CN114895976B - Service security calculation unloading method and device - Google Patents

Service security calculation unloading method and device Download PDF

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CN114895976B
CN114895976B CN202210474078.1A CN202210474078A CN114895976B CN 114895976 B CN114895976 B CN 114895976B CN 202210474078 A CN202210474078 A CN 202210474078A CN 114895976 B CN114895976 B CN 114895976B
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task
processed
energy consumption
terminal node
time delay
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CN114895976A (en
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姚继明
吴鹏
郭云飞
朱亮
陈端云
王玮
虞跃
林彧茜
刘世栋
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State Grid Smart Grid Research Institute Co ltd
State Grid Corp of China SGCC
State Grid Fujian Electric Power Co Ltd
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State Grid Smart Grid Research Institute Co ltd
State Grid Corp of China SGCC
State Grid Fujian Electric Power Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/445—Program loading or initiating
    • G06F9/44594—Unloading
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/602—Providing cryptographic facilities or services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061—Partitioning or combining of resources
    • G06F9/5072—Grid computing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2209/00—Indexing scheme relating to G06F9/00
    • G06F2209/50—Indexing scheme relating to G06F9/50
    • G06F2209/502—Proximity
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The invention provides a business security calculation unloading method and a device, wherein the method comprises the following steps: determining tasks to be processed of each terminal node; respectively determining a first execution time delay and first energy consumption when each terminal node executes a task to be processed, and a second execution time delay and second energy consumption when each task to be processed is unloaded to an edge server for execution, wherein the second execution time delay and the second energy consumption respectively comprise additional execution time delay and additional energy consumption when encryption operation and decryption operation are carried out on the task to be processed; establishing an optimization target by combining the first execution time delay, the first energy consumption, the second execution time delay and the second energy consumption; solving the optimization target to obtain a scheduling scheme of each task to be processed; and controlling each terminal node to execute the task to be processed according to the scheduling scheme, or unloading the task to be processed to the edge server. By executing the invention, the unloading decision and the safety decision of the task to be processed of each terminal node can be adjusted on the basis of ensuring the safety of the task to be processed.

Description

Service security calculation unloading method and device
Technical Field
The invention relates to the technical field of business data processing, in particular to a business security calculation unloading method and device.
Background
The deep integration of the energy Internet and 5G promotes the digital development of the power grid and improves the intelligent level of the power grid. As the number of bottom business terminals is continuously increased and intelligent inspection robots are popularized, data transmission is continuously increased. If all data are sent to the cloud for processing, time delay and energy consumption are increased, but with the development of mobile edge calculation and the open capability characteristic of 5G, the problems can be solved by using an edge calculation local offloading and shunting technology based on 5G user plane subsidence. The tasks of the local equipment are transmitted to the corresponding edge servers for calculation through calculation unloading, so that the problems of prolonged task processing and unreasonable resource allocation of cloud computing are solved.
Introducing mobile edge computing and 5G network capability opening, while bringing better terminal monitoring capability, higher power quality of service and better power communication network to smart grid, brings a series of problems in terms of security: communication security is made more difficult to secure due to the distributed deployment of edge servers. In an edge server system of multiple power terminal nodes, a malicious eavesdropper may submerge, and in the process that the terminal nodes send data to the edge server, the eavesdropper falsifies the data of a user, so that the power communication cannot normally operate, and related power privacy information is eavesdropped. Therefore, how to improve task execution efficiency based on consideration of data security is a problem to be solved.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the defect that the data security is not considered when the task execution efficiency is improved in the prior art, so as to provide a business security calculation unloading method and a business security calculation unloading device.
The first aspect of the invention provides a business security calculation unloading method, which comprises the following steps: determining tasks to be processed of each terminal node; respectively determining a first execution time delay and first energy consumption when each terminal node executes a corresponding task to be processed; determining a second execution time delay and second energy consumption when each task to be processed is unloaded to the edge server for execution, wherein the second execution time delay comprises additional execution time delay when encryption operation and decryption operation are carried out on the task to be processed, and the second energy consumption comprises additional energy consumption when the encryption operation and the decryption operation are carried out on the task to be processed; establishing an optimization target by combining the first execution time delay, the first energy consumption, the second execution time delay and the second energy consumption; solving an optimization target to obtain a scheduling scheme of each task to be processed; and controlling each terminal node to execute the task to be processed according to the scheduling scheme, or unloading the task to be processed to the edge server.
Optionally, in the service security computing and unloading method provided by the invention, the second execution time delay of the task to be processed is obtained through the following steps: determining the transmission delay of the terminal node for sending the task to be processed to the edge server according to the data size of the task to be processed and the uplink data rate of the terminal node to which the task to be processed belongs; determining the calculation time delay of the edge server according to the CPU cycle number required by the edge server to execute the task to be processed and the calculation capacity of the edge server allocated to the terminal node to which the task to be processed belongs; determining additional execution time delay according to the total number of CPU cycles required by the terminal node to which the task to be processed belongs when encrypting the data of the task to be processed, the computing power of the terminal node to which the task to be processed belongs, the total number of CPU cycles required by the edge server when decrypting the data of the task to be processed, and the computing power distributed by the edge server to the terminal node to which the task to be processed belongs; and determining the second execution delay according to the sum of the transmission delay, the calculation delay and the additional execution delay.
