CN113934472A - Task unloading method, device, equipment and storage medium - Google Patents
Task unloading method, device, equipment and storage medium Download PDFInfo
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Abstract
The disclosure relates to a task unloading method, a task unloading device, a task unloading equipment and a storage medium. The task unloading method specifically comprises the following steps: determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device; the communication adaptation degree is used for representing the overlapping degree of a first communication area of the edge device and a second communication area of the task unloading device in the process that the edge device moves from the starting point of the predicted track to the end point of the predicted track; determining the edge device with the maximum communication adaptation degree as a target edge device; and unloading the target task to the target edge device. According to the embodiment of the disclosure, the task unloading device can unload the target task to the target edge device with the largest communication adaptation degree, so that the risk of communication interruption between the target edge device and the target edge device in the moving process is reduced, and the target edge device is favorable for sending the calculation result of the target task to the task unloading device in time.
Description
Technical Field
The present disclosure relates to the field of communications technologies, and in particular, to a method, an apparatus, a device, and a storage medium for task offloading.
Background
The edge computing technology is widely applied to various scenes such as intelligent wearable equipment, video stream analysis, language voice processing, wireless sensors of the Internet of things, augmented reality technology and the like by virtue of the characteristics of low time delay, low bandwidth cost, high safety, high elasticity and the like.
For example, based on the edge computing technology, the gateway may offload the computing task to the peripheral edge devices, so that the edge devices replace the gateway to complete the computing task, and after the computing result is obtained, the computing result is fed back to the gateway. However, most of the existing task offloading strategies are directed to fixed-location edge devices, and when an edge device is movable relative to a gateway, problems such as communication interruption between the gateway and the edge device may occur. Therefore, providing a task offloading strategy for a movable edge device is a key issue that needs to be solved urgently by those skilled in the art.
Disclosure of Invention
To solve the technical problem or at least partially solve the technical problem, the present disclosure provides a task offloading method, apparatus, device, and storage medium.
In a first aspect, an embodiment of the present disclosure provides a task offloading method, where the method includes:
determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device; the communication adaptation degree is the overlapping degree of a first communication area of the edge device and a second communication area of the task unloading device in the process that the edge device moves from the starting point of the predicted track to the end point of the predicted track;
determining the edge device with the maximum communication adaptation degree as a target edge device;
unloading the target task to the target edge device;
the method for determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device comprises the following steps:
determining the overlapping area of a first communication area of the edge device and a second communication area of the task unloading device when the edge device moves to each track point on the predicted track;
determining communication adaptation degree according to the overlapping area corresponding to each track point;
determining communication adaptation degree according to the overlapping area corresponding to each track point, comprising:
carrying out weight summation on the overlapping areas corresponding to the track points to determine the communication adaptation degree;
the weight of the corresponding overlapping area is smaller when the time difference between the predicted time corresponding to the track point and the predicted time corresponding to the starting point of the predicted track is larger.
In a second aspect, an embodiment of the present disclosure provides a task offloading device, including:
the communication adaptation degree determining module is used for determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device; the communication adaptation degree is used for representing the overlapping degree of a first communication area of the edge device and a second communication area of the task unloading device in the process that the edge device moves from the starting point of the predicted track to the end point of the predicted track;
the target edge device determining module is used for determining the edge device with the maximum communication adaptation degree as the target edge device;
the task unloading module is used for unloading the target task to the target edge device;
wherein, the communication adaptation degree determining module comprises:
the overlap area determining submodule is used for determining the overlap area of a first communication area of the edge device and a second communication area of the task unloading device when the edge device moves to the track point aiming at each track point on the predicted track;
the communication adaptation degree determining submodule is used for determining the communication adaptation degree according to the overlapping area corresponding to each track point;
the communication adaptation degree determining submodule is specifically used for performing weight summation on the overlapping areas corresponding to the track points to determine the communication adaptation degree;
the weight of the corresponding overlapping area is smaller when the time difference between the predicted time corresponding to the track point and the predicted time corresponding to the starting point of the predicted track is larger.
In a third aspect, an embodiment of the present disclosure provides a task offloading device, including:
a processor;
a memory for storing executable instructions;
wherein the processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the method according to the first aspect.
In a fourth aspect, the present disclosure provides a computer-readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the method according to the first aspect is implemented.
Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has the following advantages:
according to the task unloading method, the task unloading device, the task unloading equipment and the storage medium, the communication adaptation degree of each edge device relative to the task unloading equipment can be determined according to the predicted track of each edge device, wherein the communication adaptation degree is used for representing the overlapping degree of a first communication area of the edge device and a second communication area of the task unloading equipment in the process that the edge device moves from the starting point of the predicted track to the end point of the predicted track, the edge device with the maximum communication adaptation degree is determined to be the target edge device, and the target task is unloaded to the target edge device. Therefore, the task unloading equipment can unload the target task to the target edge equipment with the maximum communication adaptation degree, the risk of communication interruption of the target edge equipment and the target edge equipment in the moving process is reduced, and the target edge equipment is favorable for sending the calculation result of the target task to the task unloading equipment in time.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present disclosure, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a flowchart of a task offloading method provided in an embodiment of the present disclosure.
