CN115002801A - Method and device for dynamically unloading edge computing resources based on passive relay cooperation - Google Patents
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Abstract
The invention discloses a method and a device for dynamically unloading edge computing resources based on passive relay cooperation, which belong to the field of optimization of an edge computing unloading strategy of an industrial Internet of things, and comprise the steps of obtaining local computing time delay, data transmission rate, time delay of task unloading to a relay, time and energy consumption of task forwarding to an edge server, processing time delay of a task in the edge server and energy collected by the relay, and constructing a total time delay minimization model based on the parameters; then, analyzing the model through an iterative algorithm based on successive convex approximation to obtain an optimal unloading decision and a power division ratio under the constraints of the task such as cut-off time, unloading strategy and energy limitation; and part of the local tasks are unloaded to the relay and the edge server for calculation, so that the load pressure of the industrial terminal is reduced, and the utilization rate of network resources is improved.
Description
Technical Field
The invention relates to the field of optimization of an industrial Internet of things edge computing unloading strategy, in particular to a passive relay cooperation-based edge computing resource dynamic unloading method and device.
Background
With the rapid development of the fourth generation of industrial revolution, the industrial internet of things puts higher requirements on the real-time performance and reliability of production line tasks. The field devices are typically configured with dedicated processors, sensors, and actuators to accomplish a single task, with very limited computational and communication resources. The industrial internet of things is required to improve the overall computing capacity of the network by means of edge computing and reduce the task load of the industrial terminal. Task migration is implemented through computing offload technology to balance the computing resources of the network. However, there are some problems, such as limited resources of the edge node, too far distance between the user and the edge node, etc. In order to fully utilize network resources, cooperative communication is considered as one of effective solutions. Relay-assisted edge computing systems are employed, but battery-powered relay energy is also limited, depending on the design of the cooperative communication scheme. Therefore, the invention realizes wireless charging by adopting passive relay and introducing an energy collection technology. In order to fully utilize limited system resources, limited space-time and frequency resources of the industrial Internet of things should be reasonably distributed, and an optimal unloading strategy of a calculation task is determined, so that the method has great theoretical value and practical significance.
Disclosure of Invention
The invention aims to provide a method and a device for dynamically unloading edge computing resources based on passive relay cooperation, which can obtain an optimal unloading strategy and power division ratio under the condition of meeting the constraints of task cutoff time, unloading strategy, energy limitation and the like.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
the method for dynamically unloading the edge computing resources based on the passive relay cooperation is characterized in that the system for dynamically unloading the edge computing resources comprises the following steps: the system comprises at least one edge server, at least one cooperative relay and n field devices, wherein the field devices are communicated with the cooperative relay, the cooperative relay is communicated with the edge server, and n is greater than or equal to 1;
the edge computing resource dynamic unloading method comprises the following steps:
the method comprises the steps that a total delay minimization model is constructed by obtaining operation delay of a field device terminal, data transmission rate and task unloading delay of a cooperative relay and an edge server, time and energy consumption of the cooperative relay for forwarding an extra task to the edge server and processing delay of the task in the edge server, and energy carried in field device communication signals collected by the cooperative relay;
and performing a successive convex approximation iterative algorithm on the total delay minimization model, and then analyzing the iterated result to obtain the optimal unloading decision and power division ratio under the constraints of the task cutoff time, unloading strategy, energy limitation and the like.
The method is further improved in that: further comprising: when the task is operated at the cooperative relay terminal, the time delay and the energy consumption of the relay operation unloading task are obtained according to the frequency of the main processing unit of the relay and the calculation force required for processing the unloading task;
the operation delay of the field device end is specifically that when a task is operated at the field device end, the local operation delay is obtained according to the frequency of a main processing unit of the field device and the calculation force required by the task;
the data transmission rate and the time delay of the task to be unloaded to the cooperative relay and the edge server are specifically obtained according to the Shannon theorem when the task needs to be unloaded to the cooperative relay and the edge server;
the time and energy consumption for forwarding the extra task to the edge server by the cooperative relay and the processing delay of the task in the edge server are specifically to obtain the time and energy consumption for forwarding the task to the edge server and the processing delay of the task in the edge server when the cooperative relay forwards the extra task to the edge server;
the energy collected by the cooperative relay for receiving the communication signal of the field device is specifically energy collected by the relay according to the energy conversion efficiency, the power division ratio, the power of the field device and the channel gain when the cooperative relay receives the communication signal of the field device.
