CN114706731A - A method for real-time dynamic monitoring of intelligent services - Google Patents

Abstract

The present application belongs to the field of service computing, and discloses a method for real-time dynamic monitoring of intelligent services. The method includes, according to user requirements, presetting multiple constraint monitoring targets on the intelligent service, and converting the monitoring targets into sequential logic formulas; The Riemann sum operator constructs a positive and negative biased Riemann sum calculation method, and generates a new quantitative satisfaction calculation method for signal timing logic; obtains the timing signal corresponding to the intelligent service monitoring target, and performs real-time processing operations to achieve Real-time dynamic monitoring of multiple constraints of intelligent services. Compared with the existing signal timing logic, the invention calculates and analyzes the positive and negative timing signals in the timing signal respectively, and proposes a correct, complete and distinguishable quantitative satisfaction degree; compared with the existing intelligent service monitoring method, The invention proposes a real-time, efficient, and contractual monitoring method based on sequential logic, which improves the monitoring efficiency.

Description

A method for real-time dynamic monitoring of intelligent services

technical field

The present application relates to the technical field of service computing, and in particular, to a method for real-time dynamic monitoring of intelligent services.

Background technique

The service-oriented Internet of Things is being studied by more and more experts and scholars, abstracting the underlying target devices into intelligent services, and then meeting the specific needs of users through intelligent service combination, recommendation, and adaptation. For example, in a smart hotel, different smart devices such as robots, voice assistants, curtains, and TVs are abstracted into smart services. By monitoring the service satisfaction of each smart device, it is judged whether the hotel meets the needs of users.

In the prior art, active or passive monitoring algorithms for intelligent services are usually used to judge whether the intelligent services meet user needs online or offline. However, these existing methods do not consider the quantitative monitoring of intelligent service satisfaction under the constraints of temporal logic operators within a period of time, and lack formal semantic specifications and quantitative measurement methods of satisfaction.

Real-time dynamic monitoring of intelligent services based on signal timing logic is an effective and feasible solution. However, the signal sequential logic has the problem of indistinguishability that the signal value is very different, and the satisfaction degree may not be different. Existing research work has noticed this defect, starting with the mean operator and smoothing operator to enhance the signal timing logic. However, these works have the problem of unrobustness caused by the signal values that do not satisfy the constraints being covered by the signal values that satisfy the constraints, such as the phenomenon that the mean value is positive and cannot represent the phenomenon that all signal values are positive. Aiming at the imperfection of the signal value being unrobust, recent research work defines the quantitative semantics of the signal values that satisfy the constraints and the parts that do not satisfy the constraints, such as averaging or smoothing only the part of the signal values that satisfy the constraints. However, these works are based on the assumption of fixed sampling rate, and are difficult to apply to the problem that the signal sampling rate is difficult to be fixed when the dynamic changes.

In order to support the scene of non-uniform signal sampling rate, the present invention constructs the Riemann sum operator under positive and negative bias based on the Riemann sum operator, and extends the time operator of the signal timing logic, so as to realize the robust timing, signal distinguishability, Real-time dynamic monitoring of dynamically applicable intelligent services.

SUMMARY OF THE INVENTION

The purpose of this application is to provide a method for real-time dynamic monitoring of intelligent services, which can improve monitoring efficiency when monitoring the constraint satisfaction degree of intelligent services.

On the one hand, a method for real-time dynamic monitoring of an intelligent service is provided, including: presetting a monitoring target of at least one constraint of the intelligent service according to user requirements, and converting the monitoring target into a sequential logic formula;

Based on the Riemann sum operator, construct a positive and negative bias Riemann sum calculation method, and generate a new quantitative satisfaction calculation method for signal sequential logic;

Obtain the time series signal corresponding to the monitoring target, and based on the new signal time series logic quantitative satisfaction calculation method, calculate the satisfaction degree of each constraint of the intelligent service in real time, and realize the real-time dynamic monitoring of the intelligent service.

In the above implementation process, by constructing a positive and negative bias Riemann sum calculation method, the time series signal is calculated and analyzed, and a correct, complete and distinguishable quantitative satisfaction degree is proposed; compared with the existing intelligent service monitoring methods , the invention proposes a real-time, efficient, and contractual monitoring method based on sequential logic, which improves the monitoring efficiency.

