows:

the expression of the unloading energy consumption model is as follows:

wherein E is a function value of the safety energy consumption objective function, K is a serial number of the user terminal, K is the total number of the user terminal, and xi_kIs the effective capacitance parameter of the kth subscriber terminal, c_kThe number of CPU cycles, l, required to calculate the 1bit task volume for the kth user terminal_kThe local task calculation amount for the kth user terminal, T is the total unloading time, p_kFor the transmission power of the kth user terminal, L_kFor the total task computation of the kth user terminal, B is the channel bandwidth, R_s，kFor the safe offload rate, p, of the kth user terminal_k ^maxAnd p_k ^minRespectively the maximum and minimum of the transmission power of the kth user terminal, l_k ^maxMaximum value of the calculation quantity, q, for the local task_kFor receiving beamforming vectors, W_kIs AN vector of, p_B ^maxIs the maximum transmission power of the base station, phi_k，nAmplitude and phase, E, of the nth reflection element of the IRS to the kth user_k ^locFor local energy consumption, E_k ^offTo unload energy consumption, t_kFor the unloading time, R, of the kth user terminal_s，kFrom q_k、W_k、φ_k，nAnd (4) determining.

In this embodiment, the expression of the security offload rate of the kth user terminal is:

wherein R is_b，kFor the offloading rate of the kth user terminal,and the wiretapping rate of the wiretapping equipment is I, I is the serial number of the wiretapping equipment, and the total number of the wiretapping equipment is I.

The user's offload rate and the eavesdropping rate of an eavesdropper can be determined by:

wherein, γ_b,kAndthe received Signal to Interference Noise Ratio (SINR) of the base station and the i-th eavesdropping device, respectively,andthe variance of Additive White Gaussian Noise (AWGN) in the BS and Eve channels, respectively. For the kth user terminal to base station channel parameters,respectively from the k-th user terminal to the i-th user terminalThe channel parameters of the eavesdropping device and the IRS, channel parameters of the IRS to the base station and the i-th eavesdropping device respectively, channel parameters from the base station to the ith eavesdropping device and IRS respectively,is the self-interference channel parameter of the base station, wherein N is the number of the reflection units in the IRS, M_tNumber of antennas, M, for base station transmission_rReceiving the number of antennas for the base station;

wherein phi_k＝diag(α_k,1exp(jφ_k,1),α_k,2exp(jφ_k,2),…,α_k,Nexp(jφ_k,N) Represents a diagonal matrix of IRS reflection coefficients, where α_k,n∈[0,1]. To maximize the received signal strength, α can be made_k,n1. All Channel State Information (CSI) is available. Also, since the effect of the reflection of the AN by the IRS on the base station is small compared to the self-interference of the base station, it can be ignored.

In this embodiment, optionally, the offload protocol of the ue is a TDMA protocol with equal time slots.

S202, specifically, the following steps are carried out:

obtaining a safe energy consumption model and an initial constraint condition according to the local energy consumption model and the unloading energy consumption model; wherein the content of the first and second substances,

the expression of the safe energy consumption model is as follows:

the initial constraints are:

||q_k||²＝1 (16)

where B is the channel bandwidth.

Since the user information is offloaded by the equal-time-slot TDMA protocol, K users are independent during the offloading process, and equation (13) in the initial constraint condition can be simplified as follows:

for the formula (12) in the initial condition, when "═ is taken, the value of the safe energy consumption model is minimum, so it is possible to set the value of the safe energy consumption model to be minimumAnd substituting the safety energy consumption model and the simplified initial constraint condition to obtain a safety energy consumption objective function and a constraint condition. Wherein the content of the first and second substances,

to simplify the calculation, one may assumeWherein v is_k,n＝exp(jφ_k,n)。Is provided with

Then h is_r,bΦ_kh_k,r+h_k,b＝f_k v_k。

Fig. 3 is a flowchart of an implementation of a method for safely uninstalling an MEC system according to another embodiment of the present invention. As shown in fig. 3, in some embodiments, the optimization algorithm includes a first algorithm and a second algorithm.

