CN114706731A - Intelligent service real-time dynamic monitoring method - Google Patents
Intelligent service real-time dynamic monitoring method Download PDFInfo
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Abstract
The application belongs to the field of service calculation, and discloses a real-time dynamic monitoring method for intelligent services, which comprises the steps of presetting a plurality of constraint monitoring targets on the intelligent services according to user requirements, and converting the monitoring targets into a time sequence logic formula; constructing a positive and negative offset Riemann and a calculation mode based on Riemann and operators to generate a novel signal time sequence logic quantification satisfaction degree calculation method; and acquiring a time sequence signal corresponding to an intelligent service monitoring target, and performing real-time processing operation to realize real-time dynamic monitoring on multiple constraints of the intelligent service. Compared with the existing signal sequential logic, the invention respectively carries out calculation and analysis on the positive and negative sequential signals in the sequential signals, and provides correct, complete and recognizable quantitative satisfaction; compared with the existing intelligent service monitoring method, the invention provides a real-time, efficient and stipulable monitoring method based on sequential logic, and the monitoring efficiency is improved.
Description
Technical Field
The application relates to the technical field of service computing, in particular to a real-time dynamic monitoring method for intelligent services.
Background
The service-oriented internet of things is being researched by more and more experts, target equipment at the bottom layer is abstracted into intelligent service, and further specific requirements of users are met through intelligent service combination, recommendation, adaptation and other modes. For example, in a smart hotel, different intelligent devices such as a robot, a voice assistant, a curtain, a television and the like are abstracted to be intelligent services, and whether the hotel meets the user requirements or not is judged by monitoring the service satisfaction degree of each intelligent device.
In the prior art, an intelligent service active or passive monitoring algorithm is generally adopted to judge whether the intelligent service meets the user requirements on line or off line. However, the existing methods do not consider the quantitative monitoring of the satisfaction degree of the intelligent service under the constraint of a sequential logic operator in a period of time, and lack formal semantic conventions and quantitative measurement methods of the satisfaction degree.
The intelligent service is dynamically monitored in real time based on the signal time sequence logic, and the method is an effective and feasible solution. The signal sequential logic has the indistinguishable problems that the signal values are different and the satisfaction degree may not be different. The existing research work has noticed the defect, starting from a mean value operator and a smoothing operator, and the signal time sequence logic is enhanced. However, these works have the problem that the signal values that do not satisfy the constraint are covered by the signal values that satisfy the constraint, which causes robustness, such as the phenomenon that the mean value is positive and cannot represent that all the signal values are positive. For the defect of signal value unreliability, recent research work defines the quantification semantics of signal values satisfying constraints and parts not satisfying constraints respectively, such as performing mean value operation or smoothing operation on signal values satisfying parts only. However, these operations are based on the assumption of a fixed sampling rate, and are difficult to be applied to the problem that the signal sampling rate is difficult to be fixed when the signal is dynamically changed.
In order to support the scene of non-uniform signal sampling rate, the invention constructs the Riemann operator under positive and negative bias based on the Riemann operator, and carries out time operator extension on signal time sequence logic, thereby realizing intelligent service real-time dynamic monitoring with robust time sequence, distinguishable signals and dynamic applicability.
Disclosure of Invention
The application aims to provide a real-time dynamic monitoring method for intelligent services, which is used for improving monitoring efficiency when the constraint satisfaction degree of the intelligent services is monitored.
In one aspect, a method for real-time dynamic monitoring of intelligent services is provided, which includes: presetting a monitoring target of at least one constraint of intelligent service according to user requirements, and converting the monitoring target into a time sequence logic formula;
constructing a positive and negative offset Riemann and a calculation mode based on Riemann and operators to generate a novel signal time sequence logic quantification satisfaction degree calculation method;
and acquiring a time sequence signal corresponding to a monitoring target, and calculating the satisfaction degree of each constraint of the intelligent service in real time based on a novel signal time sequence logic quantitative satisfaction degree calculation method, so as to realize real-time dynamic monitoring on the intelligent service.