In one embodiment, the smart service constraint includes at least one of the following attributes: a space attribute, a time attribute, an energy consumption attribute, and a resource limitation attribute.

In one embodiment, based on the Riemann sum operator, a positive and negative biased Riemann sum calculation method is constructed to generate a new method for calculating the quantitative satisfaction degree of signal sequential logic, including:

Based on the constructed Riemann sum calculation method of positive and negative biases, a new formal semantics of temporal logic for signals is constructed.

In the above implementation process, the real-time dynamic monitoring of multiple constraints of the intelligent service can be realized more accurately and efficiently by formalizing the semantics according to the new timing logic of the construction signal during the subsequent monitoring of the intelligent service.

In one embodiment, the time series signal corresponding to the monitoring target is obtained, and based on the novel signal time series logic quantitative satisfaction degree calculation method, the satisfaction degree of each constraint of the intelligent service is calculated in real time, and the real-time dynamic monitoring of the intelligent service is realized, including:

Obtain the timing signal corresponding to the monitoring target and its signal interval;

Based on the formal semantics of the constructed new sequential logic, the logic formula of the monitoring target is processed under positive and negative bias;

Real-time calculation of the degree of satisfaction of various constraints of intelligent services to realize real-time dynamic monitoring of intelligent services.

In the above implementation process, based on the formal semantics of a new type of sequential logic, real-time, efficient and accurate real-time dynamic monitoring of intelligent services can be realized.

In one aspect, a device for real-time dynamic monitoring of intelligent services is provided, including:

Conversion unit: It is used to preset a monitoring target with at least one constraint of the intelligent service according to user needs, and convert the monitoring target into a sequential logic formula;

Generation unit: It is used to construct a positive and negative biased Riemann sum calculation method based on the Riemann sum operator, and generate a new quantitative satisfaction calculation method for signal sequential logic;

Acquisition unit: used to acquire the timing signal corresponding to the monitoring target;

Processing unit: It is used to calculate the satisfaction degree of various constraints of the intelligent service in real time based on the quantitative satisfaction calculation method of the new signal timing logic, and realize the real-time dynamic monitoring of the intelligent service.

In one embodiment, the smart service constraint includes at least one of the following attributes: a space attribute, a time attribute, an energy consumption attribute, and a resource limitation attribute.

In one embodiment, the generating unit is used to:

Based on the constructed Riemann sum calculation method of positive and negative biases, a new formal semantics of temporal logic for signals is constructed.

In one embodiment, the acquisition unit is used to:

Obtain the timing signal corresponding to the monitoring target and its signal interval.

In one embodiment, the processing unit is used to:

Based on the formal semantics of the constructed new sequential logic, the logic formula of the monitoring target is processed under positive and negative bias;

Real-time calculation of the degree of satisfaction of various constraints of intelligent services to realize real-time dynamic monitoring of intelligent services.

On the one hand, an electronic device is provided, including a processor and a memory, the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, run each of the above-mentioned intelligent services dynamically monitored in real time. steps of a method provided in an alternative implementation.

On the one hand, a readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method provided in the various optional implementation manners of real-time dynamic monitoring of any of the above-mentioned intelligent services are executed when the computer program is executed. .

In one aspect, a computer program product is provided. When the computer program product runs on a computer, the computer program product enables the computer to execute the steps of the method provided in any of the foregoing various optional implementations of real-time dynamic monitoring of intelligent services.

In the embodiment of the present application, according to user requirements, a number of constraint monitoring targets on the intelligent service are preset, and the monitoring targets are converted into sequential logic formulas; based on the Riemann sum operator, a positive and negative biased Riemann sum calculation method is constructed , generate a new quantitative satisfaction calculation method of signal timing logic; obtain the timing signal corresponding to the monitoring target of intelligent service, and perform real-time processing operation to realize real-time dynamic monitoring of multiple constraints of intelligent service. Through the calculation and analysis of the time series signal, a correct, complete and distinguishable quantitative satisfaction degree is proposed; compared with the existing intelligent service monitoring methods, the invention proposes a real-time, efficient, and contractual monitoring based on the signal time series logic. method to improve the monitoring efficiency.

Other features and advantages of the present application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the present application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description, claims, and drawings.

Description of drawings

In order to explain the technical solutions of the embodiments of the present application more clearly, the following briefly introduces the accompanying drawings that need to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, therefore It should not be regarded as a limitation of the scope. For those of ordinary skill in the art, other related drawings can also be obtained from these drawings without any creative effort.