S204, comprising:

s1: optimizing a reflection phase, a received beam forming vector and AN AN vector according to a constraint condition, a first algorithm, AN initial value of transmitting power and AN initial value of local task calculation quantity to obtain AN updated reflection phase, AN updated received beam forming vector and AN updated AN vector;

s2: optimizing the transmitting power and the local task calculated amount according to the updated reflection phase, the updated received beam forming vector, the updated AN vector and a second algorithm to obtain updated transmitting power and updated local task calculated amount;

s3: judging whether the updated parameter value meets a preset condition or not according to the safe energy consumption objective function; if the preset condition is not met, jumping to S1, and iterating the updated parameter value; and if the preset conditions are met, taking the updated parameter values as target values, wherein the updated parameter values comprise updated reflection phases, updated received beam forming vectors, updated AN vectors, updated transmitting power and updated local task calculation amount.

In this embodiment, in S1, since the values of the transmit power and the local task computation amount are fixed, the optimization goal can be simplified to maximize the security offload rate of the ue, where the constraint conditions include equations (4) - (6). The safe offload rate expression at this time is:

wherein the content of the first and second substances,

in some embodiments, the first algorithm includes a semi-definite planning algorithm and a semi-definite relaxation algorithm.

S1 includes:

converting the safe energy consumption objective function into a first concave function according to the initial value of the transmitting power, the initial value of the local task calculated quantity, the initial value of the reflection phase and the initial value of the AN vector;

processing the constraint condition according to a semi-definite relaxation algorithm to obtain a convex constraint condition;

solving the first concave function according to the convex constraint condition and the semi-definite programming algorithm, processing the obtained solution through a characteristic value decomposition algorithm or a Gaussian random algorithm, and determining an updated received beam forming vector;

converting the safe energy consumption target function into a second concave function according to the updated receiving beam forming vector, the initial value of the transmitting power, the initial value of the local task calculation amount and the initial value of the reflection phase;

solving the second concave function according to the constraint condition and the semi-definite programming algorithm to obtain AN updated AN vector;

converting the safe energy consumption target function into a third concave function according to the updated received beam forming vector, the updated AN vector, the initial value of the transmitting power and the initial value of the local task calculation amount;

and solving the third concave function according to the convex constraint condition and the semi-definite programming algorithm, and processing the obtained solution through a characteristic value decomposition algorithm or a Gaussian random algorithm to obtain an updated reflection phase.

In this embodiment, the three variables of the reflection phase, the received beam forming vector and the AN vector are coupled, but when the values of two of the variables are fixed, the optimization problem is converted into a convex problem for solving one of the variables, and then the optimal solution of the variable is solved in AN iterative manner.

In this embodiment, the constraint condition is processed according to a semi-definite relaxation algorithm, and the convex constraint condition is obtained as follows: and (4) relaxing the constraint with the rank of 1 by adopting a semi-definite relaxation algorithm so as to convert the non-convex constraint in the constraint condition into the convex constraint. If all the constraints in the constraint conditions are convex constraints, the constraint conditions do not need to be processed by adopting a semi-definite relaxation algorithm.

In this embodiment, the principle of converting the safety energy consumption objective function into the first concave function, the second concave function, and the third concave function is the same, so the description will be given by taking the example of converting the safety energy consumption objective function into the second concave function, which is specifically as follows:

step I, defining a matrix Wherein Q is_k≥0，V_k≥0，rank(Q_k)＝1，rank(V_k)＝1。

In step ii, since the reflection phase and the receive beamforming vector are fixed, equation (20) can be simplified as:

wherein the content of the first and second substances,the constraint at this time is equation (5).

And step III, converting the safe energy consumption target function into a second concave function according to theorem 1. Wherein theorem 1 is: for the function y (μ) — μ x + ln μ +1,is provided withAnd the optimal solution is μ ═ 1/x. This argument gives an upper bound on y (μ), and is only reached when μ ═ 1/x.

Step III-1, the right first part of equation (21) can be simplified as follows according to theorem 1:

wherein the content of the first and second substances,

step III-2, the right second part of equation (21) can be simplified as follows according to theorem 1:

step III-3, neglecting the constant term 1/ln2, and applying the minimum maximum theory of Sion, the simplified formula of formula (21) can be obtained:

the constraint conditions are formula (5) and mu_w,k>0、Wherein the optimal values are:

in this embodiment, the principles of solving the first concave function, the second concave function, and the third concave function according to the convex constraint condition (or constraint condition) and the semi-definite programming algorithm are the same, so the example of solving the second concave function according to the constraint condition and the semi-definite programming algorithm is described as follows:

will be provided withSubstituted into equation (24) and a relaxation variable l is introduced_w,kObtaining:

R_s,k＝y_w,k(W_k,μ_w,k)-l_w,k (25)

the constraint conditions at this time are:

at this time, the optimization problem is converted into a convex problem for solving one variable, and the convex problem can be solved iteratively by using a semi-definite programming algorithm. Optionally, the solver may be a convex optimization software package CVX.