The method is further improved in that: when the task is operated at the field equipment end, a time delay model of the task in local operation is constructed, and the operation capability of the field equipment is
The time required for local computation, measured in cycles per second of the main processing unit, is as follows:
wherein L is n Size of task data volume per field device, C a Representing the number of cycles of the main processing unit required by the field device to process each byte.
The method is further improved in that: when the task is unloaded to the cooperative relay and the edge server, the data transmission rate from the field device to the cooperative relay and the data transmission rate from the relay to the edge are obtained according to the shannon theorem and respectively expressed as follows:
wherein, B 1 And B 2 Representing the bandwidth of the field device to the relay and the bandwidth of the relay to the edge server, respectively, p i Indicating the power division ratio, P, of the relay for information decoding n And P R Respectively representing the transmit power of the field device n and the transmit power of the relay,
and
watch with watch bodyIndicating the channel gain of a field device n to a relay and the channel gain of a relay to an edge server, σ 2 Representing gaussian white noise.
The method is further improved in that: according to the transmission rate of the field device n for unloading the task to the relay, the time delay of unloading the task to the cooperative relay is represented as follows:
wherein (1-x) n )L n Indicating the size of the amount of data offloaded to relay by field device n;
the time delay and energy consumption of the task of the field device n in the cooperative relay operation are expressed as follows:
wherein, C b Indicating the number of cycles of the main processing unit required to relay each byte, (1-x) n )x n，e Size of the amount of task data to be processed for the relay, f n，e Representing the computational power allocated to field device n by the cooperative relay. K b Representing coefficient of energy consumption of cooperative relaying
The method is further improved in that: the time and energy consumption for cooperative relaying to forward additional tasks to the edge server is as follows:
the acquisition latency of the task in the edge server is as follows:
wherein (1-x) n )(1-x n，e )L n Indicating the size of the task data volume, P, that the edge server needs to compute R Representing the forward power of the cooperative relay node, C d Indicating the number of cycles of the main processing unit required by the edge server to process each byte, f n，c Representing the computing power of the edge server.
The method is further improved in that: the energy collected by the cooperative relay for operation and forwarding is as follows:
where η represents the energy conversion efficiency, ρ e And ρ k Respectively representing the power division ratios of the relay for calculation and forwarding;
thus, the total latency for field device n to complete a task is represented as follows:
the method is further improved in that: constructing the total time delay minimization model as follows:
s.t.T n ≤T max ，n∈N
ρ i +ρ e +ρ k ＝1
0≤x n ≤1 0≤x n，e ≤1。
the device for dynamically unloading the edge computing resources based on the passive relay cooperation comprises at least one edge server, at least one cooperative relay and n field devices, wherein the field devices are communicated with the cooperative relay, the cooperative relay is communicated with the edge server, and n is greater than or equal to 1; the cooperative relaying includes:
the first operation module is used for obtaining the data transmission rate and the time delay of the task from the unloading to the relay according to the Shannon theorem when the task needs to be unloaded to the cooperative relay and the edge server;
the second operation module is used for obtaining the time delay and the energy consumption of the relay operation unloading task according to the frequency of the main processing unit of the relay and the calculation force required by the unloading task when the task is operated at the cooperative relay end;
the third operation module is used for acquiring the time and energy consumption for forwarding the task to the edge server and the processing time delay of the task in the edge server when the cooperative relay forwards the additional task to the edge server;
the energy collection module is used for obtaining energy collected by the relay according to the energy conversion efficiency, the power division ratio, the power of the field device and the channel gain when the cooperative relay receives the communication signal of the field device;
the unloading device further comprises:
the total delay minimization module is used for constructing a total delay minimization model based on the local operation delay, the data transmission rate, the delay for unloading the task to the relay, the time and the energy consumption for forwarding the task to the edge server, the processing delay of the task in the edge server and the energy collected by the relay;
and the result output module is used for carrying out an iterative algorithm of successive convex approximation on the total time delay minimization model, and then analyzing the iterated result to obtain the optimal unloading decision and power division ratio under the constraints of the task cutoff time, the unloading strategy, the energy limit and the like.
The dynamic unloading device of the edge computing resource based on the passive relay cooperation comprises: a memory for storing a computer program;
a processor for executing the computer program stored in the memory to implement the steps of the method for dynamically offloading edge computing resources based on passive relay cooperation as described above.