1 is a schematic diagram of the architecture of a real-time dynamic monitoring system for intelligent services provided by an embodiment of the present application;

2 is an implementation flowchart of a method for real-time dynamic monitoring of intelligent services provided by an embodiment of the present application;

3 is a detailed implementation flowchart of a method for real-time dynamic monitoring of an intelligent service provided by an embodiment of the present application;

4 is a schematic structural diagram of an apparatus for real-time dynamic monitoring of intelligent services provided by an embodiment of the present application;

FIG. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations. Thus, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the application as claimed, but is merely representative of selected embodiments of the application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present application.

It should be noted that like numerals and letters refer to like items in the following figures, so once an item is defined in one figure, it does not require further definition and explanation in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

First, some terms involved in the embodiments of the present application will be described to facilitate understanding by those skilled in the art.

Terminal equipment: can be a mobile terminal, a fixed terminal or a portable terminal, such as a mobile phone, a site, a unit, a device, a multimedia computer, a multimedia tablet, an Internet node, a communicator, a desktop computer, a laptop computer, a notebook computer, a netbook computer, Tablet computers, personal communication system devices, personal navigation devices, personal digital assistants, audio/video players, digital cameras/camcorders, pointing devices, television receivers, radio receivers, e-book devices, gaming devices, or any combination thereof, Includes accessories and peripherals for these devices or any combination thereof. It is also envisioned that the terminal device can support any type of user-oriented interface (eg, wearable device) and the like.

Server: It can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or it can provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, Cloud servers for middleware services, domain name services, security services, and basic cloud computing services such as big data and artificial intelligence platforms.

Central Processing Unit (CPU): It is the operation and control core of a computer system, and is the final execution unit for information processing and program operation.

In order to improve the monitoring efficiency when monitoring the constraint satisfaction degree of the intelligent service, an embodiment of the present application provides a method for real-time dynamic monitoring of the intelligent service.

Referring to FIG. 1 , which is a schematic diagram of the architecture of a real-time dynamic monitoring system for intelligent services according to an embodiment of the present application, the real-time dynamic monitoring system for intelligent services includes monitoring equipment and intelligent service equipment.

Intelligent service equipment: used to provide intelligent services, and as a monitoring object to meet user needs.

Monitoring equipment: According to user needs, preset the monitoring target of at least one constraint of the intelligent service, convert the monitoring target into a sequential logic formula, and build a positive and negative biased Riemann sum calculation method based on the Riemann sum operator to generate A new method for calculating the quantitative satisfaction degree of signal timing logic, obtains the time series signal corresponding to the monitoring target, and calculates the satisfaction degree of various constraints of intelligent services in real time based on the new quantitative satisfaction degree calculation method for signal timing logic, and realizes the satisfaction of intelligent services. Real-time dynamic monitoring.

In this embodiment of the present application, the execution subject may be the monitoring device in the intelligent service real-time dynamic monitoring system shown in FIG. 1 . In practical applications, the monitoring device may be electronic devices such as terminal devices and servers, which are not limited here.

Referring to FIG. 2 , an implementation flowchart of a method for real-time dynamic monitoring of intelligent services provided by an embodiment of the present application, combined with the monitoring device shown in FIG. 1 , the specific implementation process of the method is as follows:

Step 200: According to user requirements, preset a monitoring target with at least one constraint of the intelligent service, and convert the monitoring target into a sequential logic formula.

Wherein, the intelligent service constraint includes at least one of the following attributes: spatial correlation attribute, time attribute, execution energy consumption attribute and resource limitation attribute.

Optionally, the smart service may be a service provided by a smart device or a service provided by other devices, and the number of smart services may be one or multiple, which is not limited herein.

In one embodiment, the smart service system is deployed according to the smart device and the smart service provided by the smart device.

In one embodiment, the spatial correlation attribute can be obtained according to the spatial location, the sensing radius, the location of the area where the smart device is located, and the spatial constraint radius of the smart device.

表示空间相关度属性，ur.spt和

分别表示用户请求所在网络区域和智能设备可提供服务的有效作用区域。in,

Represents the spatial correlation property, ur.spt and

Respectively represent the network area where the user request is located and the effective area where the smart device can provide services.