In the implementation process, the sequential signals are calculated and analyzed by constructing a positive and negative biased Riemann and a calculation mode, and correct, complete and identifiable quantitative satisfaction is provided; compared with the existing intelligent service monitoring method, the invention provides a real-time, efficient and stipulable monitoring method based on sequential logic, and the monitoring efficiency is improved.
In one embodiment, the intelligent service constraints include at least one of the following attributes: a spatial attribute, a temporal attribute, an energy consumption attribute, and a resource restriction attribute.
In one embodiment, a novel signal sequential logic quantification satisfaction degree calculation method is generated by constructing a positive and negative offset Riemann sum calculation mode based on Riemann sum operators, and comprises the following steps:
and constructing novel sequential logic formal semantics of the signal based on the constructed Riemann with positive and negative offsets and a calculation mode.
In the implementation process, the real-time dynamic monitoring of multiple constraints of the intelligent service can be more accurately and efficiently realized according to the novel sequential logic formal semantics of the constructed signal during the subsequent monitoring of the intelligent service.
In one embodiment, a timing signal corresponding to a monitoring target is obtained, and the satisfaction degree of each constraint of an intelligent service is calculated in real time based on a novel signal timing logic quantitative satisfaction degree calculation method, so that real-time dynamic monitoring on the intelligent service is realized, and the method comprises the following steps:
acquiring a time sequence signal corresponding to a monitoring target and a signal interval thereof;
based on the constructed novel sequential logic formal semantics, performing signal processing under positive and negative bias on a logic formula of a monitoring target;
and calculating the satisfaction degree of each constraint of the intelligent service in real time, and realizing real-time dynamic monitoring of the intelligent service.
In the implementation process, the real-time dynamic monitoring of the intelligent service can be realized in real time, efficiently and accurately based on the constructed novel sequential logic formalized semantics.
In one aspect, an apparatus for real-time dynamic monitoring of intelligent services is provided, which includes:
a conversion unit: the system comprises a monitoring target, a time sequence logic formula and a service management server, wherein the monitoring target is used for presetting at least one constraint of intelligent service according to user requirements and converting the monitoring target into the time sequence logic formula;
a generation unit: the method is used for constructing a positive and negative offset Riemann and a calculation mode based on a Riemann sum operator to generate a novel signal time sequence logic quantification satisfaction calculation method;
an acquisition unit: the time sequence signal acquisition unit is used for acquiring a time sequence signal corresponding to a monitoring target;
a processing unit: the method is used for calculating the quantitative satisfaction degree based on novel signal sequential logic, calculating the satisfaction degree of each constraint of the intelligent service in real time and realizing real-time dynamic monitoring of the intelligent service.
In one embodiment, the intelligent service constraints include at least one of the following attributes: a spatial attribute, a temporal attribute, an energy consumption attribute, and a resource restriction attribute.
In one embodiment, the generating unit is configured to:
and constructing a novel sequential logic formal semantic of the signal based on the constructed Riemann with positive and negative offsets and a calculation mode.
In one embodiment, the obtaining unit is configured to:
and acquiring a time sequence signal corresponding to the monitoring target and a signal interval thereof.
In one embodiment, the processing unit is configured to:
based on the constructed novel sequential logic formalized semantics, performing signal processing under positive and negative bias on a logic formula of a monitoring target;
and calculating the satisfaction degree of each constraint of the intelligent service in real time, and realizing real-time dynamic monitoring of the intelligent service.
In one aspect, an electronic device is provided, comprising a processor and a memory, the memory storing computer readable instructions which, when executed by the processor, perform the steps of the method provided in any of the various alternative implementations of intelligent service real-time dynamic monitoring described above.
In one aspect, a readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, performs the steps of the method as provided in the various alternative implementations of the real-time dynamic monitoring of intelligent services as described above.