Fig. 2 shows that the first communication area of an edge device and the second communication area of a task offloading device provided by an embodiment of the present disclosure are at t1Schematic of a time of day.
Fig. 3 shows that the first communication area of the edge device and the second communication area of the task offloading device are at t according to the embodiment of the disclosure2Schematic of a time of day.
Fig. 4 shows that the first communication area of the edge device and the second communication area of the task offloading device are at t according to the embodiment of the disclosurenSchematic of a time of day.
Fig. 5 is a schematic diagram of a task unloading device and a peripheral edge device thereof according to an embodiment of the disclosure.
Fig. 6 is a flowchart illustrating a task offloading process according to an embodiment of the disclosure.
Fig. 7 is a schematic structural diagram of a task offloading device according to an embodiment of the disclosure.
Fig. 8 is a schematic structural diagram of a task offloading device in an embodiment of the disclosure.
Detailed Description
In order that the above objects, features and advantages of the present disclosure may be more clearly understood, aspects of the present disclosure will be further described below. It should be noted that the embodiments and features of the embodiments of the present disclosure may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced in other ways than those described herein; it is to be understood that the embodiments disclosed in the specification are only a few embodiments of the present disclosure, and not all embodiments.
Fig. 1 is a flowchart of a task offloading method provided by an embodiment of the present disclosure, which may be performed by a task offloading device. The task off-load device may be understood as an exemplary computing-enabled device such as a tablet, laptop, desktop, etc. The method can take the edge device with the maximum communication adaptability as the target edge device and unload the target task to the target edge device. As shown in fig. 1, the method provided by this embodiment includes the following steps:
and S110, determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device.
In the embodiment of the present disclosure, before determining the communication suitability of an edge device with respect to a task off-load device according to a predicted trajectory of the edge device, the task off-load device needs to obtain the predicted trajectory of the edge device.
Specifically, the edge device is a device located at the periphery of the task offloading device and having a computing function, and may be, for example, a tablet computer, a notebook computer, a desktop computer, a mobile phone, and the like, but is not limited thereto.
Specifically, the predicted trajectory is a prediction of a running trajectory of the edge device within a first preset time period from a next time instant of the current time instant. The specific duration of the first preset time period can be set by a person skilled in the art according to actual conditions, and is not limited herein.
Alternatively, the duration of the first preset time period may be an integral multiple of the calculation time required by the target task, for example, the duration of the first preset time period may be twice the calculation time required by the target task, but is not limited thereto.
In some embodiments, the edge device may periodically sample its own location information and send the sampled location information to the task off-load device. The task offload device may predict a predicted trajectory of the edge device based on position information collected for at least one sampling period of the edge device.
In one example, the location information may include a longitude and a latitude, at which point the task off-load device may perform a markov chain calculation of the longitude and latitude acquired for the current sampling period and the longitude and latitude acquired for the at least one historical sampling period to obtain the predicted trajectory. For example, the task off-load device may perform markov chain calculations on the longitude and latitude acquired for the current sampling period (i-th sampling period, i being a positive integer greater than 2) and the longitude and latitude acquired for two historical sampling periods (i-1 th sampling period and i-2 th sampling period) to derive the predicted trajectory.
In another example, the position information of the edge device may further include a speed and an azimuth, and at this time, the task offloading device may calculate the speed and the azimuth acquired in the current sampling period and the speed and the azimuth acquired in at least one historical sampling period through a motion recursion function to obtain the predicted trajectory.
In other embodiments, the edge device may periodically sample its own location information and predict its own predicted trajectory based on the location information collected for at least one sampling period. The predicted trajectory is then sent to the task off-load device.
It should be noted that the specific implementation of the edge device predicting its own predicted trajectory according to the position information acquired in the at least one sampling period may be the same as the specific implementation of the task unloading device predicting its own predicted trajectory according to the position information acquired in the at least one sampling period, and details are not described here again.
The communication adaptation degree is used for representing the overlapping degree of a first communication area of the edge device and a second communication area of the task unloading device in the process that the edge device moves from the starting point of the predicted track to the end point of the predicted track.
Specifically, the edge device has a first communication radius, and an area defined by a circle with the first communication radius as a radius is the first communication area of the edge device. Similarly, the task unloading device has a second communication radius, and an area defined by a circle with the second communication radius as the radius is the second communication area of the task unloading device with the task unloading device as the center. When the first communication area and the second communication area are overlapped, the edge device and the task unloading device can communicate with each other; when there is no overlap between the first communication area and the second communication area, the communication between the edge device and the task off-load device is interrupted.
Specifically, when the edge device moves from the starting point of the predicted trajectory to the ending point of the predicted trajectory, the relative positional relationship between the edge device and the task unloading device changes continuously, and the degree of overlap between the first communication area of the edge device and the second communication area of the task unloading device changes accordingly.