In one embodiment, the time attribute can be obtained according to the data transfer model and the calculation model.

In one embodiment, the execution energy consumption attribute can be obtained according to the transmission energy consumption model and the calculation energy consumption model of the intelligent node:

的服务

执行，其时间计算公式如下：The task tsk _k is hosted on the smart device

service

Execute, the time calculation formula is as follows:

表示时间属性，f代表

的计算能力，即每秒的CPU周期数；tsk_k.cr表示完成任务所需要的CPU周期总数。in,

Indicates the time attribute, f represents

The computing power, that is, the number of CPU cycles per second; tsk _k .cr represents the total number of CPU cycles required to complete the task.

设备所消耗的能量计算公式为：

The formula for calculating the energy consumed by the equipment is:

表示能量，k为系数，f代表

的计算能力，即每秒的CPU周期数；tsk_k.cr表示完成任务所需要的CPU周期总数。in,

Represents energy, k is the coefficient, f represents

The computing power, that is, the number of CPU cycles per second; tsk _k .cr represents the total number of CPU cycles required to complete the task.

间传输速率γ_ij计算如下：edge device

The inter-transmission rate γ _ij is calculated as follows:

表示

的传输功率，g_ij表示两个智能设备之间传输信道增益，A₁表明数据是通过局域网在端设备之间传输，A₂表明数据是通过广域网在目标服务器和端设备之间传输或在目标服务器之间传输，B_L和B_W分别表示局域网和广域网的传输带宽。in,

express

The transmission power, g _ij represents the transmission channel gain between two smart devices, A ₁ indicates that the data is transmitted between the end devices through the local area network, A ₂ indicates that the data is transmitted between the target server and the end device through the WAN For transmission between servers, _{BL and B W represent} the transmission bandwidth of the local area network and the wide area network, respectively.

The communication time formula of the transmitted data amount dt _ij is as follows:

表示边缘设备

和

的通信时间，dt_ij表示传输数据量，r_ij表示传输半径。in,

Represents an edge device

and

, dt _ij represents the amount of transmitted data, and r _ij represents the transmission radius.

The communication energy consumption formula of the transmitted data amount dt _ij is as follows:

表示边缘设备

和

的通信能耗，

表示传输功率，dt_ij表示传输数据量，r_ij表示传输半径。in,

Represents an edge device

and

communication energy consumption,

represents the transmission power, dt _ij represents the amount of transmitted data, and r _ij represents the transmission radius.

In one embodiment, the resource limitation attribute includes software and hardware information such as CPU computing power, transmission bandwidth, storage space, and software version.

In this way, it is possible to preset at least one constrained monitoring target of the intelligent service according to the personalized needs of the user, and convert the monitoring target into a sequential logic formula.

Step 201: Based on the Riemann sum operator, construct a positive and negative bias Riemann sum calculation method, and generate a new method for calculating the quantitative satisfaction degree of signal sequential logic.

Specifically, when step 201 is performed, the following steps may be performed:

Based on the constructed Riemann sum calculation method of positive and negative biases, a new formal semantics of temporal logic for signals is constructed.

In one embodiment, the Riemann sum signal timing logic can be constructed according to the following formula:

The Riemann sum operator is defined as follows:

where, I={I ₁ , I ₂ ,...,I _k }, I _i =[t _i ,t _i+1 ](i=1,2,...,k,k≥1),I _i ∩I _i+1 ={t _i+1 }. In addition, in order to achieve the robustness of the signal timing logic, a positive and negative biased Riemann sum operator is defined:

Among them, i=1...k, k is a positive integer,

将给定的一个信号时序逻辑公式

一个信号值

在一个时间点t∈I，对于一个智能服务sev∈SEV，映射到

内的一个实数值：In one embodiment, the quantitative semantics of the signal temporal logic constructed based on the positive and negative biased Riemann sum is: that is, a robust value function is defined.

Convert a given signal to the sequential logic formula

a signal value

At a point in time t ∈ I, for an intelligent service sev ∈ SEV, maps to

A real value in :

In one embodiment, to prove the correctness and completeness of the semantics of the signal timing logic constructed based on the Riemann sum, the following formula can be used:

表示我们构建的鲁棒值函数，ω，

表示一个信号值，t，t∈I，表示一个时间点，sev，sev∈SEV表示智能设备提供的服务。in,

represents our constructed robust value function, ω,

represents a signal value, t, t ∈ I, represents a time point, and sev, sev ∈ SEV represents the service provided by the smart device.