Optionally, in the service security calculation unloading method provided by the invention, the second energy consumption of the task to be processed is obtained through the following steps: determining the transmission delay of the terminal node for sending the task to be processed to the edge server according to the data size of the task to be processed and the uplink data rate of the terminal node to which the task to be processed belongs; determining unloading energy consumption according to the product of the uplink transmission power and the transmission delay of the terminal node to which the task to be processed belongs; determining additional energy consumption according to the total number of CPU cycles required when the terminal node of the task to be processed encrypts the data of the task to be processed and the energy consumed by each CPU cycle of the terminal node of the task to be processed; the second energy consumption is determined from the sum of the unloading energy consumption and the additional energy consumption.
Optionally, in the service security calculation unloading method provided by the present invention, an optimization objective is established by combining a first execution delay, a first energy consumption, a second execution delay and a second energy consumption, including: determining the terminal execution overhead of each task to be processed by combining the task delay weight, the energy consumption weight, the first execution delay and the first energy consumption of each task to be processed; determining the server execution overhead of each task to be processed by combining the task delay weight, the energy consumption weight, the second execution delay and the second energy consumption of each task to be processed; and establishing an optimization target according to the terminal execution overhead and the server execution overhead.
Optionally, in the service security calculation unloading method provided by the invention, the optimization target is as follows:
wherein N represents the number of terminal nodes, a n,s = {0,1}, when a n,s When=0, it means that the terminal node performs the calculation task, when a n,s When=1, it means that the end node offloads the computing task to the edge server,representing the overhead of the execution of the server,representing terminal execution overhead, S represents edge servers, S represents edge server set, C n = {0,1}, when C n When=0, the nth terminal node does not encrypt the data of the task to be processed, when C n When=1, the nth terminal node encrypts the data of the task to be processed and transmits the encrypted data to the edge server, and the n terminal node is added with the data>Representing the second energy consumption->Represents the first energy consumption, r n Representing the uplink data rate of the nth terminal node, B representing the transmission channel bandwidth, +.>Representing the computing power allocated by the edge server s to the nth end node, and F represents the upper limit of the edge server CPU capacity.
The second aspect of the present invention provides a service security computing and unloading device, comprising: the task determining module is used for determining tasks to be processed of each terminal node; the first overhead calculation module is used for respectively determining a first execution time delay and a first energy consumption when each terminal node executes a corresponding task to be processed; the second overhead calculation module is used for respectively determining second execution time delay and second energy consumption when each task to be processed is unloaded to the edge server for execution, wherein the second execution time delay comprises additional execution time delay when encryption operation and decryption operation are carried out on the task to be processed, and the second energy consumption comprises additional energy consumption when encryption operation and decryption operation are carried out on the task to be processed; the optimization target building module is used for building an optimization target by combining the first execution time delay, the first energy consumption, the second execution time delay and the second energy consumption; the optimization target solving module is used for solving the optimization target to obtain a scheduling scheme of each task to be processed; and the task execution module is used for controlling each terminal node to execute the task to be processed according to the scheduling scheme or unloading the task to be processed to the edge server.
Optionally, in the service security computing unloading device provided by the present invention, the second overhead computing module includes: the transmission delay calculation sub-module is used for determining the transmission delay of the terminal node for sending the task to be processed to the edge server according to the data size of the task to be processed and the uplink data rate of the terminal node to which the task to be processed belongs; the computing time delay computing sub-module is used for determining the computing time delay of the edge server according to the CPU cycle number required by the edge server to execute the task to be processed and the computing capacity distributed by the edge server for the terminal node to which the task to be processed belongs; the additional execution time delay calculation sub-module is used for determining additional execution time delay according to the total number of CPU cycles required by the terminal node to which the task to be processed belongs when encrypting the data of the task to be processed, the calculation capability of the terminal node to which the task to be processed belongs, the total number of CPU cycles required by the edge server when decrypting the data of the task to be processed, and the calculation capability of the edge server distributed to the terminal node to which the task to be processed belongs; and the execution time delay calculation sub-module is used for determining a second execution time delay according to the sum of the transmission time delay, the calculation time delay and the additional execution time delay.
Optionally, in the service security computing unloading device provided by the present invention, the second overhead computing module includes: the transmission delay calculation sub-module is used for determining the transmission delay of the terminal node for sending the task to be processed to the edge server according to the data size of the task to be processed and the uplink data rate of the terminal node to which the task to be processed belongs; the unloading energy consumption calculation submodule is used for determining unloading energy consumption according to the product of the uplink transmission power and the transmission delay of the terminal node to which the task to be processed belongs; the additional energy consumption calculation submodule is used for determining additional energy consumption according to the total number of CPU cycles required when the terminal node to which the task to be processed belongs encrypts the data of the task to be processed and the energy consumed by the terminal node to which the task to be processed belongs in each CPU cycle; and the energy consumption calculation submodule is used for determining the second energy consumption according to the sum of the unloading energy consumption and the additional energy consumption.