Exemplarily, fig. 2 shows that the first communication area of the edge device and the second communication area of the task offloading device are at t1Schematic of a time of day. Fig. 3 shows that the first communication area of the edge device and the second communication area of the task offloading device are at t according to the embodiment of the disclosure2Schematic of a time of day. Fig. 4 shows that the first communication area of the edge device and the second communication area of the task offloading device are at t according to the embodiment of the disclosurenSchematic of a time of day. As shown in fig. 2, at t1At this point, the edge device 210 is located at a track point a1 (i.e., the starting point) of the predicted track 230, and there is an overlap between the first communication area 211 of the edge device 210 and the second communication area 221 of the task off-load device 220, and the area of the overlap is S (1). As shown in fig. 3, at t2At this point, the edge device 210 is located at the track point a2 of the predicted track 230, and there is an overlap between the first communication area 211 of the edge device 210 and the second communication area 221 of the task off-load device 220, and the area of overlap of the shaded portion is S (2). As shown in fig. 4, at tnAt the moment, the edge device 210 is located at An point of the predicted trajectory 230, and there is An overlap between the first communication area 211 of the edge device 210 and the second communication area 221 of the task off-load device 220, and the overlapping area of the shaded portion is s (n).
Based on this, optionally, for each track point on the predicted track, determining an overlapping area of a first communication area of the edge device and a second communication area of the task unloading device when the edge device moves onto the track point; and determining the communication adaptation degree according to the overlapping area corresponding to each track point.
In one example, determining the communication adaptation degree according to the overlapping area corresponding to each track point may include: and directly summing the overlapping areas corresponding to the track points to obtain the communication adaptation degree.
For example, as shown in fig. 2, the predicted track 230 includes N (N is a positive integer) track points, the overlapping area of the shaded portion corresponding to the nth track point is s (N), and then the communication adaptability of the edge device 210 corresponding to the predicted track 230 with respect to the task unloading device is determined according to the overlapping area s (N)
。
And S120, determining the edge device with the maximum communication adaptation degree as a target edge device.
Specifically, a plurality of edge devices are generally present around the task unloading device, and the communication suitability of each edge device with respect to the task unloading device can be obtained through S110. And sequencing the communication adaptation degrees of the plurality of edge devices in a descending order, and taking the edge device positioned at the head as a target edge device.
Exemplarily, fig. 5 is a schematic structural diagram of a task unloading device and a peripheral edge device thereof according to an embodiment of the present disclosure. Referring to fig. 5, there are three edge devices around the task offloading device 220, which are the first edge device 201, the second edge device 202, and the third edge device 203, respectively, and the communication suitability of the three edge devices with respect to the task offloading device can be obtained through S110, and the communication suitability of the three edge devices 210 is sorted from large to small as follows: the communication adaptation degree of the first edge device 201 with respect to the task off-load device 220 > the communication adaptation degree of the third edge device 203 with respect to the task off-load device 220 > the communication adaptation degree of the second edge device 202 with respect to the task off-load device 220, and at this time, the first edge device 201 may be regarded as a target edge device.
And S130, unloading the target task to the target edge device.
Specifically, the target task may be any task to be calculated. For example, the target task may be an optimal route planning task for a certain vehicle from a departure place to a destination, a monthly expenditure statistic task for a certain user, and the like, but is not limited thereto.
The task unloading method provided by the embodiment of the disclosure can determine the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device, wherein the communication adaptation degree is used for representing the overlapping degree of a first communication area of the edge device and a second communication area of the task unloading device in the process that the edge device moves from the starting point of the predicted track to the end point of the predicted track, determining the edge device with the maximum communication adaptation degree as a target edge device, and unloading the target task to the target edge device. Therefore, the task unloading equipment can unload the target task to the target edge equipment with the maximum communication adaptation degree, the risk of communication interruption of the target edge equipment and the target edge equipment in the moving process is reduced, and the target edge equipment is favorable for sending the calculation result of the target task to the task unloading equipment in time.
In other embodiments of the present disclosure, determining the communication adaptation degree according to the overlapping area corresponding to each track point may further include: carrying out weight summation on the overlapping areas corresponding to the track points to determine the communication adaptation degree; the weight of the corresponding overlapping area is smaller when the time difference between the predicted time corresponding to the track point and the predicted time corresponding to the starting point of the predicted track is larger.
In particular, communication adaptation degree
Wherein, s (n) is an overlapping area corresponding to the nth track point, and a (n) is a weight of the overlapping area corresponding to the nth track point.
Specifically, the specific value of a (n) can be set by those skilled in the art according to practical situations, and is not limited herein. Alternatively,
wherein, tnAnd the predicted time corresponding to the nth track point.
It can be understood that the more backward (i.e. later than the current time) the prediction time corresponding to a certain track point is, the lower the prediction accuracy rate is, i.e. the lower the probability that the edge device moves to the track point at the prediction time is. Therefore, the overlapping areas corresponding to the track points are subjected to weight summation, so that the weight of the overlapping area corresponding to the track point with high prediction accuracy is larger, and the finally calculated communication adaptation degree is more accurate.