In one embodiment, logical union, logical union and logical OR operations can be performed on the constructed Riemann sum signal timing logic to prove its commutative law and associative law:

表示一个鲁棒值函数，ω，

表示一个信号值，t，t∈I，表示一个时间点，sev，sev∈SEV表示智能设备提供的服务。in,

represents a robust value function, ω,

represents a signal value, t, t ∈ I, represents a time point, and sev, sev ∈ SEV represents the service provided by the smart device.

Based on the constructed positive and negative biased Riemann sum calculation method, a new type of sequential logic formal semantics for signals can be constructed to realize real-time dynamic monitoring of intelligent services with robust timing, discernible signals, and dynamic application, and improve monitoring efficiency.

Step 202: Acquire the time series signal corresponding to the monitoring target, and calculate the satisfaction degree of each constraint of the intelligent service in real time based on the novel signal time series logic quantitative satisfaction degree calculation method, so as to realize the real-time dynamic monitoring of the intelligent service.

Specifically, when step 202 is performed, the following steps may be performed:

S2021: Acquire the timing signal corresponding to the monitoring target and the signal interval thereof.

It should be noted that the signal interval of the timing signal may be any positive integer value, and the timing signal may include timing signals that meet user requirements and/or do not meet user requirements.

S2022: Based on the formal semantics of the constructed new sequential logic, perform signal processing under positive and negative bias on the logic formula of the monitoring target.

Specifically, the monitoring device can formalize semantics based on the constructed new sequential logic, and perform signal processing under positive and negative bias on the logic formula of the monitoring target.

In one embodiment, a multi-dimensional signal variable is defined to represent the execution of multiple sub-services in the aggregated service over a period of time:

ω: I×SEV→B×R

表示一个连续时间段，SEV表示边缘网络内被监测的服务集合，

⊥：＝False，

in,

represents a continuous time period, SEV represents the set of monitored services in the edge network,

⊥:=False,

即每一个服务的多约束集合，对每一个约束x_i∈X，定义其在多维信号变量上的投影，即

并对一个服务sev_j针对约束x_i在特定时间点t上的信号值规约为

将

简写为x，对信号时序逻辑的信号时序逻辑算子(包括语法和语义)进行定义和规约的公式如下：For multiple types of constraints in aggregation services, such as spatial correlation attributes, temporal attributes, and resource limitation attributes, define

That is, the multi-constraint set of each service, for each constraint x _i ∈ X, define its projection on the multi-dimensional signal variable, namely

and reduce the signal value of a service sev _j for a constraint x _i at a specific time point t to

Will

Abbreviated as x, the formula for defining and reducing the signal temporal logic operator (including syntax and semantics) of signal temporal logic is as follows:

表示信号时序逻辑算子，x～c表示断言，c是用户指定的常数阈值；

是逻辑非，∧是逻辑与，∨是逻辑或，U_I是时序“直到”算子，表示

能在区间I内至少某一时间点t∈I满足，且

在时间点t之前总是被满足，F_I是时序“最终”算子，表示在区间I内至少某一时间点t∈I，

能被满足，G_I是时序“总是”算子，表示在区间I内所有时间点，

均能被满足。in,

Represents the signal timing logic operator, x～c represents the assertion, and c is the constant threshold specified by the user;

is logical negation, ∧ is logical AND, ∨ is logical OR, U _I is the sequential "until" operator, which means

can be satisfied at least at a certain time point t∈I in the interval I, and

is always satisfied before time point t, F _I is the temporal "final" operator, indicating that at least some time point t ∈ I in interval I,

can be satisfied, G _I is a time series "always" operator, indicating all time points in interval I,

can be satisfied.

In this way, according to the formal semantics of the constructed new sequential logic, the logic formula of the monitoring target can be processed under the positive and negative bias, and the more accurate degree of satisfaction of the constraints of the intelligent service can be obtained.

S2023: Calculate the satisfaction degree of each constraint of the intelligent service in real time, and realize the real-time dynamic monitoring of the intelligent service.

Specifically, based on the Riemann sum calculation method, the monitoring equipment performs signal processing on the part of the time series signal that meets the user's needs and does not meet the user's needs, and obtains the constraint satisfaction degree of the intelligent service.