In one aspect, a computer program product is provided, which when run on a computer causes the computer to perform the steps of the method as provided in any of the various alternative implementations of intelligent services real-time dynamic monitoring described above.
In the embodiment of the application, a plurality of constraint monitoring targets on the intelligent service are preset according to the requirements of a user, and the monitoring targets are converted into a time sequence logic formula; constructing a positive and negative offset Riemann and a calculation mode based on Riemann and operators to generate a novel signal time sequence logic quantification satisfaction degree calculation method; and acquiring a time sequence signal corresponding to an intelligent service monitoring target, and performing real-time processing operation to realize real-time dynamic monitoring on multiple constraints of the intelligent service. Through the calculation and analysis of the time sequence signals, the accurate, complete and recognizable quantitative satisfaction degree is provided; compared with the existing intelligent service monitoring method, the invention provides a real-time, efficient and protocol-controllable monitoring method based on signal sequential logic, and the monitoring efficiency is improved.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic structural diagram of an intelligent service real-time dynamic monitoring system according to an embodiment of the present disclosure;
fig. 2 is a flowchart of an implementation of a method for real-time dynamic monitoring of an intelligent service according to an embodiment of the present application;
fig. 3 is a flowchart illustrating a detailed implementation of a method for real-time dynamic monitoring of an intelligent service according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an apparatus for real-time dynamic monitoring of an intelligent service according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
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, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, as presented in the figures, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
First, some terms referred to in the embodiments of the present application will be described to facilitate understanding by those skilled in the art.
The terminal equipment: may be a mobile terminal, a fixed terminal, or a portable terminal such as a mobile handset, station, unit, device, multimedia computer, multimedia tablet, internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system device, personal navigation device, personal digital assistant, audio/video player, digital camera/camcorder, positioning device, television receiver, radio broadcast receiver, electronic book device, gaming device, or any combination thereof, including the accessories and peripherals of these devices, or any combination thereof. It is also contemplated that the terminal device can support any type of interface to the user (e.g., wearable device), and the like.
A server: the cloud server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, and can also be a cloud server for providing basic cloud computing services such as cloud service, a cloud database, cloud computing, cloud functions, cloud storage, network service, cloud communication, middleware service, domain name service, security service, big data and artificial intelligence platform and the like.
Central Processing Unit (CPU): the computer system is an operation and control core of the computer system and is a final execution unit for information processing and program operation.
In order to improve monitoring efficiency when monitoring constraint satisfaction of intelligent service, the embodiment of the application provides a method for real-time dynamic monitoring of intelligent service.
Fig. 1 is a schematic diagram of an architecture of an intelligent service real-time dynamic monitoring system according to an embodiment of the present application, where the intelligent service real-time dynamic monitoring system includes a monitoring device and an intelligent service device.
The intelligent service equipment: the system is used for providing intelligent services and serving as a monitoring object for meeting the requirements of users.
Monitoring equipment: the method comprises the steps of presetting a monitoring target of at least one constraint of the intelligent service according to user requirements, converting the monitoring target into a sequential logic formula, constructing a positive and negative offset Riemann and a calculation mode based on the Riemann and an operator, generating a novel signal sequential logic quantitative satisfaction calculation method, obtaining sequential signals corresponding to the monitoring target, calculating the satisfaction of each constraint of the intelligent service in real time based on the novel signal sequential logic quantitative satisfaction calculation method, and realizing real-time dynamic monitoring on the intelligent service.
In this embodiment of the application, the execution subject may be a monitoring device in the intelligent service real-time dynamic monitoring system shown in fig. 1, and in practical application, the monitoring device may be an electronic device such as a terminal device and a server, which is not limited herein.
Referring to fig. 2, an implementation flow chart of a method for real-time dynamic monitoring of an intelligent service according to an embodiment of the present application is shown, and with reference to the monitoring device shown in fig. 1, a specific implementation flow of the method is as follows:
step 200: according to the user requirements, at least one constraint monitoring target of the intelligent service is preset, and the monitoring target is converted into a time sequence logic formula.