In this embodiment, the updated reflection phase, the updated receive beamforming vector, and the updated AN vector have symbols respectively as follows:

in some embodiments, the second algorithm is a Dinkelbach algorithm.

S2 includes:

determining updated transmitting power according to the constraint condition, the updated reflection phase, the updated received beam forming vector, the updated AN vector, the initial value of the local task calculation amount, the first preset parameter and the Dinkelbach algorithm;

and determining updated local task calculation amount according to the constraint condition, the updated reflection phase, the updated received beam forming vector, the updated AN vector and the updated transmitting power.

In this embodiment, three variables, i.e., the reflection phase, the receive beamforming vector, and the AN vector, are already solved in S1, and since the local task computation amount and the transmission power are coupled, the solution needs to be performed in the following manner:

step i, fixing the local task calculation amount, the first part on the right side of the equal sign of the safety energy consumption objective function in formula (1) is a fixed value, and the second part on the right side of the equal sign can be simplified as follows:

the constraint condition at this time is equation (2). The optimization problem is still a non-convex problem.

Step ii, further processing the formula (28) according to the first preset parameter and the Dinkelbach algorithm to obtain:

wherein the content of the first and second substances,

the optimal solution is obtained according to equation (29):

wherein the content of the first and second substances,for the updated transmission power,

Step iii, there are many situations in the updated transmit power, so the updated local task computation amount is solved through the following two situations:

(1)or

At this time, p_kAnd l_kAre independent of each other, so that it can be easily solved:

thus:

wherein the content of the first and second substances,the amount of computation is for the updated local task.

(2)

At this time, the process of the present invention,is equivalent toAndtherefore, the safety energy consumption objective function of formula (1) can be simplified as follows:

the constraint at this time is equation (3).

Order to

ByThe optimization problem at this time can be found to be a convex problem,as extreme points, from this can be derived:

wherein l₀To solve by dichotomyTo obtain the root.

In some embodiments, determining whether the value of the output parameter satisfies a predetermined condition includes:

calculating a function value of a safe energy consumption objective function corresponding to the output parameter obtained by each iteration after each iteration;

if the difference value between the function value of the current iteration and the function value of the last iteration does not exceed the preset fault-tolerant error, judging that the value of the output parameter meets the preset condition; otherwise, judging that the value of the output parameter does not meet the preset condition.

In this embodiment, the expression of the preset condition is as follows:

||E_k(it)-E_k(it-1)||≤ε (35)

in some embodiments, the communication parameters of the base station may include, but are not limited to, at least one of: maximum transmitting power of a base station, variance of additive white Gaussian noise in a base station channel and an eavesdropper channel, and base station self-interference channel parameters;

the calculation capability parameter of the user terminal may include, but is not limited to, at least one of the following: local calculation task amount, total task calculation amount, effective capacitance parameter and CPU periodicity.

In some embodiments, before optimizing the parameters of the safety energy consumption objective function according to the optimization algorithm, the input parameters, and the constraint conditions, with the minimum function value of the safety energy consumption objective function as the optimization objective, the method further includes:

initializing the first preset parameter and the output parameter.

The method for safely uninstalling the MEC system is described below by using an implementation example, but the implementation example is not limited thereto.

In this embodiment, the method for safely unloading the MEC system includes the following steps:

step 1, establishing a local energy consumption model and an unloading energy consumption model of a user terminal in total unloading time.

And 2, determining a safe energy consumption objective function and a constraint condition according to the local energy consumption model and the unloading energy consumption model.

And 3, initializing a first preset parameter eta and an output parameter.

Step 4, obtaining input parameters:

and step 5, it is 1.

And step 6, fixing other parameters and updating the received beam forming vector.

And 7, fixing other parameters and updating the AN vector.

And 8, fixing other parameters and updating the reflection phase.

And 9, fixing other parameters and updating the transmitting power.

And step 10, fixing other parameters and updating the local task calculation amount.

And 11, updating the first preset parameter.