Due to the adoption of the technical scheme, the invention has the technical progress that:
1. the invention researches an industrial internet dynamic unloading method and device based on edge calculation of passive relay cooperation, solves the optimal unloading strategy and power division ratio under the constraints of task cut-off time, unloading strategy, energy limitation and the like, realizes the joint cross-layer distribution of time-space-frequency resources and reduces the time delay of a system.
2. The relay is charged through an energy collection technology, and the collected energy is further divided into energy used for calculation and energy used for forwarding through a power divider.
3. Aiming at the problems that the edge computing resources are limited, the distance between a user and an edge node is too far and the like, a relay technology is introduced to realize cooperative communication, and a part of a local task is unloaded to a relay for computing, so that the load pressure of an industrial terminal and an edge server is reduced, and the utilization rate of network resources is improved. Meanwhile, the energy collection technology is adopted to charge the passive relay, so that the problem of relay energy limitation caused by power supply of a battery is solved. And (3) solving the optimal unloading strategy and power division ratio under the constraints of the task cut-off time, the unloading strategy, the energy limitation and the like through a successive convex approximation loop iteration algorithm to minimize the time delay of the system.
Drawings
In order to more clearly illustrate the operation principle and the technical scheme used by the invention, the figures needed to be used by the operation principle and the used technology are briefly described below. It is further evident that the drawings in the following description are only some working examples of the invention, and that for a person skilled in the art, other drawings can be derived from these drawings without inventive effort.
FIG. 1 is an overall flow diagram of resource allocation for the method of the present invention;
fig. 2 is a structural diagram of the industrial internet of things.
Detailed Description
The invention is further described with reference to the accompanying drawings:
as shown in fig. 2, the industrial internet architecture of the present invention is composed of field devices, cooperative relays, and edge servers. In order to solve the problem of unbalanced computing power of equipment in a heterogeneous network, the invention adopts a computing unloading technology to unload a part of tasks of a field equipment end to a cooperative relay, and because computing resources are limited, infinite computing services cannot be provided for all equipment in the range of the field equipment end, and additional tasks need to be further unloaded to an edge server connected with the field equipment end.
As shown in fig. 1, the offloading strategy for minimizing system latency implemented by the present invention includes the following steps:
step 1: constructing a delay model of the local calculation of the task,
for the computing power of the field device itself, measured in cycles per second of the main processing unit, the time required for local computation is as follows:
wherein L is n Size of task data volume per device, C a Indicating the number of cycles of the main processing unit required by the field device to process each byte.
Step 2: according to shannon's theorem, the data transmission rate from the field device end to the relay and the data transmission rate from the relay to the edge server are calculated as follows:
wherein, B 1 And B 2 Representing the bandwidth of the field device to the relay and the bandwidth of the relay to the edge server, respectively, p i Indicating the power split ratio, P, of the relay for information decoding n And P R Respectively representing the transmit power of the field device n and the transmit power of the relay,
and
representing the field device n to the relay channel gain and the relay to the edge server channel gain, σ, respectively 2 Representing gaussian white noise.
Step 3, on the basis of the step 2, calculating the time delay from the unloading task of the field device n to the relay, as follows:
wherein (1-x) n )L n Representing the size of the amount of data offloaded to relay by device n,
the time delay and energy consumption of the task of device n in the relay calculation are expressed as follows:
wherein, C b Indicating the number of cycles of the main processing unit required for each byte to be processed by the relay, (1-x) n )x n，e L n Size of the amount of task data to be processed by the relay, f n，e Indicating the power of the relay assigned to device n, K b Representing the energy consumption coefficient of the cooperative relaying.
Step 4, calculating the time and energy consumption of the task forwarded from the relay to the edge server, as follows:
the task processing latency in the edge server is as follows:
wherein (1-x) n )(1-x n，e )L n Representing the amount of task data, P, that the edge server needs to compute R Indicating the forwarding power of the relay node, C d Indicating the number of cycles of the main processing unit required by the edge server to process each byte, f n，c Representing the computing power of the edge server.
And 5, calculating the energy collected by the relay for calculation and forwarding, wherein the energy collected by the relay for calculation and forwarding is respectively as follows:
where η represents energy conversion efficiency, ρ e And ρ k Representing the power split ratios used by the relay for calculation and forwarding, respectively.
And 6, representing the total time delay of the device n for completing the task as follows:
and 7, constructing a system time delay minimization model, which is specifically represented as follows:
s.t.T n ≤T max ，n∈N
ρ i +ρ e +ρ k ＝1
0≤x n ≤1 0≤x n，e ≤1
and 8: and solving the optimal unloading strategy and power division ratio under the constraints of task cutoff time, unloading strategy, energy limitation and the like through a successive convex approximation loop iteration algorithm, so that the time delay of the system is minimum.