A third aspect of the present invention provides a computer apparatus comprising: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to perform the business security computing offload method as provided in the first aspect of the present invention.
A fourth aspect of the present invention provides a computer readable storage medium having stored thereon computer instructions for causing a computer to perform a business safety calculation offload method as provided in the first aspect of the present invention.
The technical scheme of the invention has the following advantages:
the invention provides a service security calculation unloading method and a service security calculation unloading device, and aims to obtain an optimal unloading and resource allocation strategy in an edge calculation system of a plurality of terminal nodes through a proposed improved algorithm so as to minimize the calculation time delay and the energy consumption of the whole system. In the invention, the optimization target comprises an unloading and resource allocation strategy function and constraint conditions, the unloading and resource allocation strategy function is divided into two parts of local calculation and edge server unloading calculation, the two parts are established by a first execution time delay, a first energy consumption, a second execution time delay and a second energy consumption, and the unloading decision and the safety decision of the terminal nodes to the task to be processed can be properly adjusted by comprehensively considering the calculation capacity and the service requirement of different terminal nodes according to the self, the calculation capacity of the edge server and the system communication resource on the basis of ensuring the data safety of the task to be processed by solving the optimization target.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a multi-user single-edge server computing offload system in accordance with an embodiment of the present invention;
FIG. 2 is a flowchart of a specific example of a business security computing offload method in accordance with an embodiment of the present invention;
FIG. 3 is a schematic block diagram of a specific example of a business security computing offload device in accordance with an embodiment of the present invention;
fig. 4 is a schematic block diagram of a specific example of a computer device in an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, it should be noted that the terms "first," "second," and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In addition, the technical features of the different embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
In the multi-user single edge server computing offload system model shown in FIG. 1, the model includes multiplePersonal terminal nodeAnd an edge server S, wherein after each terminal node generates a task to be processed, the processing modes of the task to be processed are divided into three modes: firstly, the terminal node calculates the collected data locally in time; secondly, all terminal nodes unload tasks to an adjacent edge server for calculation, namely, all users unload tasks; and thirdly, each terminal node selectively uninstalls according to the computing resources and the communication resources of the edge server, which is called user part uninstallation, so that the burden of individual terminal nodes can be lightened, other real-time data can be continuously collected, and the computing resources and the communication resources of the whole system can be fully utilized. In order to improve the execution efficiency of a task to be processed on the basis of guaranteeing data security, the embodiment of the invention provides a business security calculation unloading method which can be executed in an edge server, as shown in fig. 2, and comprises the following steps:
Step S11: and determining the task to be processed of each terminal node.
In an alternative embodiment, each terminal node may send information of each task to be processed to an edge server, and the edge server determines an execution subject of each task to be processed.
In an alternative embodiment, the task information of the task to be processed is represented as { beta } by a binary group n ,δ n And }, where beta n Representing the total number of CPU cycles, delta, required to execute a task to be processed n Indicating the size of the data volume of the task to be processed. The system model proposed by the embodiment of the invention is carried out in a quasi-static condition, and the number of terminal nodes is kept unchanged during unloading.
Step S12: and respectively determining a first execution time delay and first energy consumption when each terminal node executes the corresponding task to be processed.
In an alternative embodiment, the first execution delay is calculated according to the total number of CPU cycles required for calculating the task to be processed and the computing power of the terminal node:
wherein beta is n The total number of CPU cycles required to perform the task to be processed,representing the computational power of the end node, the computational power unit of the end node is expressed as CPU cycles per second.
In an alternative embodiment, the first energy consumption is calculated from the total number of CPU cycles required to perform the task to be processed and the energy consumed by the terminal node per CPU cycle:
Wherein, xi n Is a constant and represents the energy consumed by the terminal node in each CPU cycle, beta n The total number of CPU cycles required to execute the task to be processed.
Step S13: and respectively determining a second execution time delay and second energy consumption when each task to be processed is unloaded to the edge server for execution, wherein the second execution time delay comprises an additional execution time delay when encryption operation and decryption operation are carried out on the task to be processed, and the second energy consumption comprises an additional energy consumption when the encryption operation and the decryption operation are carried out on the task to be processed.
In consideration of the risk of data leakage in the process of unloading the task to be processed to the edge server, in the embodiment of the invention, after the terminal node encrypts the data of the task to be processed locally, the terminal node transmits the encrypted data to the edge server, and the edge server decrypts the encrypted data and then executes the task to be processed after receiving the encrypted data.