In some embodiments of the present disclosure, determining a communication suitability of each edge device with respect to the task off-load device according to the predicted trajectory of each edge device includes: acquiring a first predicted track and a second predicted track of each edge device; determining a first communication adaptation degree of each edge device relative to the task unloading device according to the first predicted track of each edge device; determining a second communication adaptation degree of each edge device relative to the task unloading device according to the second predicted track of each edge device; and for each edge device, respectively carrying out weight summation on the first communication adaptation degree and the second communication adaptation degree of the edge device, and determining the communication adaptation degree of the edge device.
Specifically, the task unloading device may predict a predicted trajectory of the edge device according to the first type of location information acquired in at least one sampling period of the edge device, so as to obtain a first predicted trajectory.
Alternatively, the first type of location information may include a longitude and a latitude. In this case, the specific determination manner of the first predicted track may refer to the foregoing, and is not described herein again.
At this time, the first communication suitability K1 may be calculated by the following formula:
，
. Wherein S1(n) is the overlapping area corresponding to the nth track point on the first predicted track, a1(n) is the weight of the overlapping area corresponding to the nth track point on the first predicted track, and t1nAnd the predicted time corresponding to the nth track point on the first predicted track is obtained.
Specifically, the task unloading device may also predict the predicted trajectory of the edge device according to the second type of location information acquired in at least one sampling period of the edge device, so as to obtain a second predicted trajectory.
Alternatively, the second type of location information may include velocity and azimuth. In this case, the specific determination manner of the second predicted track may refer to the foregoing, and is not described herein again.
At this time, the second communication suitability K2 can be calculated by the following formula:
，
. Wherein the content of the first and second substances,
is the overlapping area corresponding to the nth track point on the second predicted track, a2(n) is the weight of the overlapping area corresponding to the nth track point on the second predicted track, t2nAnd the predicted time corresponding to the nth track point on the second predicted track is obtained.
The communication adaptation degree K can be calculated by the following formula:
. Where α is a weight of the first communication adaptation degree K1 and β is a weight of the second communication adaptation degree K2. The specific values of α and β can be set by those skilled in the art according to practical situations, and are not limited herein.
Optionally, when the overlap ratio of the historically predicted first predicted track and the corresponding real track is greater than the overlap ratio of the historically predicted second predicted track and the corresponding real track, determining that α > β, otherwise, α < β. Therefore, the weight of the communication adaptation degree component obtained according to the predicted track which is more accurate in prediction is larger, and the accuracy of the communication adaptation degree obtained through final calculation is improved.
It should be noted that, the edge device may also perform periodic sampling on its own location information, where the location information includes a first type of location information and a second type of location information; the edge device predicts a first predicted trajectory of the edge device according to the first type of position information acquired in the at least one sampling period, and predicts a second predicted trajectory of the edge device according to the second type of position information acquired in the at least one sampling period. The first predicted trajectory and the second predicted trajectory are then transmitted to the task off-load device.
It can be understood that the first predicted trajectory and the second predicted trajectory, which are predicted by adopting different types of position information and different modes, have respective advantages and can mutually make up for the defects of the other side, so that the first communication adaptation degree and the second communication adaptation degree of the prediction device are respectively determined according to the first predicted trajectory and the second predicted trajectory, and then the first communication adaptation degree and the second communication adaptation degree are subjected to weight addition to obtain the communication adaptation degree, which is beneficial to improving the accuracy of the finally calculated communication adaptation degree.
In some further embodiments of the present disclosure, before determining that the edge device with the largest communication adaptation degree is the target edge device, the task offloading method further includes: determining the continuous overlapping time of the first communication area of the edge device and the second communication area of the task unloading device during the process that the edge device moves from the starting point of the corresponding predicted track to the end point of the predicted track; taking the edge device with the continuous overlapping time larger than a preset time threshold value as an alternative edge device; wherein, determining the edge device with the maximum communication adaptation degree as the target edge device comprises: and determining the candidate edge device with the maximum communication adaptation degree as the target edge device.
Specifically, the preset time threshold may be set by a person skilled in the art according to the calculation time required by the target task, and is not limited herein.
Specifically, among a plurality of edge devices around the task unloading device, an edge device whose continuous overlapping time is greater than a preset time threshold is used as an alternative edge device (i.e., in an alternative list), and other edge devices are not in the alternative list. Therefore, the continuous overlapping time of the overlapping of the first communication area of the candidate edge device and the second communication area of the task unloading device in the candidate list is longer, namely the time for the candidate edge device and the task unloading device to keep continuous communication is longer, the probability of communication interruption of the candidate edge device and the task unloading device is lower, and the target edge device is favorable for uploading the calculation result to the task unloading device in time after the calculation result is calculated for the target task.
Optionally, the preset time threshold is greater than the target task required computation time setting. In this way, the finally determined continuous overlapping time of the overlapping of the first communication area of the target edge device and the second communication area of the task unloading device is longer than the calculation time required by the target task, and when the target edge device calculates the calculation result for the target task, the calculation result can be immediately sent to the task unloading device.