Wherein the intelligent service constraints comprise at least one of the following attributes: a spatial correlation attribute, a temporal attribute, an execution energy consumption attribute, and a resource restriction attribute.
Optionally, the intelligent service may be a service provided by an intelligent device, or may be a service provided by another device, and the number of the intelligent services may be one or multiple, which is not limited herein.
In one embodiment, an intelligent service system is deployed based on an intelligent device and an intelligent service provided by the intelligent device.
In one embodiment, the spatial correlation attribute may be obtained according to a spatial position, a sensing radius, a position of an area where the smart device is located, and a spatial constraint radius of the smart device.
Wherein,
represents the spatial correlation property, ur
Respectively indicating the network area where the user requests and the effective action area where the intelligent device can provide the service.
In one embodiment, the time attribute may be obtained from a data transfer model and a calculation model.
In one embodiment, the execution energy consumption attribute may be obtained from the intelligent node transmission energy consumption model and the calculation energy consumption model:
task tskkHosted by the smart device
Of a service
The time calculation formula is as follows:
wherein,
representing a time attribute, f represents
I.e. number of CPU cycles per second; tskkCr denotes the total number of CPU cycles required to complete the task.
wherein,
representing energy, k being a coefficient, f representing
I.e. number of CPU cycles per second; tskkCr denotes the total number of CPU cycles required to complete the task.
Edge device
Inter transfer rate gammaijThe calculation is as follows:
wherein,
to represent
Transmission power of gijRepresenting the gain of the transmission channel between two intelligent devices, A1Indicating that data is being transmitted between end devices over a local area network, A2Indicating that data is being transmitted between the target server and the end device or is being transmitted between the target server and the end device over the wide area networkTransmission between mark servers, BLAnd BWRepresenting the transmission bandwidth of the local area network and the wide area network, respectively.
Amount of data transmitted dtijThe communication time formula of (c) is as follows:
wherein,
representing edge devices
And
communication time of dtijRepresenting the amount of data transmitted, rijRepresenting the transmission radius.
Amount of data transmitted dtijThe communication energy consumption formula is as follows:
wherein,
representing edge devices
And
the energy consumption of the communication of (2),
representing transmission power, dtijRepresenting the amount of data transmitted, rijRepresenting the transmission radius.
In one embodiment, the resource restriction attributes include software and hardware information such as CPU power, transmission bandwidth, storage space, and software version.
Therefore, at least one constraint monitoring target of the intelligent service can be preset according to the personalized requirements of the user, and the monitoring target is converted into a time sequence logic formula.
Step 201: and constructing a positive and negative offset Riemann and a calculation mode based on the Riemann sum operator to generate a novel signal time sequence logic quantification satisfaction degree calculation method.
Specifically, when step 201 is executed, the following steps may be executed:
and constructing novel sequential logic formal semantics of the signal based on the constructed Riemann with positive and negative offsets and a calculation mode.
In one embodiment, the Riemann sum signal timing logic may be constructed according to the following equation:
the riemann sum operator is defined as follows:
wherein I ═ I1，I2，...，Ik}，Ii＝[ti，ti+1](i＝1，2，...，k，k≥1)，Ii∩Ii+1＝{ti+1}. Furthermore, to achieve robustness of the signal timing logic, positive and negative biased riemann sum operators are defined:
wherein i is 1 … … k, k is a positive integer,
in one embodiment, the positive and negative bias based riemann and the quantified semantics of the constructed signal timing logic are as follows: i.e. defining a robust value function
Given a signal sequential logic formula
A signal value
At a point in time t e I, for an intelligent service SEV e SEV, mapping to
A real value of:
in one embodiment, the correctness and completeness of the semantics of the signal timing logic based on Riemann and the construction can be proved by adopting the following formula:
wherein,
the robust value function, ω,
represents a signal value, t, te I, represents a point in time, SEV, SEV e SEV represents the services provided by the smart device.