The device based on the unloading method comprises the following steps:
the system comprises at least one edge server, at least one cooperative relay, n field devices, a total delay minimization module and an output module. The field device is communicated with a cooperative relay, the cooperative relay is communicated with an edge server, and n is greater than or equal to 1; the cooperative relaying includes: the device comprises a first operation module, a second operation module, a third operation module and an energy collection module.
The first operation module is used for obtaining a data transmission rate and a time delay from task unloading to relay according to Shannon theorem when the task needs to be unloaded to a cooperative relay and an edge server; the second operation module is used for obtaining the time delay and the energy consumption of the relay operation unloading task according to the frequency of the main processing unit of the relay and the calculation force required by the unloading task when the task is operated at the cooperative relay end; the third operation module is used for obtaining the time and energy consumption for forwarding the task to the edge server and the processing time delay of the task in the edge server when the cooperative relay forwards the additional task to the edge server; the energy collection module is used for obtaining energy collected by the relay according to the energy conversion efficiency, the power division ratio, the power of the field device and the channel gain when the cooperative relay receives the communication signal of the field device; the total delay minimization module is used for constructing a total delay minimization model based on the local operation delay, the data transmission rate, the delay of unloading the task to the relay, the time and energy consumption of forwarding the task to the edge server, the processing delay of the task in the edge server and the energy collected by the relay; and the result output module is used for carrying out an iterative algorithm of successive convex approximation on the total delay minimization model, and then analyzing the iterated result to obtain the optimal unloading decision and power division ratio under the constraints of the deadline of the task, the unloading strategy, energy limitation and the like.
To further embody the inventive concept, the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method as described above.
The above-mentioned embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solution of the present invention by those skilled in the art should fall within the protection scope defined by the claims of the present invention without departing from the spirit of the present invention.
Claims (10)
1. The method for dynamically unloading the edge computing resources based on the passive relay cooperation is characterized in that the system for dynamically unloading the edge computing resources comprises the following steps: the system comprises at least one edge server, at least one cooperative relay and n field devices, wherein the field devices are communicated with the cooperative relay, the cooperative relay is communicated with the edge server, and n is greater than or equal to 1;
the edge computing resource dynamic unloading method comprises the following steps:
the method comprises the steps that a total delay minimization model is constructed by obtaining operation delay of a field device terminal, data transmission rate and task unloading delay of a cooperative relay and an edge server, time and energy consumption of the cooperative relay for forwarding an extra task to the edge server and processing delay of the task in the edge server, and energy carried in field device communication signals collected by the cooperative relay;
and performing a successive convex approximation iterative algorithm on the total delay minimization model, and then analyzing the iterated result to obtain the optimal unloading decision and power division ratio under the constraints of the task cutoff time, unloading strategy, energy limitation and the like.
2. The method for dynamic offload of edge computing resources based on passive relay cooperation according to claim 1, further comprising: when the task is operated at the cooperative relay terminal, the time delay and the energy consumption of the relay operation unloading task are obtained according to the frequency of the main processing unit of the relay and the calculation force required for processing the unloading task;
the operation delay of the field device end is specifically that when a task is operated at the field device end, the local operation delay is obtained according to the frequency of a main processing unit of the field device and the calculation force required by the task;
the data transmission rate and the time delay of task unloading to the cooperative relay and the edge server are specifically obtained according to Shannon's theorem when the task needs to be unloaded to the cooperative relay and the edge server;
the time and energy consumption for forwarding the extra task to the edge server by the cooperative relay and the processing delay of the task in the edge server are specifically to obtain the time and energy consumption for forwarding the task to the edge server and the processing delay of the task in the edge server when the cooperative relay forwards the extra task to the edge server;
the energy collected by the relay of the cooperative relay receiving the communication signal of the field device is specifically the energy collected by the relay according to the energy conversion efficiency, the power division ratio, the power of the field device and the channel gain when the cooperative relay receives the communication signal of the field device.
3. The method for dynamically unloading edge computing resources based on passive relay cooperation according to claim 1 or 2, wherein when the task is operated at the field device end, a time delay model of the task operated locally is constructed, and the operation capability of the field device is that
The time required for local computation, measured in cycles per second of the main processing unit, is as follows:
wherein L is n Size of task data volume per field device, C a Representing the number of cycles of the main processing unit required by the field device to process each byte.
