Distributed target range virtual machine deployment scheduling method and system based on topology awareness

Abstract

The invention discloses a distributed target range virtual machine deployment scheduling method and system based on topology awareness. The method comprises the following steps: firstly, constructing a target topology instance structure according to network topology information input by a user; then arranging all virtual machine nodes in the target topology instance in a descending order according to connectivity and / or required hardware resource constraints; starting from the node index number of the virtual machine, recursively calling an exploration function, and exploring a feasible deployment scheme of the topological structure based on a depth-first mode; the exploration function aims at minimizing the link and transmission cost, the number of occupied cross-target range links is accurately tracked and verified in each step, it is ensured that the placement decision of any virtual machine cannot cause link capacity overrun between target range pairs, and therefore the link feasibility of a generation scheme can be ensured in the scheduling stage. According to the method, the virtual machine deployment scheduling problem of the complex network topology in the multi-target range environment can be solved, and the resource utilization efficiency and the deployment quality are improved.

Description

Technical Field

[0001] The present invention relates to a topology-aware distributed shooting range virtual machine deployment and scheduling method and system, and belongs to the technical field of network security. Background Art

[0002] The network range uses virtualization technology to simulate the real cyberspace attack and defense combat environment. It is a platform that supports various tests such as combat capability research and weapon equipment verification. As the scale of network security tests expands, higher requirements are placed on the simulation capabilities of the range. The traditional single range model has bottlenecks in performance and simulation scale. It is necessary to support more complex network tests through joint simulation of multiple ranges. When expanding to a joint verification method of multiple ranges, the typical networking method is as follows: Figure 1 shown.

[0003] Figure 1 The topology contains two sub-ranges: Range A and Range B. The labels on the nodes in the topology represent the range to which the node image belongs. When instantiating a range, you need to consider which range each node is instantiated in. Different instantiation methods will incur different communication and network transmission costs.

[0004] For the City A-Product Department network in the figure, if the "User 3" node is instantiated in Range A, the image must be copied from Range B to Range A, incurring a latency penalty for image transmission. However, subsequent communication between this node and the "Access Switch 2" node, because they belong to the same sub-range A, does not require an additional communication link. If the "User 3" node is instantiated in Range B, no additional image transmission is required for instantiation. However, because the "User 3" node and "Access Switch 2" are in different sub-ranges, subsequent communication requires an additional communication link (Range A and Range B may span regions or even the public network, necessitating an additional link).

[0005] Joint range verification presents the following challenges: When deployed within a single range, communication between virtual machines typically relies on a high-bandwidth, low-latency internal network with relatively abundant link resources. However, when the topology expands to multiple ranges, the physical links between ranges are often a valuable resource with limited bandwidth and a fixed quantity. Some simple multi-range scheduling strategies may only consider compute resources or underestimate the cost of cross-range communication, resulting in scheduling schemes being infeasible due to link exhaustion in actual deployments, or unnecessarily occupying a large number of cross-range links, affecting the demand for other potential cross-range communications. Summary of the Invention

[0006] Purpose of the invention: In response to the problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a distributed target range virtual machine deployment scheduling method and system based on topology awareness, to solve the problem of virtual machine deployment scheduling in a complex network topology in a multi-target range environment, and to improve resource utilization efficiency and deployment quality.

[0007] Technical solution: To achieve the above-mentioned purpose, the present invention adopts the following technical solution: In a first aspect, the present invention provides a distributed range virtual machine deployment and scheduling method based on topology awareness, comprising the following steps: Step 1: Construct the target topology instance structure based on the network topology information input by the user; Step 2: Arrange all virtual machine nodes in the target topology instance in descending order according to connectivity and / or required hardware resource constraints; Step 3: Initialize the optimal deployment plan to be empty and the minimum cost to be infinite; Step 4: Starting from the virtual machine node index number 1, recursively call the exploration function, passing in the index number, the currently explored deployment plan, and the used interconnection links; the exploration function explores feasible deployment plans of the topology structure based on a depth-first approach, and the execution steps include: Calculate the link and transmission costs of the currently explored deployment solution. If the cost is greater than the minimum cost, exit the current exploration function. When the passed index number is equal to the number of all virtual machine nodes, the global optimal deployment plan is determined according to the principle of minimum cost, and the current exploration function is exited; Traverse all available sub-ranges and check whether the remaining resources meet the needs of the current virtual machine node. For sub-ranges that meet the needs, traverse the neighbors of the current virtual machine node. If the neighbors are deployed and the ranges are different, update the link count between the two ranges and check whether the cross-range link meets the constraints. If the link also meets the constraints, update the deployment range of the current virtual machine node and deduct resources. After adding one to the index number, recursively call the exploration function to enter the exploration of the next virtual machine node. Step 5: After the exploration is completed, if there is an optimal deployment solution, it will be output.