In one embodiment, the constructed riemann and signal sequence logic can be logically combined, logically combined and logically OR-ed, so as to prove the exchange law and the combination law:
wherein,
represents the function of a robust value, ω,
represents a signal value, t, te I, represents a point in time, SEV, SEV e SEV represents the services provided by the smart device.
Based on the constructed Riemann of positive and negative bias and a calculation mode, novel sequential logic formalized semantics of the signals can be constructed, intelligent service real-time dynamic monitoring with robust timing, distinguishable signals and dynamic applicability is realized, and the monitoring efficiency is improved.
Step 202: and acquiring a time sequence signal corresponding to a monitoring target, and calculating the satisfaction degree of each constraint of the intelligent service in real time based on a novel signal time sequence logic quantitative satisfaction degree calculation method, so as to realize real-time dynamic monitoring on the intelligent service.
Specifically, when step 202 is executed, the following steps may be executed:
s2021: and acquiring a time sequence signal corresponding to the monitoring target and a 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 a timing signal that meets and/or does not meet the user requirement.
S2022: and based on the constructed novel sequential logic formal semantics, performing signal processing under positive and negative bias on a logic formula of a monitoring target.
Specifically, the monitoring device can perform signal processing under positive and negative bias on a logic formula of a monitored target based on the constructed novel sequential logic formalized semantics.
In one embodiment, a multidimensional signal variable is defined to represent performance of a plurality of sub-services in an aggregated service over a period of time:
ω:I×SEV→B×R
wherein,
representing a continuous period of time, the SEV represents the set of services monitored within the edge network,
⊥：＝False，
defining multiple classes of constraints in an aggregated service, e.g., spatial correlation attributes, temporal attributes, and resource constraint attributes
I.e. multiple constraint sets per service, for each constraint xiE.g. X, defining its projection on a multidimensional signal variable, i.e.
And to a service sevjFor constraint xiThe signal value at a particular point in time t is reduced to
Will be provided with
Abbreviated as x, the formula for defining and specifying signal sequential logic operators (including syntax and semantics) for signal sequential logic is as follows:
wherein,
representing a signal time sequence logic operator, x-c represent assertions, and c is a constant threshold value specified by a user;
is logic not, inverted V is logic AND, V is logic OR, UIIs a sequential "up" operator, representing
Can meet the requirement of t epsilon I at least a certain time point within the interval IAnd is made of
Is always satisfied before the time t, FIIs a time-sequence 'final' operator, which means that at least a certain time point t e I in the interval I,
can be satisfied with GIIs a time-sequential "always" operator, indicating that at all time points within interval I,
can be satisfied.
Therefore, signal processing under positive and negative bias can be carried out on the logic formula of the monitoring target according to the constructed novel sequential logic formalized semantics, and more accurate satisfaction degree of each constraint of the intelligent service is obtained.
S2023: and calculating the satisfaction degree of each constraint of the intelligent service in real time, and realizing real-time dynamic monitoring of the intelligent service.
Specifically, the monitoring device performs signal processing on the parts, which meet the user requirements and do not meet the user requirements, in the time-series signals based on Riemann and a calculation method, so as to obtain the constraint satisfaction degree of the intelligent service.
Wherein the constraint satisfaction degree indicates the degree to which the intelligent service satisfies the user's needs at a certain moment or a certain time period.
It should be noted that, the portion of the timing signal that meets the user requirement is a positive value, and the portion that does not meet the user requirement is a negative value.
It should be noted that the user requirement refers to predicate assertion (predicate) on at least one attribute of at least one intelligent service.
In one embodiment, the monitoring device of the user is set, namely single-service single-constraint monitoring, single-service multi-constraint monitoring and multi-service multi-constraint monitoring, and the monitoring formula of the signal sequential logic is generated based on logical and, logical or, logical not, up to, always and finally equal signal sequential logic operators.