In an alternative embodiment, the types of tasks to be processed are different, the security requirements are also different, when the tasks to be processed have security requirements, the additional time delay and the additional energy consumption of the tasks to be processed are determined according to the time required for carrying out encryption operation and decryption operation on the data of the tasks to be processed, and when the tasks to be processed have no security requirements, the additional time delay and the additional energy consumption of the tasks to be processed are zero.
Step S14: and establishing an optimization target by combining the first execution time delay, the first energy consumption, the second execution time delay and the second energy consumption.
The business security calculation unloading method provided by the embodiment of the invention aims to obtain the optimal unloading and resource allocation strategy in the edge calculation systems of a plurality of terminal nodes through the proposed improved algorithm so as to minimize the calculation time delay and the energy consumption of the whole system. In the embodiment of the invention, the optimization target comprises an unloading and resource allocation strategy function and constraint conditions, the unloading and resource allocation strategy function is divided into two parts of local calculation and edge server unloading calculation, the two parts are established by a first execution time delay, a first energy consumption, a second execution time delay and a second energy consumption, and the unloading decision and the safety decision of the terminal nodes to the task to be processed can be properly adjusted by comprehensively considering the calculation capacity and the service requirement of different terminal nodes according to the self and the calculation capacity of the edge server and the system communication resource on the basis of ensuring the data safety of the task to be processed by solving the optimization target.
Step S15: and solving the optimization target to obtain a scheduling scheme of each task to be processed.
In an alternative embodiment, the solution to the optimization objective in the embodiments of the present invention is to solve the problem of offloading and resource allocation policy, which is a 0-1 integer linear programming problem, which is an NP-hard problem when the data volume is large in a security-based computational offloading scheme. In order to further solve the problem, in the embodiment of the invention, the optimal approximate solution is obtained by solving the optimization target based on the quantum evolution algorithm, and the scheduling scheme of each task to be processed is determined through the optimal approximate solution.
Step S16: and controlling each terminal node to execute the task to be processed according to the scheduling scheme, or unloading the task to be processed to the edge server.
In an alternative embodiment, if it is determined that the terminal node needs to offload the task to be processed to the edge server according to the scheduling scheme, it is further determined whether the terminal node needs to encrypt the data of the task to be processed according to the scheduling scheme.
According to the business security calculation unloading method provided by the embodiment of the invention, after the first execution time delay and the first energy consumption of each terminal node when locally executing the task to be processed are determined, and the second execution time delay and the second energy consumption of the task to be processed when being unloaded to the edge server for execution are respectively, an optimization target is established according to the first execution time delay, the first energy consumption, the second execution time delay and the second energy consumption, and the execution strategy of each terminal node to be processed is determined through solving the target.
In an optional embodiment, in the service security computing and unloading method provided by the embodiment of the present invention, the second execution delay of the task to be processed is obtained by:
firstly, determining the transmission delay of the terminal node for sending the task to be processed to the edge server according to the data size of the task to be processed and the uplink data rate of the terminal node to which the task to be processed belongs:
wherein delta n Representing the data size of the task to be processed corresponding to the nth terminal node, r n Representing the uplink data rate of the nth terminal node.
The uplink data rate of the nth terminal node is calculated by the following formula:
wherein B represents transmission channel bandwidth, P n Represents the nth terminal node m n Uplink transmission power of (N) 0 Representing the channel noise power density, g represents the transmission channel gain.
Secondly, determining the computing time delay of the edge server according to the CPU cycle number required by the edge server to execute the task to be processed and the computing capacity allocated by the edge server to the terminal node to which the task to be processed belongs:
wherein beta is n Represents the number of CPU cycles required by the edge server to execute the task to be processed corresponding to the nth end node,representing the computing power allocated by the edge server to the terminal node (nth terminal node) to which the task to be processed belongs.
Then, determining an additional execution delay according to the total number of CPU cycles required by the terminal node to which the task to be processed belongs when encrypting the data of the task to be processed, the computing power of the terminal node to which the task to be processed belongs, the total number of CPU cycles required by the edge server when decrypting the data of the task to be processed, and the computing power allocated by the edge server to the terminal node to which the task to be processed belongs:
wherein,represents the encryption latency under security model, < +.>Represents decryption latency under security model, D n Represents the total number of CPU cycles required for encrypting the task to be processed of the nth terminal node, E n Represents the total number of CPU cycles required for decrypting the task to be processed of the nth terminal node, for example>Representing the computing power allocated by the edge server to the terminal node to which the task to be processed belongs (nth terminal node), is +.>Representing the computational power of the nth end node.
Finally, determining a second execution delay according to the sum of the transmission delay, the calculation delay and the additional execution delay:
in an alternative embodiment, the second execution delay may include, in addition to the transmission delay, the calculation delay, and the additional execution delay, a delay when the edge server returns the execution result of the task to be processed to the terminal node. However, when the data size of the execution result of the task to be processed is far smaller than the data size of the task to be processed and the downlink rate of the edge server is higher than the uplink rate of the terminal node, the delay when the edge server returns the execution result of the task to be processed to the terminal node may be ignored.