[0008] Preferably, in step 1, a target topology instance structure is constructed, including a set of all virtual machine nodes in the topology, a set of all connections in the topology, the target range to which the original image corresponding to each virtual machine node belongs, the file size of the original image, and the hardware constraints required to instantiate the virtual machine.

[0009] Preferably, the link and transmission cost is the weighted sum of the usage cost of the interconnection link in the explored deployment scheme and the cost of mirror transmission to a remote target range for startup; wherein the usage cost of the interconnection link is obtained by accumulating the link counts between all target range pairs; the cost of mirror transmission to a remote target range for startup is obtained by accumulating the mirror transmission time of virtual machine nodes that are different from the deployment target range and the mirror storage target range.

[0010] Preferably, the checking of whether the cross-range links meet the constraints only checks the neighbors that are topologically connected to the current virtual machine node and have been deployed, and for each cross-range neighbor, verifies whether the link count of the corresponding range pair is less than a preset maximum value.

[0011] Preferably, the step of checking cross-range link constraints includes: Traverse the neighbors of the current VM node based on the set of all links in the topology; If the neighbor is already in the currently explored deployment scheme, the target range mapped by the neighbor is obtained. If it is different from the target range mapped by the current virtual machine node, a sorted target range pair is generated. If the link count of the corresponding target range pair exceeds the preset maximum value, the constraint is violated; After all neighbors pass the check, the link constraint is considered satisfied.

[0012] Preferably, the traversal of all available sub-ranges is performed in the order of giving priority to the sub-range where the image corresponding to the current virtual machine node is located, or giving priority to the sub-range where the resources are most sufficient.

[0013] Preferably, the determining of the global optimal deployment solution according to the minimum cost principle is that when the link and transmission costs of the currently explored deployment solution are less than the global optimal deployment solution, the currently explored deployment solution is used to replace the global optimal deployment solution.

[0014] In a second aspect, the present invention provides a topology-aware distributed range virtual machine deployment and scheduling system, comprising: The information extraction module is used to construct a target topology instance structure based on the network topology information input by the user; A pre-processing module is used to sort all virtual machine nodes in the target topology instance in descending order according to connectivity and / or required hardware resource constraints; and to initialize the optimal deployment solution to be empty and the minimum cost to be infinite; The solution exploration module is used to recursively call the exploration function starting from the virtual machine node index number 1, passing in the index number, the currently explored deployment solution, and the used interconnection links; the exploration function explores feasible deployment solutions of the topology structure based on a depth-first approach, and the execution steps include: Calculate the link and transmission costs of the currently explored deployment solution. If the cost is greater than the minimum cost, exit the current exploration function. When the passed index number is equal to the number of all virtual machine nodes, the global optimal deployment plan is determined according to the principle of minimum cost, and the current exploration function is exited; Traverse all available sub-ranges and check whether the remaining resources meet the needs of the current virtual machine node. For sub-ranges that meet the needs, traverse the neighbors of the current virtual machine node. If the neighbors are deployed and the ranges are different, update the link count between the two ranges and check whether the cross-range link meets the constraints. If the link also meets the constraints, update the deployment range of the current virtual machine node and deduct resources. After adding one to the index number, recursively call the exploration function to enter the exploration of the next virtual machine node. The output module is used to output the optimal deployment solution if one exists after the exploration is completed.

[0015] In a third aspect, the present invention provides a computer system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the distributed target range virtual machine deployment and scheduling method based on topology awareness are implemented.

[0016] In a fourth aspect, the present invention provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of a distributed shooting range virtual machine deployment and scheduling method based on topology awareness.