In one embodiment, the following formula may be used for monitoring a single-service single constraint:
wherein cnt1And cnt2The representation is defined in the single service seviDifferent constraints on the space, such as spatial location or spatial resources.
In one embodiment, the following formula may be used for monitoring multiple services and multiple constraints:
wherein SEV is { SEV ═ in1,sev2,…,seviDenotes a plurality of services,
representing constraints on each service.
In one embodiment, in the dynamic monitoring process of the intelligent hotel, based on a monitoring formula of signal time sequence logic and a constraint satisfaction degree calculation mode of signal time sequence logic operators such as logical AND, logical OR, logical NOT, up to, always and finally constructed in the signal time sequence logic, qualitative and quantitative constraint satisfaction degrees of all devices in the intelligent hotel are calculated.
In the embodiment of the application, a plurality of constraint monitoring targets on the intelligent service are preset according to the requirements of a user, and the monitoring targets are converted into a time sequence logic formula; constructing a positive and negative offset Riemann and a calculation mode based on Riemann and operators to generate a novel signal time sequence logic quantification satisfaction degree calculation method; and acquiring a time sequence signal corresponding to an intelligent service monitoring target, and performing real-time processing operation to realize real-time dynamic monitoring on multiple constraints of the intelligent service. Through respectively calculating and analyzing positive and negative time sequence signals in the time sequence signals, the accurate, complete and recognizable quantitative satisfaction degree is provided; compared with the existing intelligent service monitoring method, the invention provides a real-time, efficient and stipulable monitoring method based on sequential logic, and the monitoring efficiency is improved.
Referring to fig. 3, a detailed implementation flowchart of a method for real-time dynamic monitoring of an intelligent service according to an embodiment of the present application is shown, and the specific implementation flow of the method is as follows:
step 300: and presetting at least one constrained monitoring target of the intelligent service according to the user requirement, and converting the monitoring target into a time sequence logic formula.
Step 301: and constructing a positive and negative offset Riemann and a calculation mode based on the Riemann sum operator to generate a novel signal time sequence logic quantification satisfaction degree calculation method.
Step 302: and acquiring a time sequence signal corresponding to the monitoring target and a signal interval thereof.
Step 303: and based on the constructed novel sequential logic formal semantics, performing signal processing under positive and negative bias on a logic formula of a monitoring target.
Step 304: and calculating the satisfaction degree of each constraint of the intelligent service in real time, and realizing real-time dynamic monitoring of the intelligent service.
Specifically, when step 300 to step 304 are executed, the specific steps refer to step 200 to step 202, which are not described herein again.
Based on the same inventive concept, the embodiment of the application also provides a device for real-time dynamic monitoring of the intelligent service.
Referring to fig. 4, a schematic structural diagram of an apparatus for real-time dynamic monitoring of an intelligent service provided in an embodiment of the present application is shown, including:
the conversion unit 401: the system comprises a monitoring target, a time sequence logic formula and a service management server, wherein the monitoring target is used for presetting at least one constraint of intelligent service according to user requirements and converting the monitoring target into the time sequence logic formula;
the generation unit 402: the method is used for constructing a positive and negative offset Riemann and a calculation mode based on a Riemann sum operator to generate a novel signal time sequence logic quantification satisfaction calculation method;
the acquisition unit 403: the time sequence signal acquisition unit is used for acquiring a time sequence signal corresponding to a monitoring target;
the processing unit 404: the method is used for calculating the quantitative satisfaction degree based on novel signal sequential logic, calculating the satisfaction degree of each constraint of the intelligent service in real time and realizing real-time dynamic monitoring of the intelligent service.
In one embodiment, the generating unit 402 is configured to:
and constructing a novel sequential logic formal semantic of the signal based on the constructed Riemann with positive and negative offsets and a calculation mode.
In one embodiment, the obtaining unit 403 is configured to:
and acquiring a time sequence signal corresponding to the monitoring target and a signal interval thereof.