In an optional embodiment, in the service security computing and unloading method provided by the embodiment of the present invention, the second energy consumption of the task to be processed is obtained through the following steps:
firstly, determining the transmission delay of the terminal node for sending the task to be processed to the edge server according to the data size of the task to be processed and the uplink data rate of the terminal node to which the task to be processed belongs:
wherein delta n Representing the data size of the task to be processed corresponding to the nth terminal node, r n Representing the uplink data rate of the nth terminal node.
Secondly, determining unloading energy consumption according to the product of the uplink transmission power and the transmission delay of the terminal node to which the task to be processed belongs:
wherein P is n Indicating the uplink transmission power of the nth terminal node,representing the transmission delay of the nth terminal node to send the task to be processed to the edge server.
Then, determining additional energy consumption according to the total number of CPU cycles required by the terminal node of the task to be processed when encrypting the data of the task to be processed and the energy consumed by each CPU cycle of the terminal node of the task to be processed:
wherein D is n Represents the total number of CPU cycles required for encrypting the task to be processed of the nth terminal node, E n Representing the total number of CPU cycles, ζ, required for decrypting the task to be processed of the nth terminal node n Representing the energy consumed by the end node per CPU cycle.
Finally, determining a second energy consumption according to the sum of the unloading energy consumption and the additional energy consumption:
in an alternative embodiment, the second energy consumption may include, in addition to the unloading energy consumption and the additional energy consumption, energy consumption when the edge server returns the execution result of the task to be processed to the terminal node. However, when the data size of the execution result of the task to be processed is far smaller than the data size of the task to be processed and the downlink rate of the edge server is higher than the uplink rate of the terminal node, the energy consumption when the edge server returns the execution result of the task to be processed to the terminal node can be ignored.
In an alternative embodiment, the step S14 specifically includes the following steps:
firstly, determining the terminal execution overhead of each task to be processed by combining the task delay weight, the energy consumption weight, the first execution delay and the first energy consumption of each task to be processed:
wherein, gamma= {0,1} represents the energy consumption weight and task delay weight of the task to be processed. Different tasks to be processed are set to different targets due to different demands of the different tasks to be processed. For example, when γ=0, it means that the task to be processed needs to be processed as soon as possible, and the delay requirement is high; when γ=1, the amount of data representing the task to be processed is large, and the required energy consumption is high.
Then, determining the server execution overhead of each task to be processed by combining the task delay weight, the energy consumption weight, the second execution delay and the second energy consumption of each task to be processed:
and finally, establishing an optimization target according to the terminal execution overhead and the server execution overhead.
Constraint C 1 Representing binary computation offload decisions for the terminal nodes; constraint C 2 Representing a binary security decision of the terminal node; constraint C 3 Ensuring that the total energy consumption of remote execution of all terminal nodes does not exceed the total energy consumption of local execution, wherein the total energy consumption of remote execution is the total energy consumption when all tasks to be processed are offloaded to an edge server for execution; constraint C 4 Representing channel bandwidth capacity between the end node and the edge server; constraint C 5 Representing the upper limit of the edge server CPU capacity.
Wherein N represents the number of terminal nodes, a n,s = {0,1}, when a n,s When=0, it means that the terminal node performs the calculation task, when a n,s When=1, it means that the end node offloads the computing task to the edge server,representing the overhead of the execution of the server,representing terminal execution overhead, S represents edge servers, S represents edge server set, C n = {0,1}, when C n When=0, the nth terminal node does not encrypt the data of the task to be processed, when C n When=1, the nth terminal node encrypts the data of the task to be processed and transmits the encrypted data to the edge server, and the n terminal node is added with the data>Representing the second energy consumption->Represents the first energy consumption, r n Representing the uplink data rate of the nth terminal node, B representing the transmission channel bandwidth, +.>Representing the computing power allocated by the edge server s to the nth end node, and F represents the upper limit of the edge server CPU capacity.
In an alternative embodiment, the process of calculating the optimization target by adopting the quantum evolutionary algorithm specifically comprises the following steps:
1) Setting the current iteration number K to 0, setting the maximum iteration number K, initializing a Q (K) unloading decision matrix, and initializing unloading decisions of each terminal node to be
2) For all terminal nodes, the task requirements and the computing power { beta } of each terminal node will be calculated within a given time interval t n, δ n, D n, E n ,P n And transferred to the edge server.
3) And calculating the uplink data rate of each user by using an uplink data rate formula.
4) And using a formula provided by a calculation unloading and resource allocation strategy optimization problem, and observing the state of Q (k) through a make subroutine to determine an optimal calculation unloading decision value of each terminal node, wherein the optimal calculation unloading decision value is represented by an optimal solution matrix P (t).
5) The overall cost corresponding to P (k) is revised and evaluated for P (k) through a repair subroutine (constraint condition), so that the total cost of the whole system in terms of energy and time is minimized.