[0017] Beneficial effects: Compared with the prior art, the present invention has the following advantages: 1. The present invention incorporates the maximum available number of cross-range physical communication links as a core hard constraint into the virtual machine scheduling decision, and ensures that the placement decision of any virtual machine will not cause the link capacity between the range pairs to exceed the limit by accurately tracking and verifying the number of occupied cross-range links at each step of the solution exploration, thereby ensuring the link feasibility of the generated solution in the scheduling stage, and avoiding the problem of insufficient links during deployment that may arise from traditional methods. 2. The present invention systematically explores the potential placement combinations of all virtual machines in a single topology instance, comprehensively considering minimizing the use of cross-range links and mirror transmission costs, and can find and determine the globally optimal or near-optimal virtual machine placement solution under the premise of meeting all resource and link constraints, thereby improving resource utilization efficiency and deployment quality. 3. The present invention sorts the virtual machines by connectivity / resource requirements before exploration, which can trigger link / resource constraint conflict detection in advance, effectively improving the efficiency of algorithm exploration. 4. The present invention integrates multiple constraints such as virtual machine resource requirements, image location, and cross-range link capacity, performs refined modeling and verification, and solves the problem through a unified solution exploration framework, effectively solving the problem of virtual machine deployment and scheduling in complex network topologies in a multi-range environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1This is an example diagram for multi-range deployment.

[0019] Figure 2 Schematic diagram of a method flow in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings and specific embodiments.

[0021] like Figure 2 As shown, the embodiment of the present invention discloses a distributed shooting range virtual machine deployment and scheduling method based on topology awareness, which mainly includes the following steps: Step 1: Construct the target topology instance structure based on the network topology information input by the user.

[0022] Step 2: Arrange all virtual machine nodes in the target topology instance in descending order according to connectivity and / or required hardware resource constraints.

[0023] Step 3: Initialize the optimal deployment plan to be empty and the minimum cost to be infinite.

[0024] Step 4: Starting from the virtual machine node index number 1, recursively call the exploration function, passing in the index number, the currently explored deployment plan, and the used interconnection links; the exploration function explores feasible deployment plans of the topology structure based on a depth-first approach, and the execution steps include: Calculate the link and transmission costs of the currently explored deployment solution. If the cost is greater than the minimum cost, exit the current exploration function. When the passed index number is equal to the number of all virtual machine nodes, the global optimal deployment plan is determined according to the principle of minimum cost, and the current exploration function is exited; Traverse all available sub-target ranges and check whether the remaining resources meet the needs of the current virtual machine node. For sub-target ranges that meet the needs, traverse the neighbors of the current virtual machine node. If the neighbors are deployed and the target ranges are different, update the link count between the two target ranges and check whether the cross-target range link meets the constraints. If the link also meets the constraints, update the deployment target range of the current virtual machine node and deduct resources. After adding one to the index number, recursively call the exploration function to enter the exploration of the next virtual machine node.

[0025] Step 5: After the exploration is completed, if there is an optimal deployment solution, it will be output.

[0026] Specifically, in this embodiment, the target topology instance structure constructed in step 1 includes the set of all virtual machine nodes in the topology, the set of all connections in the topology, the target range to which the original image corresponding to each virtual machine node belongs, the file size of the original image, and the hardware constraints required to instantiate the virtual machine.

[0027] For example, the network topology structure is decomposed into the following target_topology_instance structure, the main elements of which are as follows: A) V: The set of all virtual machine nodes in the topology, denoted as V={vm1,vm2,...,vm n}, representing n virtual machine nodes; the virtual machine nodes here include terminals, network devices, and other various nodes in the topology that can be generated by the virtualization platform based on virtual machine images.

[0028] B) E: The set of all connections in the topology, denoted as E = {(u, v), (x, y)...}, where elements such as u, v, x, and y represent a virtual machine node.

[0029] C) image_location[vm i ]:vm i The shooting range to which the corresponding original image belongs.

[0030] D) image_size[vm i ]:vm i The file size corresponding to the original image.

[0031] E) requirements[vm i ]: Hardware constraints required to instantiate a virtual machine, such as an 8-core CPU, 64GB of memory, etc.