Optionally, when there is no edge device that satisfies that the continuous overlapping time is greater than the preset time threshold among the plurality of edge devices around the task unloading device, the edge device that satisfies the following condition may be taken as the candidate edge device: taking the current time as an initial time, enabling a first communication area of the edge device and a second communication area of the task unloading device to be overlapped for at least a second preset time period, and taking the time corresponding to the time required by the backward lapse of the current time for calculating the target task as the initial time, enabling the first communication area of the edge device and the second communication area of the task unloading device to be overlapped for at least a third preset time period; determining the edge device with the largest communication adaptation degree as the target edge device may include: and determining the candidate edge device with the maximum communication adaptation degree as the target edge device. Therefore, the task unloading device can timely unload the target task to the target edge device, and the target edge device can immediately send the calculation result to the task unloading device when the calculation result is calculated for the target task.
Specifically, the specific values of the second preset time period and the third preset time period may be set by those skilled in the art according to actual situations, and are not limited herein.
In some further embodiments of the present disclosure, before determining that the edge device with the largest communication adaptation degree is the target edge device, the task offloading method further includes: when detecting that the edge device does not perform the calculation task currently, taking the edge device as a standby edge device; wherein, determining the edge device with the maximum communication adaptation degree as the target edge device comprises: and determining the candidate edge device with the maximum communication adaptation degree as the target edge device.
Specifically, among a plurality of edge devices around the task offloading device, an edge device that does not perform the calculation task at the current time is used as an alternative edge device (i.e., in the alternative list), and the other edge devices are not in the alternative list. Therefore, after receiving the target task, the candidate edge devices in the candidate list can immediately start to calculate the target task, so that the calculated calculation result is uploaded to the task unloading device as soon as possible, and the waiting time from the task unloading device to the receiving of the calculation result is shortened.
In still other embodiments of the present disclosure, after offloading the target task to the target edge device, the task offloading method further includes: determining a deviation value between the real track and the predicted track of the target edge equipment according to the real track of the target edge equipment; and when the deviation value is detected to be larger than the preset deviation threshold value, returning to execute the operation of determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device.
Specifically, after receiving the target task, the target edge device may further send the periodically collected position information to the task unloading device in real time, so that the task unloading device may determine the real track of the target edge device according to the position information. Alternatively, the location information may include a longitude and a latitude, but is not limited thereto.
In some embodiments, the specific determination of the deviation value between the real track and the predicted track of the target edge device may include: calculating the distance between the coordinates (longitude and latitude) of the predicted track at the moment and the coordinates (longitude and latitude) of the real track at the moment aiming at each moment to obtain the deviation distance corresponding to the moment; calculating the sum of the deviation distances corresponding to all the moments to obtain the Euclidean distance; and calculating the Euclidean distance and the length of the real track to obtain a deviation value of the real track and the predicted track.
Specifically, the specific value of the preset deviation threshold can be set by a person skilled in the art according to the actual situation, and is not limited herein. For example, the preset deviation threshold may be 60%.
Specifically, when the deviation value is detected to be greater than the preset deviation threshold value, it indicates that the deviation between the predicted trajectory and the real trajectory is large, that is, the accuracy of the predicted trajectory is low, and the actual communication adaptation degree of the target edge device selected based on the predicted trajectory with low accuracy relative to the task offloading device may be low.
Specifically, when the deviation value is detected to be smaller than or equal to the preset deviation threshold value, it is indicated that the deviation between the predicted track and the real track is small, at this time, whether a calculation result uploaded by the target edge device is received or not can be judged, and if yes, the task is ended; if not, continuing to return to the operation of determining the deviation value of the real track and the predicted track of the target edge equipment according to the real track of the target edge equipment.
It can be understood that there is usually a deviation between the predicted trajectory and the actual trajectory, and when the deviation between the predicted trajectory and the actual trajectory is large, the accuracy and reliability of the communication suitability determined according to the predicted trajectory are low, and a problem that the current target edge device cannot upload a calculation result calculated for the target task to the task offloading device may occur, and the target task can be offloaded again to a new target edge device with the best communication suitability by re-determining the target edge device.
It should be noted that, when the predicted trajectory includes a first predicted trajectory and a second predicted trajectory, a first deviation value between the real trajectory of the target edge device and the first predicted trajectory and a second deviation value between the real trajectory and the second predicted trajectory may be determined according to the real trajectory of the target edge device; and when the first deviation value and/or the second deviation value is detected to be larger than a preset deviation threshold value, returning to execute the operation of determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device.
In still other embodiments of the present disclosure, after offloading the target task to the target edge device, the task offloading method further includes: determining accumulated deviation time of a first communication area of the target edge device and a second communication area of the task unloading device, wherein the accumulated deviation time is not overlapped; and when the accumulated deviation time is detected to be larger than the preset deviation time threshold, returning to execute the operation of determining the communication adaptation degree of each edge device relative to the task unloading device according to the corresponding predicted track of the edge device.
Specifically, the accumulated deviation time is a total length of time that the first communication area of the target edge device and the second communication area of the task off-load device do not overlap after the target task is off-loaded onto the target edge device.
Correspondingly, after the target task is unloaded to the target edge device, when the first communication area of the target edge device and the second communication area of the task unloading device are not overlapped each time in the process that the target edge device moves along the real track, the duration of the non-overlapping each time is recorded, and the duration of the non-overlapping each time is added, so that the accumulated deviation time can be obtained.