Step 12, judging whether the updated parameter value meets a preset condition according to the safe energy consumption objective function: i E_k(it)-E_kAnd (it-1) is less than or equal to epsilon. If the preset condition is not met, the unit it is equal to the unit it +1 and the step 5 is skipped; and if the preset condition is met, jumping to the step 13.

Step 13, using the updated parameter value as the target value of the output parameter

The invention has the beneficial effects that:

(1) the security offload performance of the MEC system is improved by utilizing the IRS, and meanwhile, the FD-BS (Full duplex base station) is considered to transmit the AN while receiving signals, so that the security offload performance of the MEC system with a plurality of eavesdropping devices is improved.

(2) Energy consumption is an important performance index of the MEC system, an optimization problem with minimum user safety energy consumption is established for the MEC system, and an iterative optimization algorithm is provided to solve the problem, so that the safety energy consumption of the system can be effectively reduced.

(3) Through numerical simulation, it can be derived that: the number of the reflection units of the IRS is properly increased, and the system performance can be well improved by deploying the IRS at a position close to a transmitting end or a receiving end; in addition, the smaller the self-interference coefficient of the FD-BS is, the larger the maximum transmitting power is, which is more beneficial to improving the performance of the system.

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

Fig. 4 is a schematic structural diagram of a MEC system safety unloading device according to an embodiment of the present invention. Wherein, dispose intelligent reflection surface IRS in the MEC system, as shown in fig. 4, MEC system safety uninstallation device 4 includes:

and a model establishing module 410, configured to establish a local energy consumption model and an offload energy consumption model of the user terminal within the total offload time.

And the optimization preparation module 420 is configured to determine a safe energy consumption objective function and a constraint condition according to the local energy consumption model and the offload energy consumption model.

The parameter input module 430 is configured to obtain the set communication parameters of the base station, the calculation capability parameters of the user terminal, and the total offloading time as input parameters.

The parameter optimization module 440 is configured to optimize according to an optimization algorithm, an input parameter, and a constraint condition, with a minimum function value of the safety energy consumption objective function as an optimization target, to obtain a target value of an output parameter; the target values of the output parameters are used for safe offloading of the MEC system.

The output parameters comprise the reflection phase of the IRS, a receiving beam forming vector of the base station BS, AN artificial noise AN vector, the transmitting power of the user terminal and the local calculation task amount.

Optionally, the optimization algorithm includes a first algorithm and a second algorithm.

A parameter optimization module 440 to:

s1: optimizing a reflection phase, a received beam forming vector and AN AN vector according to a constraint condition, a first algorithm, AN initial value of transmitting power and AN initial value of local task calculation quantity to obtain AN updated reflection phase, AN updated received beam forming vector and AN updated AN vector;

s2: optimizing the transmitting power and the local task calculated amount according to the updated reflection phase, the updated received beam forming vector, the updated AN vector and a second algorithm to obtain updated transmitting power and updated local task calculated amount;

s3: judging whether the updated parameter value meets a preset condition or not according to the safe energy consumption objective function; if the preset condition is not met, jumping to S1, and iterating the updated parameter value; and if the preset conditions are met, taking the updated parameter values as target values, wherein the updated parameter values comprise updated reflection phases, updated received beam forming vectors, updated AN vectors, updated transmitting power and updated local task calculation amount.

Optionally, the first algorithm includes a semi-definite planning algorithm and a semi-definite relaxation algorithm.

A parameter optimization module 440 to:

converting the safe energy consumption objective function into a first concave function according to the initial value of the transmitting power, the initial value of the local task calculated quantity, the initial value of the reflection phase and the initial value of the AN vector;

processing the constraint condition according to a semi-definite relaxation algorithm to obtain a convex constraint condition;

solving the first concave function according to the convex constraint condition and the semi-definite programming algorithm, processing the obtained solution through a characteristic value decomposition algorithm or a Gaussian random algorithm, and determining an updated received beam forming vector;

converting the safe energy consumption target function into a second concave function according to the updated receiving beam forming vector, the initial value of the transmitting power, the initial value of the local task calculation amount and the initial value of the reflection phase;

solving the second concave function according to the constraint condition and the semi-definite programming algorithm to obtain AN updated AN vector;

converting the safe energy consumption target function into a third concave function according to the updated received beam forming vector, the updated AN vector, the initial value of the transmitting power and the initial value of the local task calculation amount;

and solving the third concave function according to the convex constraint condition and the semi-definite programming algorithm, and processing the obtained solution through a characteristic value decomposition algorithm or a Gaussian random algorithm to obtain an updated reflection phase.