[0032] In this embodiment, ranges is used to represent the available sub-range set, which is in the form of ranges={range1,range2,...,range k} represents k available sub-ranges. Use range_available_res to represent the remaining resource quantity list of sub-ranges, range_available_res[range i ] represents the range i The remaining resources (remaining resources can be values ​​of multiple dimensions such as CPU, memory, disk, etc.). In actual operation, if any dimension of resources does not meet the deployment requirements, the range is considered undeployable. Use max_link[range i ][range j ] indicates the range i and shooting range j The maximum number of interconnection links between them.

[0033] Based on the elements defined above, the detailed steps of a topology-aware distributed range virtual machine deployment and scheduling method described in this embodiment are as follows: Step S1: Split the network topology input by the user according to the data structure of target_topology_instance.

[0034] Step S2: Arrange all nodes V in target_topology_instance in descending order according to one or both of the virtual machine node connectivity and the required hardware resource constraints.

[0035] Step S3: Initialize the current optimal solution optimal_placement to be empty, the cost score min_optimal_score corresponding to the optimal solution to be infinite, and the flag find_solution indicating whether a feasible solution is found to be false.

[0036] Step S4: Starting from vm_idx=1, recursively call the exploration function to explore feasible deployment methods for the current topology. The exploration function is executed as shown in steps S41 to S46.

[0037] When calling the exploration function, the currently explored virtual machine deployment plan is recorded as current_placement, which records the mapping relationship between vm and range; the interconnection used by the current plan is recorded as current_used_links, which records the interconnection links used by the two ranges, in the same format as max_link.

[0038] Step S41, the virtual machine node in target_topology_instance.V[vm_idx] is recorded as vm x , each node is explored according to steps S42 to S46.

[0039] Step S42: Calculate the deployment cost current_cost based on the currently explored deployment solution current_placement and current_used_links. The calculation formula is as follows: current_cost = w1*transfer_cost + w2*link_cost. Where w1 and w2 are weights, link_cost represents the cost of using the interconnection link of the current solution, and the calculation method includes but is not limited to adding 1 to the value for each link used; transfer_cost represents the cost of mirroring to a remote target range for startup. The calculation method is as follows: Traverse each deployed VM node in current_placement. If the target deployment range is inconsistent with the range to which the image belongs, a transmission cost will be incurred, that is, current_placement[vm] is not equal to image_location[vm]. The calculation method for each image transmission cost includes but is not limited to the image size / communication bandwidth between the two ranges.

[0040] Step S43: If the current deployment cost current_cost is greater than min_optimal_score, it means that the deployment solution under the current branch is not the optimal solution, and the current exploration function is exited.

[0041] Otherwise, determine based on vm_idx: If vm_idx is equal to len(target_topology_instance.V), choose between the current deployment solution and the optimal deployment solution. If current_cost is less than min_optimal_score, replace the optimal deployment solution with the current deployment solution. This means that min_optimal_score is equal to current_cost, optimal_placement is equal to current_placement, and find_solution is true. If vm_idx is less than len(target_topology_instance.V), jump to step S44.

[0042] Step S44, explore vm x The feasibility of deploying to all available sub-targets can be tested one by one according to the preset priority (such as the current VM x The sub-range where the corresponding image is located is given priority, and the sub-range with the most sufficient resources is given priority). The sub-range currently being attempted is recorded as range_x.

[0043] Step S45: Check whether the remaining resources of the current sub-range range_x meet the vm x The resource satisfaction check method for deployment requirements is as follows: According to range_available_res[range_x], determine whether the remaining resources of the target sub-range meet requirements[vm x ]’s needs, if any dimension does not meet the needs, it will be judged as unmet needs.

[0044] If the inspection result shows that the requirements are not met, the current sub-shooting range is skipped and the next sub-shooting range is continued; otherwise, the process jumps to step S46.

[0045] Step S46: Find the current vm in target_topology_instance.E x All neighbor nodes of vm i For example, if current_placement[vm i ] is not equal to range_x, an interconnection link needs to be added.