Specifically, the specific value of the preset deviation time threshold may be set by a person skilled in the art according to the actual situation, and is not limited herein.
Optionally, the preset deviation time threshold is a product of a time period corresponding to the predicted trajectory and a first preset ratio. The specific value of the first preset ratio can be set by a person skilled in the art according to practical situations, and is not limited herein, for example, the first preset ratio can be 40%.
Specifically, when the accumulated deviation time is greater than the preset deviation time threshold, it indicates that the deviation between the predicted trajectory and the real trajectory is large, at this time, the operation of determining the communication adaptation degree of each edge device relative to the task offloading device according to the predicted trajectory of each edge device may be returned to be executed, so as to reselect the target edge device, and the task offloading device may offload the calculation task to a new target edge device.
Specifically, when the accumulated deviation time is detected to be less than or equal to the preset deviation time threshold, it is indicated that the deviation between the predicted track and the real track is small, at this time, whether a calculation result uploaded by the target edge device is received or not can be judged, and if yes, the task is ended; if not, continuing to return to execute the operation of determining that the accumulated deviation time which is not overlapped exists between the first communication area of the edge device and the second communication area of the task unloading device according to the real track of the target edge device.
It can be understood that there is usually a deviation between the predicted trajectory and the actual trajectory, and when the deviation between the predicted trajectory and the actual trajectory is large, the accuracy and reliability of the communication suitability determined according to the predicted trajectory are low, and a problem that the current target edge device cannot upload a calculation result calculated for the target task to the task offloading device may occur, and the target task can be offloaded again to a new target edge device with the best communication suitability by re-determining the target edge device.
Hereinafter, a task offloading method provided by the embodiments of the present disclosure will be described in detail based on a specific example.
Fig. 6 is a flowchart illustrating a task offloading process according to an embodiment of the disclosure.
S610, acquiring a first predicted track and a second predicted track of each edge device.
S620, determining a first communication adaptation degree of each edge device relative to the task unloading device according to the first predicted track of each edge device.
And S630, determining a second communication adaptation degree of each edge device relative to the task unloading device according to the second predicted track of each edge device.
And S640, respectively carrying out weight summation on the first communication adaptation degree and the second communication adaptation degree of the edge device aiming at each edge device, and determining the communication adaptation degree of the edge device.
S650, determining the continuous overlapping time of the first communication area of the edge device and the second communication area of the task unloading device in the process that the edge device moves from the starting point of the corresponding predicted track to the end point of the predicted track.
And S660, taking the edge device with the continuous overlapping time larger than the preset time threshold as a candidate edge device.
S670, determining the candidate edge device with the maximum communication adaptation degree as the target edge device.
And S680, unloading the target task to the target edge device.
And S690, judging whether a calculation result uploaded by the target edge device is received. If so, the process is terminated, otherwise, S710 is executed.
S710, according to the real track of the target edge device, determining a first deviation value between the real track of the target edge device and the first predicted track and a second deviation value between the real track and the second predicted track.
S720, judging whether at least one of the first deviation value and the second deviation value is larger than a preset deviation threshold value. If yes, the process returns to step S610, otherwise, step S730 is performed.
And S730, determining accumulated deviation time which is not overlapped between the first communication area of the target edge device and the second communication area of the task unloading device according to the real track of the target edge device.
And S740, judging whether the accumulated deviation time is larger than a preset deviation time threshold value. If so, the process returns to step S610, otherwise, the process returns to step S690.
Fig. 7 is a schematic structural diagram of a task offloading device according to an embodiment of the present disclosure, where the task offloading device may be understood as the task offloading device or a part of functional modules in the task offloading device. As shown in fig. 7, the task unloading apparatus 700 includes:
a communication suitability determining module 710, configured to determine, according to the predicted trajectory of each edge device, a communication suitability of each edge device with respect to the task unloading device; the communication adaptation degree is the overlapping degree of a first communication area of the edge device and a second communication area of the task unloading device in the process that the edge device moves from the starting point of the predicted track to the end point of the predicted track;
a target edge device determining module 720, configured to determine that the edge device with the largest communication adaptation degree is a target edge device;
a task offloading module 730, configured to offload a target task to the target edge device;
the communication adaptation degree determining module 710 may include:
the overlap area determining submodule is used for determining the overlap area of a first communication area of the edge device and a second communication area of the task unloading device when the edge device moves to the track point aiming at each track point on the predicted track;
and the communication adaptation degree determining submodule is used for determining the communication adaptation degree according to the overlapping area corresponding to each track point.
The communication adaptation degree determining submodule can be specifically used for performing weight summation on the overlapping area corresponding to each track point to determine the communication adaptation degree;
the weight of the corresponding overlapping area is smaller when the time difference between the predicted time corresponding to the track point and the predicted time corresponding to the starting point of the predicted track is larger.