In one embodiment, the processing unit 404 is configured to:
based on the constructed novel sequential logic formalized semantics, performing signal processing under positive and negative bias on a logic formula of a monitoring target;
and calculating the satisfaction degree of each constraint of the intelligent service in real time, and realizing real-time dynamic monitoring of the intelligent service.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.
The electronic device 5000 includes: the processor 5010 and the memory 5020 can optionally include a power supply 5030, a display unit 5040, and an input unit 5050.
The processor 5010 is a control center of the electronic apparatus 5000, connects various components using various interfaces and lines, and performs various functions of the electronic apparatus 5000 by running or executing software programs and/or data stored in the memory 5020, thereby performing overall monitoring of the electronic apparatus 5000.
In the embodiment of the present application, the processor 5010 executes a method for real-time dynamic monitoring of an intelligent service provided by the embodiment shown in fig. 2 when calling a computer program stored in the memory 5020.
Optionally, the processor 5010 can include one or more processing units; preferably, the processor 5010 can integrate an application processor, which mainly handles operating systems, user interfaces, applications, etc., and a modem processor, which mainly handles wireless communications. It is to be appreciated that the modem processor described above may not be integrated into processor 5010. In some embodiments, the processor, memory, and memory may be implemented on a single chip, or in some embodiments, they may be implemented separately on separate chips.
The memory 5020 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, various applications, and the like; the storage data area may store data created according to the use of the electronic device 5000, and the like. Further, the memory 5020 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid state storage device.
The electronic device 5000 also includes a power supply 5030 (e.g., a battery) that provides power to the various components and that may be logically connected to the processor 5010 via a power management system to provide management of charging, discharging, and power consumption via the power management system.
The display unit 5040 may be configured to display information input by a user or information provided to the user, and various menus of the electronic device 5000, and in this embodiment of the present invention, the display unit is mainly configured to display a display interface of each application in the electronic device 5000 and objects such as texts and pictures displayed in the display interface. 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 (LCD), an Organic Light-Emitting Diode (OLED), or the like.
The input unit 5050 may be used to receive information such as numbers or characters input by a user. Input units 5050 may include touch panel 5051 as well as other input devices 5052. Among other things, the touch panel 5051, also referred to as a touch screen, may collect touch operations by a user on or near the touch panel 5051 (e.g., operations by a user on or near the touch panel 5051 using a finger, a stylus, or any other suitable object or attachment).
Specifically, the touch panel 5051 can detect a touch operation by a user, detect signals resulting from the touch operation, convert the signals into touch point coordinates, transmit the touch point coordinates to the processor 5010, and receive and execute a command transmitted from the processor 5010. In addition, the touch panel 5051 may be implemented in various types, such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. Other input devices 5052 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control keys, power on/off keys, etc.), a trackball, a mouse, a joystick, and the like.
Of course, the touch panel 5051 may cover the display panel 5041, and when the touch panel 5051 detects a touch operation thereon or thereabout, it is transmitted to the processor 5010 to determine the type of touch event, and then the processor 5010 provides a corresponding visual output on the display panel 5041 according to the type of touch event. Although in fig. 5, the touch panel 5051 and the display panel 5041 are implemented as two separate components to implement input and output functions of the electronic device 5000, in some embodiments, the touch panel 5051 and the display panel 5041 may be integrated to implement input and output functions of the electronic device 5000.
The electronic device 5000 may also include one or more sensors, such as pressure sensors, gravitational acceleration sensors, proximity light sensors, and the like. Of course, the electronic device 5000 may further include other components such as a camera according to the requirements of a specific application, and these components are not shown in fig. 5 and are not described in detail since they are not components used in this embodiment of the present application.
Those skilled in the art will appreciate that fig. 5 is merely an example of an electronic device and is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or different components.
In an embodiment of the present application, a readable storage medium has a computer program stored thereon, and when the computer program is executed by a processor, the communication device may perform the steps in the above embodiments.