[0046] After adding the interconnection link check, you need to check whether the link meets the deployment requirements. The check method is as follows: Get all neighbor nodes S of the current node vm_x to be deployed in target_topology_instance.V, and get the deployment target range P corresponding to these nodes S in current_placement = {range x ,range y ,...}. If the following constraints are met, the interconnection link constraint check passes: ∀range∈P,current_used_links[range_x][range]≤max_link[range_x][range] If the link constraint is met, vm_idx is incremented by 1. At the same time, based on the check result, the corresponding record is added to current_used_links and the corresponding deduction is made to range_available_res. The exploration function is recursively called with the new vm_idx, current_used_links, and range_available_res as parameters; otherwise, the process jumps to step S44 to continue the feasibility exploration of the next sub-range.

[0047] Step S5: After traversing all branches of the topology, a judgment is made based on find_solution. If find_solution is false, it means that there is no available deployment solution for the current topology; otherwise, the result corresponding to optimal_placement is the optimal deployment solution.

[0048] Based on the same inventive concept, an embodiment of the present invention discloses a topology-aware distributed shooting range virtual machine deployment and scheduling system, including: an information extraction module, used to construct a target topology instance structure according to the network topology information input by the user; a preprocessing module, used to arrange all virtual machine nodes in the target topology instance in descending order according to the connectivity and / or required hardware resource constraints; and initialize the optimal deployment plan to be empty and the minimum cost to be infinite; a solution exploration module, used to recursively call the exploration function starting from the virtual machine node index number as one, passing in the index number, the currently explored deployment plan and the used interconnection link; and an output module, used to output the optimal deployment plan if there is one after the exploration is completed.

[0049] The exploration function explores feasible deployment solutions for the topology structure based on a depth-first approach. The execution steps include: Calculate the link and transmission costs of the currently explored deployment solution. If the cost is greater than the minimum cost, exit the current exploration function. When the passed index number is equal to the number of all virtual machine nodes, the global optimal deployment plan is determined according to the principle of minimum cost, and the current exploration function is exited; Traverse all available sub-target ranges and check whether the remaining resources meet the needs of the current virtual machine node. For sub-target ranges that meet the needs, traverse the neighbors of the current virtual machine node. If the neighbors are deployed and the target ranges are different, update the link count between the two target ranges and check whether the cross-target range link meets the constraints. If the link also meets the constraints, update the deployment target range of the current virtual machine node and deduct resources. After adding one to the index number, recursively call the exploration function to enter the exploration of the next virtual machine node.

[0050] A computer system disclosed in an embodiment of the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the distributed shooting range virtual machine deployment and scheduling method based on topology awareness are implemented.

[0051] A computer program product disclosed in an embodiment of the present invention includes a computer program. When the computer program is executed by a processor, the computer program implements the steps of the distributed shooting range virtual machine deployment and scheduling method based on topology awareness.

[0052] The program code for implementing the inventive method can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that the program code, when executed by the processor or controller, causes the steps of the inventive method to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as an independent software package and partially on a remote machine, or completely on a remote machine or server. The present invention is not described in detail herein, and all of these are known techniques to those skilled in the art.

Claims

1. A distributed shooting range virtual machine deployment and scheduling method based on topology awareness, characterized in that: The steps include: Step 1: Construct the target topology instance structure based on the network topology information input by the user; Step 2: Arrange all virtual machine nodes in the target topology instance in descending order according to connectivity and / or required hardware resource constraints; Step 3: Initialize the optimal deployment plan to be empty and the minimum cost to be infinite; Step 4: Starting from the VM node index number 1, recursively call the exploration function, passing in the index number, the currently explored deployment solution, and the used interconnection link; The exploration function explores feasible deployment solutions for the topology structure based on a depth-first approach, and the execution steps include: Calculate the link and transmission costs of the currently explored deployment solution. If the cost is greater than the minimum cost, exit the current exploration function. When the passed index number is equal to the number of all virtual machine nodes, the global optimal deployment plan is determined according to the principle of minimum cost, and the current exploration function is exited; Traverse all available sub-ranges and check whether the remaining resources meet the needs of the current virtual machine node. For sub-ranges that meet the needs, traverse the neighbors of the current virtual machine node. If the neighbors are deployed and the ranges are different, update the link count between the two ranges and check whether the cross-range link meets the constraints. If the link also meets the constraints, update the deployment range of the current virtual machine node and deduct resources. After adding one to the index number, recursively call the exploration function to enter the exploration of the next virtual machine node. Step 5: After the exploration is completed, if there is an optimal deployment solution, it will be output.