6) Storing the optimal solution in P (K) into B (K), and executing the following steps if the current iteration number is smaller than the maximum iteration number K:
the current iteration number k is increased by 1;
observing the Q (k-1) state through a make sub-algorithm to determine P (k);
evaluating the minimum value of the overall overhead corresponding to P (k);
updating Q (k) with an update subroutine;
storing the optimal solutions in P (k) and B (k-1) into B (k), and setting the optimal solution in B (k) as B;
and determining a scheduling scheme of each task to be processed according to the current optimal solution until the current iteration number is greater than or equal to the maximum iteration number K.
The embodiment of the invention provides a business security calculation unloading device, as shown in fig. 3, comprising:
the task determining module 21 is configured to determine a task to be processed of each terminal node, and details of the task determining module are described in the above embodiment in step S11, which is not described herein.
The first overhead calculating module 22 is configured to determine the first execution delay and the first energy consumption when each terminal node executes the corresponding task to be processed, and the detailed content is referred to the description of step S12 in the above embodiment, which is not repeated herein.
The second overhead calculating module 23 is configured to determine a second execution delay and a second energy consumption when each task to be processed is offloaded to the edge server for execution, where the second execution delay includes an additional execution delay when the task to be processed performs an encryption operation and a decryption operation, and the second energy consumption includes an additional energy consumption when the task to be processed performs an encryption operation and a decryption operation, and details of the step S13 are described in the above embodiments, and are not repeated herein.
The optimization objective establishing module 24 is configured to establish an optimization objective in combination with the first execution delay, the first energy consumption, the second execution delay, and the second energy consumption, and the details of which are described in the above embodiment in step S14 are not repeated here.
The optimization target solving module 25 is configured to solve the optimization target to obtain a scheduling scheme of each task to be processed, and details of the description of step S15 in the foregoing embodiment are not described herein. The task execution module 26 is configured to control each terminal node to execute a task to be processed according to a scheduling scheme, or offload the task to be processed to an edge server, and details of the task execution module are described in the above embodiment in step S16, which is not described herein again.
In an alternative embodiment, the second overhead calculation module 23 comprises:
the transmission delay calculation sub-module is configured to determine a transmission delay of the terminal node to send the task to be processed to the edge server according to the data size of the task to be processed and an uplink data rate of the terminal node to which the task to be processed belongs, and details of the transmission delay are described in the above method embodiments and are not described herein.
The computing time delay computing sub-module is configured to determine the computing time delay of the edge server according to the number of CPU cycles required by the edge server to execute the task to be processed and the computing capability of the edge server allocated to the terminal node to which the task to be processed belongs, and details of the computing time delay of the edge server are described in the above method embodiments and are not repeated herein.
The additional execution time delay calculation sub-module is configured to determine an additional execution time delay according to a total number of CPU cycles required when the terminal node to which the task to be processed belongs encrypts data of the task to be processed, a calculation capability of the terminal node to which the task to be processed belongs, a total number of CPU cycles required when the edge server decrypts data of the task to be processed, and a calculation capability of the edge server allocated to the terminal node to which the task to be processed belongs, and details are described in the above method embodiments and are not repeated herein.
The execution time delay calculation sub-module is configured to determine the second execution time delay according to the sum of the transmission time delay, the calculation time delay, and the additional execution time delay, and details of the execution time delay calculation sub-module are described in the above method embodiments, and are not described herein.
Optionally, in the service security computing unloading device provided in the embodiment of the present invention, the second overhead computing module 23 includes:
the transmission delay calculation sub-module is configured to determine a transmission delay of the terminal node to send the task to be processed to the edge server according to the data size of the task to be processed and an uplink data rate of the terminal node to which the task to be processed belongs, and details of the transmission delay are described in the above method embodiments and are not described herein.
The unloading energy consumption calculating submodule is configured to determine unloading energy consumption according to a product of uplink transmission power and transmission delay of the terminal node to which the task to be processed belongs, and details of the unloading energy consumption are described in the above method embodiments and are not described herein.
The extra energy consumption calculating submodule is used for determining extra energy consumption according to the total number of CPU cycles required when the terminal node to which the task to be processed belongs encrypts the data of the task to be processed and the energy consumed by each CPU cycle of the terminal node to which the task to be processed belongs, and details are described in the embodiment of the method and are not repeated herein.
The energy consumption calculating submodule is configured to determine the second energy consumption according to the sum of the unloading energy consumption and the additional energy consumption, and details of the description in the above method embodiments are not repeated herein.
The embodiment of the present invention provides a computer device, as shown in fig. 4, which mainly includes one or more processors 31 and a memory 32, and in fig. 4, one processor 31 is taken as an example.
The computer device may further include: an input device 33 and an output device 34.
The processor 31, the memory 32, the input device 33 and the output device 34 may be connected by a bus or otherwise, for example in fig. 4.