Among them, the constraint satisfaction degree represents the degree to which the intelligent service meets the user's needs at a certain moment or a certain period of time.

It should be noted that the part of the time sequence signal that meets the user's requirement is a positive value, and the part that does not meet the user's requirement is a negative value.

It should be noted that the user requirement refers to a predicate (predicate) for at least one attribute in at least one intelligent service.

In one embodiment, the monitoring equipment of the user is set, namely the monitoring of a single service with a single constraint, the monitoring of a single service with multiple constraints, and the monitoring of multiple services with multiple constraints, based on logical AND, logical OR, logical NOT, until, always, and Finally, the equal-signal sequential logic operator generates the monitoring formula of the signal sequential logic.

In one embodiment, the monitoring of a single constraint of a single service can use the following formula:

Among them, cnt ₁ and cnt ₂ represent different constraints defined on the single service _sevi , such as constraints such as spatial location or spatial resources.

In one embodiment, the following formula can be used for monitoring multiple services and multiple constraints:

代表每一个服务上的约束。Among them, SEV={sev ₁ , sev ₂ ,..., sev _i }, representing multiple services,

Represents a constraint on each service.

In one embodiment, in the dynamic monitoring process of the smart hotel, the monitoring formula based on the signal timing logic, and the signal timing logic calculation such as logical AND, logical OR, logical NOT, until, always and finally constructed in the signal timing logic. The calculation method of the constraint satisfaction degree of the child is used to calculate the qualitative and quantitative constraint satisfaction degree of each device in the smart hotel.

In the embodiment of the present application, according to user requirements, a number of constraint monitoring targets on the intelligent service are preset, and the monitoring targets are converted into sequential logic formulas; based on the Riemann sum operator, a positive and negative biased Riemann sum calculation method is constructed , generate a new quantitative satisfaction calculation method of signal timing logic; obtain the timing signal corresponding to the monitoring target of intelligent service, and perform real-time processing operation to realize real-time dynamic monitoring of multiple constraints of intelligent service. By calculating and analyzing the positive and negative time-series signals in the time-series signals respectively, a correct, complete and distinguishable quantitative satisfaction degree is proposed; compared with the existing intelligent service monitoring methods, the invention proposes a real-time, efficient and effective time-series logic-based method. , The stipulation monitoring method improves the monitoring efficiency.

Referring to FIG. 3 , a detailed implementation flowchart of a method for real-time dynamic monitoring of intelligent services provided by an embodiment of the present application, the specific implementation process of the method is as follows:

Step 300: According to user requirements, preset a monitoring target with at least one constraint of the intelligent service, and convert the monitoring target into a sequential logic formula.

Step 301: Based on the Riemann sum operator, construct a positive and negative bias Riemann sum calculation method, and generate a new method for calculating the quantitative satisfaction degree of signal sequential logic.

Step 302: Acquire the timing signal corresponding to the monitoring target and the signal interval thereof.

Step 303: Based on the constructed new-type sequential logic formal semantics, perform signal processing under positive and negative bias on the logic formula of the monitoring target.

Step 304: Calculate the satisfaction degree of each constraint of the intelligent service in real time, so as to realize real-time dynamic monitoring of the intelligent service.

Specifically, when steps 300 to 304 are executed, refer to the above steps 200 to 202 for specific steps, which will not be repeated here.

Based on the same inventive concept, the embodiments of the present application also provide a device for real-time dynamic monitoring of intelligent services.

Referring to FIG. 4, a schematic structural diagram of an apparatus for real-time dynamic monitoring of intelligent services provided by an embodiment of the present application includes:

Conversion unit 401: used to preset a monitoring target of at least one constraint of the intelligent service according to user requirements, and convert the monitoring target into a sequential logic formula;

Generating unit 402: for constructing a positive and negative biased Riemann sum calculation method based on the Riemann sum operator, and generating a new method for calculating the quantitative satisfaction degree of signal sequential logic;

Obtaining unit 403: used to obtain the timing signal corresponding to the monitoring target;

The processing unit 404 is configured to calculate the satisfaction degree of each constraint of the intelligent service in real time based on the novel signal timing logic quantitative satisfaction degree calculation method, so as to realize the real-time dynamic monitoring of the intelligent service.