2. A topology-aware distributed range virtual machine deployment and scheduling method according to claim 1, characterized in that: In step 1, the target topology instance structure is constructed, including the set of all virtual machine nodes in the topology, the set of all connections in the topology, the target range to which the original image corresponding to each virtual machine node belongs, the file size of the original image, and the hardware constraints required to instantiate the virtual machine.

3. A topology-aware distributed shooting range virtual machine deployment and scheduling method according to claim 1, characterized in that: The link and transmission cost is the weighted sum of the usage cost of the interconnection link in the explored deployment scheme and the cost of mirror transmission to a remote target range for startup; the usage cost of the interconnection link is obtained by accumulating the link counts between all target range pairs; the cost of mirror transmission to a remote target range for startup is obtained by accumulating the mirror transmission time of virtual machine nodes that are different from the deployment target range and the mirror storage target range.

4. A distributed shooting range virtual machine deployment and scheduling method based on topology awareness according to claim 1, characterized in that: The check of whether the cross-range links meet the constraints only checks the neighbors that are topologically connected to the current virtual machine node and have been deployed. For each cross-range neighbor, it is verified whether the link count of the corresponding range pair is less than the preset maximum value.

5. A topology-aware distributed shooting range virtual machine deployment and scheduling method according to claim 4, characterized in that: The steps for cross-range link constraint checking include: Traverse the neighbors of the current VM node based on the set of all links in the topology; If the neighbor is already in the currently explored deployment scheme, the target range mapped by the neighbor is obtained. If it is different from the target range mapped by the current virtual machine node, a sorted target range pair is generated. If the link count of the corresponding target range pair exceeds the preset maximum value, the constraint is violated; After all neighbors have passed the check, the link constraint is considered to be met.

6. A topology-aware distributed range virtual machine deployment and scheduling method according to claim 1, characterized in that: The traversal of all available sub-targets is performed in the order of giving priority to the sub-target where the image corresponding to the current virtual machine node is located, or giving priority to the sub-target where the resources are most sufficient.

7. The method for deploying and scheduling distributed virtual machines in a shooting range based on topology awareness according to claim 1, characterized in that: The determining of the global optimal deployment solution according to the minimum cost principle is that when the link and transmission costs of the currently explored deployment solution are less than the global optimal deployment solution, the currently explored deployment solution is used to replace the global optimal deployment solution.

8. A distributed shooting range virtual machine deployment and scheduling system based on topology awareness, characterized in that: include: The information extraction module is used to construct a target topology instance structure based on the network topology information input by the user; A pre-processing module is used to sort all virtual machine nodes in the target topology instance in descending order according to connectivity and / or required hardware resource constraints; and to initialize the optimal deployment solution to be empty and the minimum cost to be infinite; The solution exploration module is used to recursively call the exploration function starting from the virtual machine node index number one, passing in the index number, the currently explored deployment solution, and the used interconnection links; The exploration function explores feasible deployment solutions for the topology structure based on a depth-first approach, and the execution steps include: Calculate the link and transmission costs of the currently explored deployment solution. If the cost is greater than the minimum cost, exit the current exploration function. When the passed index number is equal to the number of all virtual machine nodes, the global optimal deployment plan is determined according to the principle of minimum cost, and the current exploration function is exited; Traverse all available sub-ranges and check whether the remaining resources meet the needs of the current virtual machine node. For sub-ranges that meet the needs, traverse the neighbors of the current virtual machine node. If the neighbors are deployed and the ranges are different, update the link count between the two ranges and check whether the cross-range link meets the constraints. If the link also meets the constraints, update the deployment range of the current virtual machine node and deduct resources. After adding one to the index number, recursively call the exploration function to enter the exploration of the next virtual machine node. The output module is used to output the optimal deployment solution if one exists after the exploration is completed.

9. A computer system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the computer program is executed by a processor, the steps of a topology-aware distributed shooting range virtual machine deployment and scheduling method are implemented according to any one of claims 1 to 7.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of a topology-aware distributed shooting range virtual machine deployment and scheduling method are implemented according to any one of claims 1 to 7.

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