The processor 31 may be a central processing unit (Central Processing Unit, CPU). The processor 31 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination thereof. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The memory 32 may include a storage program area that may store an operating system, at least one application program required for functions, and a storage data area; the storage data area may store data created from the use of the business security computing offload device, etc. In addition, the memory 32 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 32 may optionally include memory located remotely from processor 31, which may be connected to the business safety computing offload device via a network. The input device 33 may receive a user entered calculation request (or other numeric or character information) and generate key signal inputs related to the business safety calculation offload device. The output device 34 may include a display device such as a display screen for outputting the calculation result.
The embodiment of the invention provides a computer readable storage medium, which stores computer instructions, and the computer storage medium stores computer executable instructions, and the computer executable instructions can execute the business security calculation unloading method in any of the method embodiments. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), or a Solid State Drive (SSD); the storage medium may also comprise a combination of memories of the kind described above.
It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. While still being apparent from variations or modifications that may be made by those skilled in the art are within the scope of the invention.

Claims (8)

1. A business security computing offload method, comprising:
Determining tasks to be processed of each terminal node;
respectively determining a first execution time delay and first energy consumption when each terminal node executes a corresponding task to be processed;
determining a second execution time delay and second energy consumption when each task to be processed is unloaded to an edge server for execution, wherein the second execution time delay comprises additional execution time delay when encryption operation and decryption operation are carried out on the task to be processed, and the second energy consumption comprises additional energy consumption when the encryption operation and the decryption operation are carried out on the task to be processed;
establishing an optimization target by combining the first execution time delay, the first energy consumption, the second execution time delay and the second energy consumption;
solving the optimization targets to obtain a scheduling scheme of each task to be processed;
controlling each terminal node to execute the task to be processed according to the scheduling scheme, or unloading the task to be processed to the edge server;
establishing an optimization target by combining the first execution time delay, the first energy consumption, the second execution time delay and the second energy consumption, wherein the optimization target comprises the following steps:
determining the terminal execution overhead of each task to be processed by combining the task delay weight, the energy consumption weight, the first execution delay and the first energy consumption of each task to be processed;
Determining the server execution overhead of each task to be processed by combining the task delay weight, the energy consumption weight, the second execution delay and the second energy consumption of each task to be processed;
establishing the optimization target according to the terminal execution overhead and the server execution overhead;
the optimization targets are as follows:
wherein N represents the number of terminal nodes, a n,s = {0,1}, when a n,s When=0, it means that the terminal node performs the calculation task, when a n,s When=1, it means that the end node offloads the computing task to the edge server,representing the overhead of the execution of the server,representing terminal execution overhead, S represents edge servers, S represents edge server set, C n = {0,1}, when C n When=0, the nth terminal node does not encrypt the data of the task to be processed, when C n When=1, the nth terminal node encrypts the data of the task to be processed and transmits the encrypted data to the edge server, and the n terminal node is added with the data>Representing the second energy consumption->Represents the first energy consumption, r n Representing the uplink data rate of the nth terminal node, B representing the transmission channel bandwidth, +.>Representing the computing power allocated by the edge server s to the nth end node, and F represents the upper limit of the edge server CPU capacity.
2. The traffic safety computation offload method of claim 1, wherein the second execution delay of the task to be processed is obtained by:
determining the transmission delay of the terminal node for transmitting the task to be processed to the edge server according to the data size of the task to be processed and the uplink data rate of the terminal node to which the task to be processed belongs;
determining the computation time delay of the edge server according to the CPU cycle number required by the edge server to execute the task to be processed and the computation capacity distributed by the edge server to the terminal node to which the task to be processed belongs;
determining the additional execution time delay according to the total number of CPU cycles required by the terminal node to which the task to be processed belongs when encrypting the data of the task to be processed, the computing capacity of the terminal node to which the task to be processed belongs, the total number of CPU cycles required by the edge server to decrypt the data of the task to be processed, and the computing capacity allocated by the edge server to the terminal node to which the task to be processed belongs;
and determining the second execution time delay according to the sum of the transmission time delay, the calculation time delay and the additional execution time delay.
3. The business safety calculation offloading method of claim 1, wherein the second energy consumption of the task to be processed is obtained by:
determining the transmission delay of the terminal node for transmitting the task to be processed to the edge server according to the data size of the task to be processed and the uplink data rate of the terminal node to which the task to be processed belongs;
determining unloading energy consumption according to the product of the uplink transmission power of the terminal node to which the task to be processed belongs and the transmission delay;
determining the extra energy consumption according to the total number of CPU cycles required by the terminal node to which the task to be processed belongs when encrypting the data of the task to be processed and the energy consumed by the terminal node to which the task to be processed belongs in each CPU cycle;
the second energy consumption is determined from the sum of the unloading energy consumption and the additional energy consumption.