4. The method for dynamically unloading edge computing resources based on passive relay cooperation according to claim 3, wherein when the task is unloaded to the cooperative relay and the edge server, the data transmission rate from the field device to the cooperative relay and the data transmission rate from the relay to the edge are obtained according to Shannon's theorem and are respectively expressed as follows:
wherein, B 1 And B 2 Representing the bandwidth of the field device to the relay and the bandwidth of the relay to the edge server, respectively, p i Indicating the power division ratio, P, of the relay for information decoding n And P R Respectively representing the transmit power of the field device n and the transmit power of the relay,
and
representing the field device n to the relayed channel gain, and the relayed to the edge server channel gain, σ, respectively 2 Representing gaussian white noise.
5. The method for dynamically unloading edge computing resources based on passive relay cooperation according to claim 4, wherein the time delay for unloading the task to the cooperative relay is represented as follows according to the transmission rate of the field device n for unloading the task to the relay:
wherein (1-x) n )L n Indicating the size of the amount of data offloaded to relay by field device n;
the time delay and energy consumption of the task of the field device n in the cooperative relay operation are expressed as follows:
wherein, C b Indicating the number of cycles of the main processing unit required to relay each byte, (1-x) n )x n，e Size of the amount of task data to be processed by the relay, f n，ｅ Indicating the power of the cooperative relay assigned to the field device n, K b Representing the energy consumption coefficient of the cooperative relaying.
6. The method for dynamically offloading edge computing resources based on passive relay cooperation according to claim 5, wherein the time and energy consumption for cooperative relay to forward additional tasks to the edge server are as follows:
the acquisition latency of the task in the edge server is as follows:
wherein (1-x) n )(1-x n，e )L n Indicating the size of the task data volume, P, that the edge server needs to compute R Representing the forward power of the cooperative relaying, C d Indicating the number of cycles of the main processing unit required by the edge server to process each byte, f n，c Indicating the computing power of the edge server.
7. The method for dynamically offloading edge computing resources based on passive relay cooperation according to claim 6, wherein the cooperative relay collects energy for computation and forwarding, and the energy collected by the relay for computation and forwarding is as follows:
where η represents the energy conversion efficiency, ρ e And ρ k Respectively representing the power division ratios of the relay for calculation and forwarding;
thus, the total latency for field device n to complete a task is represented as follows:
8. the method of claim 7, wherein the total latency minimization model is constructed by:
s.t.T n ≤T max ，n∈N
ρ i +ρ e +ρ k ＝1
0≤x n ≤1 0≤x n，e ≤1。
9. the device for dynamically unloading the edge computing resources based on the passive relay cooperation is characterized by comprising at least one edge server, at least one cooperative relay and n field devices, wherein the field devices are communicated with the cooperative relay, the cooperative relay is communicated with the edge server, and n is greater than or equal to 1; the cooperative relaying includes:
the first operation module is used for obtaining the data transmission rate and the time delay of the task from the unloading to the relay according to the Shannon theorem when the task needs to be unloaded to the cooperative relay and the edge server;
the second operation module is used for obtaining the time delay and the energy consumption of the relay operation unloading task according to the frequency of the main processing unit of the relay and the calculation force required by the unloading task when the task is operated at the cooperative relay end;
the third operation module is used for acquiring the time and energy consumption for forwarding the task to the edge server and the processing time delay of the task in the edge server when the cooperative relay forwards the additional task to the edge server;
the energy collection module is used for obtaining energy collected by the relay according to the energy conversion efficiency, the power division ratio, the power of the field device and the channel gain when the cooperative relay receives the communication signal of the field device;
the unloading device further comprises:
the total time delay minimizing module is used for constructing a total time delay minimizing model based on the local operation time delay, the data transmission rate, the time delay of unloading the task to the relay, the time and energy consumption of forwarding the task to the edge server, the processing time delay of the task in the edge server and the energy collected by the relay;
and the result output module is used for carrying out an iterative algorithm of successive convex approximation on the total time delay minimization model, and then analyzing the iterated result to obtain the optimal unloading decision and power division ratio under the constraints of the task cutoff time, the unloading strategy, the energy limit and the like.
10. The device for dynamically unloading the edge computing resources based on the passive relay cooperation is characterized by comprising the following steps:
a memory for storing a computer program;
a processor for executing a computer program stored in the memory to implement the steps of the passive relay cooperation based edge computing resource dynamic offload method of any of claims 1 to 8.
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