The task offloading device provided by the embodiment of the disclosure can determine the communication adaptation degree of each edge device relative to the task offloading device according to the predicted track of each edge device, where the communication adaptation degree is used to represent the overlapping degree of a first communication area of the edge device and a second communication area of the task offloading device in the process that the edge device moves from the starting point of the predicted track to the end point of the predicted track, and determine the edge device with the largest communication adaptation degree as a target edge device, and offload the target task to the target edge device. Therefore, the task unloading equipment can unload the target task to the target edge equipment with the maximum communication adaptation degree, the risk of communication interruption of the target edge equipment and the target edge equipment in the moving process is reduced, and the target edge equipment is favorable for sending the calculation result of the target task to the task unloading equipment in time.
In still other embodiments of the present disclosure, the communication suitability determination module 710 may include:
the track acquisition submodule is used for acquiring a first predicted track and a second predicted track of each edge device;
the first communication adaptation degree determining sub-module is used for determining the first communication adaptation degree of each edge device relative to the task unloading device according to the first predicted track of each edge device;
the second communication adaptation degree determining submodule is used for determining second communication adaptation degrees of the edge devices relative to the task unloading device according to the second predicted tracks of the edge devices;
and the weight adding submodule is used for respectively performing weight addition on the first communication adaptation degree and the second communication adaptation degree of the edge equipment aiming at each edge equipment to determine the communication adaptation degree of the edge equipment.
In still other embodiments of the present disclosure, the apparatus may further include:
the continuous overlapping time determining module is used for determining the continuous overlapping time of a first communication area of the edge device and a second communication area of the task unloading device in the process that the edge device moves from the starting point of the corresponding predicted track to the end point of the predicted track before the edge device with the largest communication adaptation degree is determined to be the target edge device;
the first alternative edge device determining module is used for taking the edge device with the continuous overlapping time larger than a preset time threshold value as an alternative edge device;
the target edge device determining module 720 is specifically configured to determine that the candidate edge device with the largest communication adaptation degree is the target edge device.
In still other embodiments of the present disclosure, the apparatus may further include:
the second alternative edge device determining module is used for taking the edge device as an alternative edge device when the edge device is detected not to perform the calculation task currently;
the target edge device determining module 720 is specifically configured to determine that the candidate edge device with the largest communication adaptation degree is the target edge device.
In still other embodiments of the present disclosure, the apparatus may further include:
the deviation value determining module is used for determining a deviation value between a real track and a predicted track of the target edge equipment according to the real track of the target edge equipment after the target task is unloaded onto the target edge equipment;
and the first return execution module is used for returning and executing the operation of determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device when the deviation value is detected to be larger than the preset deviation threshold value.
In still other embodiments of the present disclosure, the apparatus may further include:
the accumulated deviation time determining module is used for determining accumulated deviation time which does not overlap between a first communication area of the target edge device and a second communication area of the task unloading device according to the real track of the target edge device after the target task is unloaded to the target edge device;
and the second return execution module is used for returning and executing the operation of determining the communication adaptation degree of each edge device relative to the task unloading device according to the corresponding predicted track of the edge device when the accumulated deviation time is detected to be larger than the preset deviation time threshold.
The apparatus provided in this embodiment can execute the method in any one of the above embodiments in fig. 1 and fig. 6, and the execution manner and the beneficial effects are similar, and are not described herein again.
For example, fig. 8 is a schematic structural diagram of a task offloading device in an embodiment of the present disclosure. Referring now specifically to FIG. 8, a schematic diagram of a task off-load device 800 suitable for use in implementing embodiments of the present disclosure is shown. The task uninstalling apparatus 800 in the embodiment of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (e.g., a car navigation terminal), and the like, and a stationary terminal such as a digital TV, a desktop computer, and the like. The task off-loading device shown in fig. 8 is only an example, and should not bring any limitation to the function and the scope of use of the embodiments of the present disclosure.
As shown in fig. 8, the task uninstall apparatus 800 may include a processing device 801 that can perform various appropriate actions and processes according to a program stored in a ROM802 or a program loaded from a storage device 808 into a RAM 803. In the RAM803, various programs and data necessary for the operation of the task uninstall apparatus 800 are also stored. The processing apparatus 801, the ROM802, and the RAM803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.
Generally, the following devices may be connected to the I/O interface 805: input devices 806 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 807 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage 808 including, for example, magnetic tape, hard disk, etc.; and a communication device 809. Communications 809 may allow task off-load device 800 to communicate wirelessly or by wire with other devices to exchange data. While FIG. 8 illustrates a task off-load device 800 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication means 809, or installed from the storage means 808, or installed from the ROM 802. The computer program, when executed by the processing apparatus 801, performs the above-described functions defined in the methods of the embodiments of the present disclosure.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the task off-load device; or may exist separately and not be assembled into the task unloading device.
The computer readable medium carries one or more programs which, when executed by the task off-load device, cause the task off-load device to: determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device; the communication adaptation degree is used for representing the overlapping degree of a first communication area of the edge device and a second communication area of the task unloading device in the process that the edge device moves from the starting point of the predicted track to the end point of the predicted track; determining the edge device with the maximum communication adaptation degree as a target edge device; and unloading the target task to the target edge device.