In one embodiment, the generating unit 402 is used to:

Based on the constructed Riemann sum calculation method of positive and negative biases, a new formal semantics of temporal logic for signals is constructed.

In one embodiment, the obtaining unit 403 is used for:

Obtain the timing signal corresponding to the monitoring target and its signal interval.

In one embodiment, the processing unit 404 is used to:

Based on the formal semantics of the constructed new sequential logic, the logic formula of the monitoring target is processed under positive and negative bias;

Real-time calculation of the degree of satisfaction of various constraints of intelligent services to realize real-time dynamic monitoring of intelligent services.

Referring to FIG. 5 , it is a schematic structural diagram of an electronic device according to an embodiment of the present application.

The electronic device 5000 includes: a processor 5010 and a memory 5020 , and optionally, a power supply 5030 , a display unit 5040 , and an input unit 5050 .

The processor 5010 is the control center of the electronic device 5000, uses various interfaces and lines to connect various components, and executes various functions of the electronic device 5000 by running or executing the software programs and/or data stored in the memory 5020, so as to control the electronic device 5000. Device 5000 performs overall monitoring.

In this embodiment of the present application, when the processor 5010 invokes the computer program stored in the memory 5020, the method for real-time dynamic monitoring of an intelligent service provided by the embodiment shown in FIG. 2 is executed.

Optionally, the processor 5010 may include one or more processing units; preferably, the processor 5010 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and applications, etc. The modem processor mainly handles wireless communication. It can be understood that, the above-mentioned modulation and demodulation processor may not be integrated into the processor 5010. In some embodiments, the processor, memory, can be implemented on a single chip, and in some embodiments, they can also be implemented separately on separate chips.

The memory 5020 may mainly include a stored program area and a stored data area, wherein the stored program area may store an operating system, various applications, etc.; the storage data area may store data created according to the use of the electronic device 5000, and the like. In addition, memory 5020 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device, or the like.

The electronic device 5000 also includes a power supply 5030 (such as a battery) for supplying power to various components. The power supply can be logically connected to the processor 5010 through a power management system, so as to manage charging, discharging, and power consumption functions through the power management system.

The display unit 5040 may be used to display information input by the user or information provided to the user, various menus of the electronic device 5000, etc., and is mainly used to display the display interface of each application in the electronic device 5000 and the display in the display interface in this embodiment of the present invention. text, pictures and other objects. The display unit 5040 may include a display panel 5041 . The display panel 5041 may be configured in the form of a liquid crystal display (Liquid Crystal Display, LCD), an organic light-emitting diode (Organic Light-Emitting Diode, OLED) and the like.

The input unit 5050 may be used to receive information such as numbers or characters input by the user. The input unit 5050 may include a touch panel 5051 and other input devices 5052 . Among them, the touch panel 5051, also known as a touch screen, can collect the user's touch operations on or near it (for example, the user uses any suitable objects or accessories such as a finger, a touch pen, etc. on the touch panel 5051 or on the touch panel 5051). nearby operations).

Specifically, the touch panel 5051 can detect the user's touch operation, and detect the signals brought by the touch operation, convert these signals into contact coordinates, send them to the processor 5010, and receive the commands sent by the processor 5010 and execute them . In addition, the touch panel 5051 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic waves. Other input devices 5052 may include, but are not limited to, one or more of physical keyboards, function keys (such as volume control keys, power-on/off keys, etc.), trackballs, mice, joysticks, and the like.

Of course, the touch panel 5051 can cover the display panel 5041. When the touch panel 5051 detects a touch operation on or near it, it transmits it to the processor 5010 to determine the type of the touch event, and then the processor 5010 determines the type of the touch event according to the type of the touch event. Corresponding visual outputs are provided on the display panel 5041 . Although in FIG. 5, the touch panel 5051 and the display panel 5041 are used as two independent components to realize the input and output functions of the electronic device 5000, in some embodiments, the touch panel 5051 and the display panel 5041 may be The input and output functions of the electronic device 5000 are implemented by integration.

The electronic device 5000 may also include one or more sensors, such as a pressure sensor, a gravitational acceleration sensor, a proximity light sensor, and the like. Of course, according to the needs of specific applications, the above electronic device 5000 may also include other components such as cameras. Since these components are not the key components used in the embodiments of this application, they are not shown in FIG. 5 and will not be described in detail. .