Optionally, the second algorithm is a Dinkelbach algorithm.

A parameter optimization module 440 to:

determining updated transmitting power according to the constraint condition, the updated reflection phase, the updated received beam forming vector, the updated AN vector, the initial value of the local task calculation amount, the first preset parameter and the Dinkelbach algorithm;

and determining updated local task calculation amount according to the constraint condition, the updated reflection phase, the updated received beam forming vector, the updated AN vector and the updated transmitting power.

Optionally, the parameter optimization module 440 is configured to:

calculating a function value of a safe energy consumption objective function corresponding to the output parameter obtained by each iteration after each iteration;

if the difference value between the function value of the current iteration and the function value of the last iteration does not exceed the preset fault-tolerant error, judging that the value of the output parameter meets the preset condition; otherwise, judging that the value of the output parameter does not meet the preset condition.

Optionally, the expression of the safe energy consumption objective function is as follows:

constraints may include, but are not limited to, at least one of:

||q_k||²＝1

the expression of the local energy consumption model is as follows:

the expression of the unloading energy consumption model is as follows:

wherein E is a function value of the safety energy consumption objective function, K is a serial number of the user terminal, K is the total number of the user terminal, and xi_kIs the effective capacitance parameter of the kth subscriber terminal, c_kThe number of CPU cycles, l, required to calculate the 1bit task volume for the kth user terminal_kThe local task calculation amount for the kth user terminal, T is the total unloading time, p_kFor the transmission power of the kth user terminal, L_kFor the total task computation of the kth user terminal, B is the channel bandwidth, R_s，kFor the safe offload rate, p, of the kth user terminal_k ^maxAnd p_k ^minRespectively the maximum and minimum of the transmission power of the kth user terminal, l_k ^maxMaximizing computation of volume for local tasksValue q_kFor receiving beamforming vectors, W_kIs AN vector of, p_B ^maxIs the maximum transmission power of the base station, phi_k，nAmplitude and phase reflection phase shift matrix constraints for the kth user for the nth reflection element of the IRS, E_k ^locFor local energy consumption, E_k ^offTo unload energy consumption, t_kFor the unloading time, R, of the kth user terminal_s，kFrom q_k、W_k、φ_k，nAnd (4) determining.

Optionally, the communication parameters of the base station may include, but are not limited to, at least one of the following: maximum transmitting power of a base station, variance of additive white Gaussian noise in a base station channel and an eavesdropper channel, and base station self-interference channel parameters;

the calculation capability parameter of the user terminal may include, but is not limited to, at least one of the following: local calculation task amount, total task calculation amount, effective capacitance parameter and CPU periodicity.

Optionally, before the minimum function value of the safety energy consumption objective function is taken as an optimization objective and the parameters of the safety energy consumption objective function are optimized according to the optimization algorithm, the input parameters and the constraint conditions, the method further includes:

initializing the first preset parameter and the output parameter.

Optionally, the offload protocol of the ue is a TDMA protocol with equal time slots.

The MEC system security uninstalling apparatus provided in this embodiment may be used to execute the method embodiments described above, and the implementation principle and technical effect are similar, which are not described herein again.

Fig. 5 is a schematic diagram of a base station according to an embodiment of the present invention. As shown in fig. 5, an embodiment of the present invention provides a base station 5, where the base station 5 of the embodiment includes: a processor 50, a memory 51 and a computer program 52 stored in the memory 51 and executable on the processor 50. The processor 50 executes the computer program 52 to implement the steps in the above-described embodiment of the MEC system security uninstalling method, such as the steps 201 to 204 shown in fig. 2. Alternatively, the processor 50, when executing the computer program 52, implements the functions of the modules/units in the above-described device embodiments, such as the functions of the modules 410 to 440 shown in fig. 4.

Illustratively, the computer program 52 may be divided into one or more modules/units, which are stored in the memory 51 and executed by the processor 50 to carry out the invention. One or more of the modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 52 in the base station 5.