4. A business safety computing offload device, comprising:
the task determining module is used for determining tasks to be processed of each terminal node;
the first overhead calculation module is used for respectively determining a first execution time delay and a first energy consumption when each terminal node executes a corresponding task to be processed;
The second overhead calculation module is used for respectively determining a second execution time delay and a second energy consumption when each task to be processed is unloaded to the edge server for execution, wherein the second execution time delay comprises an additional execution time delay when encryption operation and decryption operation are carried out on the task to be processed, and the second energy consumption comprises an additional energy consumption when the encryption operation and the decryption operation are carried out on the task to be processed;
the optimization target building module is used for building an optimization target by combining the first execution time delay, the first energy consumption, the second execution time delay and the second energy consumption;
the optimization target solving module is used for solving the optimization target to obtain a scheduling scheme of each task to be processed;
the task execution module is used for controlling each terminal node to execute the task to be processed according to the scheduling scheme or unloading the task to be processed to the edge server;
the optimization target building module is specifically configured to determine a terminal execution overhead of each task to be processed by combining a task delay weight, an energy consumption weight, a first execution delay and a first energy consumption of each task to be processed; determining the server execution overhead of each task to be processed by combining the task delay weight, the energy consumption weight, the second execution delay and the second energy consumption of each task to be processed; establishing an optimization target according to the terminal execution overhead and the server execution overhead;
The optimization targets are as follows:
wherein N represents the number of terminal nodes, a n,s = {0,1}, when a n,s When=0, it means that the terminal node performs the calculation task, when a n,s When=1, it means that the end node offloads the computing task to the edge server,representing the overhead of the execution of the server,representing terminal execution overhead, S represents edge servers, S represents edge server set, C n = {0,1}, when C n When=0, the nth terminal node does not encrypt the data of the task to be processed, when C n When=1, the nth terminal node encrypts the data of the task to be processed and transmits the encrypted data to the edge server, and the n terminal node is added with the data>Representing the second energy consumption->Represents the first energy consumption, r n Representing the uplink data rate of the nth terminal node, B representing the transmission channel bandwidth, +.>Representing the computing power allocated by the edge server s to the nth end node, and F represents the upper limit of the edge server CPU capacity.
5. The traffic safety computation offload device of claim 4, wherein the second overhead computation module comprises:
the transmission delay calculation sub-module is used for determining the transmission delay of the terminal node for sending the task to be processed to the edge server according to the data size of the task to be processed and the uplink data rate of the terminal node to which the task to be processed belongs;
The computing time delay computing sub-module is used for determining the computing time delay of the edge server according to the CPU cycle number required by the edge server to execute the task to be processed and the computing capacity distributed by the edge server for the terminal node to which the task to be processed belongs;
an extra execution time delay calculation sub-module, configured to determine the extra execution time delay according to a total number of CPU cycles required when the terminal node to which the task to be processed belongs encrypts the data of the task to be processed, a calculation capability of the terminal node to which the task to be processed belongs, a total number of CPU cycles required when the edge server decrypts the data of the task to be processed, and a calculation capability allocated by the edge server to the terminal node to which the task to be processed belongs;
and the execution time delay calculation sub-module is used for determining the second execution time delay according to the sum of the transmission time delay, the calculation time delay and the additional execution time delay.
6. The traffic safety computation offload device of claim 4, wherein the second overhead computation module comprises:
the transmission delay calculation sub-module is used for determining the transmission delay of the terminal node for sending the task to be processed to the edge server according to the data size of the task to be processed and the uplink data rate of the terminal node to which the task to be processed belongs;
The unloading energy consumption calculation submodule is used for determining unloading energy consumption according to the product of the uplink transmission power of the terminal node to which the task to be processed belongs and the transmission delay;
the additional energy consumption calculation submodule is used for determining the additional energy consumption according to the total number of CPU cycles required when the terminal node to which the task to be processed belongs encrypts the data of the task to be processed and the energy consumed by the terminal node to which the task to be processed belongs in each CPU cycle;
and the energy consumption calculation submodule is used for determining the second energy consumption according to the sum of the unloading energy consumption and the additional energy consumption.
7. A computer device, comprising:
at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to perform the business safety computation offload method of any of claims 1-3.
8. A computer readable storage medium storing computer instructions for causing the computer to perform the business safety computation offload method of any of claims 1-3.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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CN113965961A (en) * 2021-10-27 2022-01-21 中国科学院计算技术研究所 Method and system for unloading edge computing tasks in Internet of vehicles environment
CN114281544A (en) * 2021-12-28 2022-04-05 全球能源互联网研究院有限公司 Electric power task execution method and device based on edge calculation

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2022011755A1 (en) * 2020-07-15 2022-01-20 南通大学 Computing unloading method and system for energy efficiency optimization in in-vehicle edge computing network
CN113965961A (en) * 2021-10-27 2022-01-21 中国科学院计算技术研究所 Method and system for unloading edge computing tasks in Internet of vehicles environment
CN114281544A (en) * 2021-12-28 2022-04-05 全球能源互联网研究院有限公司 Electric power task execution method and device based on edge calculation

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