Those skilled in the art can understand that FIG. 5 is only an example of an electronic device, and does not constitute a limitation to the electronic device, and may include more or less components than shown, or combine some components, or different components.

In this embodiment of the present application, a readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, the communication device can perform each step in the foregoing embodiments.

For the convenience of description, the above parts are divided into modules (or units) according to their functions and described respectively. Of course, the functions of each module (or unit) may be implemented in one or more software or hardware when implementing the present application.

As will be appreciated by those skilled in the art, the embodiments of the present application may be provided as a method, a system, or a computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

While the preferred embodiments of the present application have been described, additional changes and modifications to these embodiments may occur to those skilled in the art once the basic inventive concepts are known. Therefore, the appended claims are intended to be construed to include the preferred embodiment and all changes and modifications that fall within the scope of this application.

Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims (11)

1. a method for intelligent service real-time dynamic monitoring, is characterized in that, comprises: According to user requirements, preset a monitoring target with at least one constraint of the intelligent service, and convert the monitoring target into a sequential logic formula; Based on the Riemann sum operator, construct a positive and negative bias Riemann sum calculation method, and generate a new quantitative satisfaction calculation method for signal sequential logic; The time sequence signal corresponding to the monitoring target is acquired, and based on the novel signal time sequence logic quantitative satisfaction degree calculation method, the satisfaction degree of each constraint of the intelligent service is calculated in real time, so as to realize the real-time dynamic monitoring of the intelligent service. 2. The method according to claim 1, wherein the intelligent service constraint comprises at least one of the following attributes: a space attribute, a time attribute, an energy consumption attribute and a resource limitation attribute. 3. method according to claim 1 and 2, is characterized in that, described based on Riemann sum operator, construct positive and negative bias Riemann sum calculation mode, generate a kind of novel signal sequential logic quantitative satisfaction degree calculation methods, including: Based on the constructed Riemann sum calculation method of positive and negative biases, a new formal semantics of temporal logic for signals is constructed. 4. The method according to claim 3, characterized in that, the acquisition of the time sequence signal corresponding to the monitoring target, and based on the novel signal time sequence logic quantitative satisfaction calculation method, real-time calculation of the constraints of the intelligent service. Satisfaction, realize the real-time dynamic monitoring of intelligent services, including: Obtain the timing signal corresponding to the monitoring target and the signal interval thereof; Based on the constructed new sequential logic formal semantics, perform signal processing under positive and negative bias on the logic formula of the monitoring target; The satisfaction degree of each constraint of the intelligent service is calculated in real time, so as to realize the real-time dynamic monitoring of the intelligent service. 5. A device for real-time dynamic monitoring of intelligent services, characterized in that, comprising: a conversion unit, configured to preset a monitoring target with at least one constraint of the intelligent service according to user requirements, and convert the monitoring target into a sequential logic formula; The generation unit is used to construct a positive and negative biased Riemann sum calculation method based on the Riemann sum operator, and generate a new quantitative satisfaction calculation method for signal sequential logic; an acquisition unit, configured to acquire the time sequence signal corresponding to the monitoring target; The processing unit is configured to calculate the satisfaction degree of each constraint of the intelligent service in real time based on the novel signal timing logic quantitative satisfaction degree calculation method, so as to realize the real-time dynamic monitoring of the intelligent service. 6. The apparatus according to claim 5, wherein the intelligent service constraint comprises at least one of the following attributes: a space attribute, a time attribute, an energy consumption attribute, and a resource limitation attribute. 7. device according to claim 5 or 6, is characterized in that, described generation unit is specially used for: Based on the constructed Riemann sum calculation method of positive and negative biases, a new formal semantics of temporal logic for signals is constructed. 8. The device according to claim 7, wherein the acquiring unit is specifically configured to: Acquire the timing signal corresponding to the monitoring target and the signal interval thereof. 9. The apparatus according to claim 7, wherein the processing unit is specifically configured to: Based on the constructed new sequential logic formal semantics, perform signal processing under positive and negative bias on the logic formula of the monitoring target; The satisfaction degree of each constraint of the intelligent service is calculated in real time, so as to realize the real-time dynamic monitoring of the intelligent service. 10. An electronic device, comprising a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, claims 1-4 are executed any of the described methods. 11. A computer-readable storage medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the method according to any one of claims 1-4 is executed.

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