Computer program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of an element does not in some cases constitute a limitation on the element itself.
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The embodiments of the present disclosure also provide a computer-readable storage medium, where a computer program is stored in the storage medium, and when the computer program is executed by a processor, the method of any of the embodiments can be implemented, and the execution manner and the beneficial effects are similar, and are not described herein again.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present disclosure, which enable those skilled in the art to understand or practice the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. A task offloading method, performed by a task offloading device, the method comprising:
determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device; the communication adaptation degree is the overlapping degree of a first communication area of the edge device and a second communication area of the task unloading device in the process that the edge device moves from the starting point of the predicted track to the end point of the predicted track;
determining the edge device with the maximum communication adaptation degree as a target edge device;
offloading a target task onto the target edge device;
wherein the determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted trajectory of each edge device includes:
for each track point on the predicted track, determining an overlapping area of a first communication area of the edge device and a second communication area of the task unloading device when the edge device moves to the track point;
determining the communication adaptation degree according to the overlapping area corresponding to each track point;
determining the communication adaptation degree according to the overlapping area corresponding to each track point, including:
weighting and summing the overlapping areas corresponding to the track points to determine the communication adaptation degree;
and the weight of the corresponding overlapping area is smaller when the time difference between the corresponding prediction time of the track point and the prediction time corresponding to the starting point of the prediction track is larger.
2. The task offloading method of claim 1, wherein determining the communication suitability of each edge device with respect to the task offloading device based on the predicted trajectory of each edge device comprises:
acquiring a first predicted track and a second predicted track of each edge device;
determining a first communication adaptation degree of each edge device relative to the task unloading device according to a first predicted track of each edge device;
determining a second communication adaptation degree of each edge device relative to the task unloading device according to a second predicted track of each edge device;
and for each edge device, respectively carrying out weight summation on the first communication adaptation degree and the second communication adaptation degree of the edge device, and determining the communication adaptation degree of the edge device relative to the task unloading device.
3. The task offloading method of claim 1, wherein before determining the edge device with the greatest communication adaptation as a target edge device, the method further comprises:
determining the continuous overlapping time of a first communication area of the edge device and a second communication area of the task unloading device in the process that the edge device moves from the starting point of the corresponding predicted track to the end point of the predicted track;
taking the edge device with the continuous overlapping time larger than a preset time threshold value as an alternative edge device;
wherein the determining that the edge device with the largest communication adaptation degree is a target edge device comprises:
and determining the candidate edge device with the maximum communication adaptation degree as a target edge device.
4. The task offloading method of claim 1, wherein before determining that the edge device with the greatest communication adaptation is a target edge device, the method further comprises:
when detecting that the edge device does not perform a calculation task currently, taking the edge device as a standby edge device;
wherein the determining that the edge device with the largest communication adaptation degree is a target edge device comprises:
and determining the candidate edge device with the maximum communication adaptation degree as a target edge device.
5. The task offloading method of claim 1, wherein after offloading the target task onto the target edge device, the method further comprises:
determining a deviation value between the real track and the predicted track of the target edge device according to the real track of the target edge device;
and when the deviation value is detected to be larger than a preset deviation threshold value, returning to execute the operation of determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device.
6. The task offloading method of claim 5, wherein after offloading the target task onto the target edge device, the method further comprises:
determining accumulated deviation time of a first communication area of the target edge device and a second communication area of the task unloading device, wherein the accumulated deviation time is not overlapped;
and when detecting that the accumulated deviation time is larger than a preset deviation time threshold value, returning to execute the operation of determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device.
7. A task off-loading device, comprising:
the communication adaptation degree determining module is used for determining the communication adaptation degree of each edge device relative to the task unloading device according to the predicted track of each edge device; the communication adaptation degree is the overlapping degree of a first communication area of the edge device and a second communication area of the task unloading device in the process that the edge device moves from the starting point of the predicted track to the end point of the predicted track;
a target edge device determining module, configured to determine that the edge device with the largest communication adaptation degree is a target edge device;
the task unloading module is used for unloading the target task to the target edge device;
wherein, the communication adaptation degree determining module comprises:
the overlap area determining submodule is used for determining the overlap area of a first communication area of the edge device and a second communication area of the task unloading device when the edge device moves to each track point on the predicted track;
a communication adaptation degree determining submodule, configured to determine the communication adaptation degree according to the overlapping area corresponding to each of the trajectory points;
the communication adaptation degree determining submodule is specifically configured to perform weight summation on the overlapping areas corresponding to the track points to determine the communication adaptation degree;
and the weight of the corresponding overlapping area is smaller when the time difference between the corresponding prediction time of the track point and the prediction time corresponding to the starting point of the prediction track is larger.
8. A task off-loading device, comprising:
a processor;
a memory for storing executable instructions;
wherein the processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the task offloading method of any of claims 1-6.
9. A computer-readable storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, causes the processor to carry out the task offloading method of any of the preceding claims 1-6.
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| CN117377085A (en) * | 2023-10-20 | 2024-01-09 | 四川水利职业技术学院 | Computing resource scheduling method, system, terminal and medium based on edge computing |
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