The base station 5 may be a 4G/5G mobile communication base station, etc., and the base station 5 may include a transceiver for transmitting and receiving signals and a computing device having functions of monitoring, calculating, controlling, etc., where the computing device may be a desktop computer, a notebook computer, a palm computer, a cloud server, etc., and is not limited herein. The terminal may include, but is not limited to, a processor 50, a memory 51. It will be appreciated by those skilled in the art that fig. 5 is only an example of a base station 5 and does not constitute a limitation of the base station 5 and may include more or less components than shown, or combine certain components, or different components, e.g. the terminal may also include input output devices, network access devices, buses, etc.

The Processor 50 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 51 may be an internal storage unit of the base station 5, such as a hard disk or a memory of the base station 5. The memory 51 may also be an external storage device of the base station 5, such as a plug-in hard disk provided on the base station 5, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the memory 51 may also include both an internal storage unit of the base station 5 and an external storage device. The memory 51 is used for storing computer programs and other programs and data required by the terminal. The memory 51 may also be used to temporarily store data that has been output or is to be output.

An embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps in the embodiment of the MEC system security offload method are implemented.

The computer-readable storage medium stores a computer program 52, the computer program 52 includes program instructions, and when the program instructions are executed by the processor 50, all or part of the processes in the method according to the above embodiments may be implemented by the computer program 52 instructing related hardware, and the computer program 52 may be stored in a computer-readable storage medium, and when the computer program 52 is executed by the processor 50, the steps of the above embodiments of the method may be implemented. The computer program 52 comprises, inter alia, computer program code, which may be in the form of source code, object code, an executable file or some intermediate form. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like. It should be noted that the computer readable medium may include any suitable increase or decrease as required by legislation and patent practice in the jurisdiction, for example, in some jurisdictions, computer readable media may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.

The computer readable storage medium may be an internal storage unit of the terminal of any of the foregoing embodiments, for example, a hard disk or a memory of the terminal. The computer readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk provided on the terminal, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the computer-readable storage medium may also include both an internal storage unit and an external storage device of the terminal. The computer-readable storage medium is used for storing a computer program and other programs and data required by the terminal. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

Fig. 6 is a schematic structural diagram of an MEC system according to an embodiment of the present invention. As shown in fig. 6, the MEC system includes a base station 61, an intelligent reflective surface IRS62, and an IRS controller 63; the IRS controller is used for adjusting the reflection phase of the IRS and controlling the working state of the IRS; the operating state includes a receiving state and a reflecting state.

In this embodiment, the IRS not only assists the user in improving the unloading performance and reducing the energy consumption, but also weakens the received signal strength of the eavesdropper and improves the system security.

In some embodiments, base stations 61 in the MES system transmit the artificial noise AN in full duplex mode while receiving the user's offloaded data.

In this embodiment, the base station 61 is configured to obtain an input parameter; wherein, the input parameter may be preset, such as the maximum transmitting power of the base station; or may be collected in real time, such as the channel parameters of each channel in the embodiment shown in fig. 1; and is not limited herein.

The base station 61 is further configured to optimize the output parameter according to the input parameter and the MEC system security offloading method according to any of the embodiments described above, so as to obtain a target value of the output parameter. The output parameters include the reflection phase of the IRS62, the receive beamforming vector of the base station BS, the artificial noise AN vector, the transmit power of the user terminal, and the local computation workload.

The base station 61 is further configured to adjust the receive beamforming vector and the artificial noise AN vector of the base station BS to their target values, control the IRS through the IRS controller 63 to adjust the reflection phase of the IRS62 to its target value, and send the target values of the transmit power of the user terminal and the local computation task amount to the user terminal, so that the user terminal performs security offloading according to the target values.

In this embodiment, the reception state is used to estimate channel state information, and the reflection state is used to transmit data.

In this embodiment, since the input parameters acquired in real time are constantly changed, after each acquisition, the output parameters need to be optimized according to the new input parameters to obtain the target values of the new output parameters, so that the output parameters are adjusted in real time according to the real-time changes (changes of the channel) of the input parameters.

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules, so as to perform all or part of the functions described above. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal and method may be implemented in other ways. For example, the above-described apparatus/terminal embodiments are merely illustrative, and for example, a module or a unit may be divided into only one logical function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method according to the embodiments of the present invention may also be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of the embodiments of the method. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like. It should be noted that the computer readable medium may include any suitable increase or decrease as required by legislation and patent practice in the jurisdiction, for example, in some jurisdictions, computer readable media may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.

The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.