For convenience of description, the above parts are described separately as modules (or units) according to functions. Of course, the functionality of the various modules (or units) may be implemented in the same one or more pieces of software or hardware when implementing the present application.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or 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, and the like) 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 application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the present application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such 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 intended to include such modifications and variations as well.
Claims (11)
1. A method for real-time dynamic monitoring of intelligent services is characterized by comprising the following steps:
presetting at least one constrained monitoring target of the intelligent service according to the user requirement, and converting the monitoring target into a time sequence logic formula;
constructing a positive and negative offset Riemann sum calculation mode based on Riemann sum operators to generate a novel signal time sequence logic quantification satisfaction calculation method;
and acquiring a time sequence signal corresponding to the monitoring target, and calculating the satisfaction degree of each constraint of the intelligent service in real time based on the novel signal time sequence logic quantitative satisfaction degree calculation method, so as to realize real-time dynamic monitoring of the intelligent service.
2. The method of claim 1, wherein the intelligent service constraints comprise at least one of the following attributes: a spatial attribute, a temporal attribute, an energy consumption attribute, and a resource restriction attribute.
3. The method according to claim 1 or 2, wherein the Riemann and calculation mode for constructing positive and negative offsets based on Riemann and operators generates a novel signal time sequence logic quantification satisfaction calculation method, which comprises the following steps:
and constructing a novel sequential logic formal semantic of the signal based on the constructed Riemann with positive and negative offsets and a calculation mode.
4. The method according to claim 3, wherein the acquiring of the time-series signal corresponding to the monitoring target and the quantitative satisfaction calculation method based on the novel signal time-series logic are used for calculating the satisfaction of each constraint of the intelligent service in real time, so as to realize the real-time dynamic monitoring of the intelligent service, and comprises:
acquiring a time sequence signal corresponding to the monitoring target and a signal interval thereof;
based on the constructed novel sequential logic formal semantics, performing signal processing under positive and negative bias on a logic formula of the monitoring target;
and calculating the satisfaction degree of each constraint of the intelligent service in real time, and realizing real-time dynamic monitoring of the intelligent service.
5. An apparatus for real-time dynamic monitoring of intelligent services, comprising:
the conversion unit is used for presetting a monitoring target of at least one constraint of intelligent service according to the user requirement and converting the monitoring target into a time sequence logic formula;
the generating unit is used for constructing a positive and negative offset Riemann and a calculation mode based on a Riemann sum operator to generate a novel signal time sequence logic quantification satisfaction calculation method;
the acquisition unit is used for acquiring a time sequence signal corresponding to the monitoring target;
and the processing unit is used for calculating the satisfaction degree of each constraint of the intelligent service in real time based on the novel signal time sequence logic quantitative satisfaction degree calculation method, and realizing real-time dynamic monitoring of the intelligent service.
6. The apparatus of claim 5, wherein the smart service constraints comprise at least one of the following attributes: a spatial attribute, a temporal attribute, an energy consumption attribute, and a resource restriction attribute.
7. The apparatus according to claim 5 or 6, wherein the generating unit is specifically configured to:
and constructing a novel sequential logic formal semantic of the signal based on the constructed Riemann with positive and negative offsets and a calculation mode.
8. The apparatus according to claim 7, wherein the obtaining unit is specifically configured to:
and acquiring a time sequence signal corresponding to the monitoring target and a signal interval thereof.
9. The apparatus according to claim 7, wherein the processing unit is specifically configured to:
based on the constructed novel sequential logic formal semantics, performing signal processing under positive and negative bias on a logic formula of the monitoring target;
and calculating the satisfaction degree of each constraint of the intelligent service in real time, and realizing real-time dynamic monitoring of the intelligent service.
10. An electronic device comprising a processor and a memory, the memory storing computer readable instructions that, when executed by the processor, perform the method of any of claims 1-4.
11. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 4.
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