A storage area QoS allocation system based on quantum computing

Abstract

The present invention discloses a storage area QoS allocation system based on quantum computing, which applies a cloud host, QKDN and multiple quantum computing device network elements. The cloud host verifies the identity of the quantum computing device network element; after verification, system resources are allocated to the quantum computing device network element, and cloud storage area space is allocated to the quantum computing device network element in the cloud host; the cloud storage area space is divided into multiple independent memory spaces according to the business modules of the quantum computing device network element, and each business module corresponds to an independent memory space; the flow of each business module is limited by a dual-speed dual-bucket token bucket, and each business module sets the same CIR rate and token bucket capacity of the CBS bucket and the EBS bucket; the token bucket parameters are adaptively and dynamically adjusted for each independent business module according to the actual business volume. The present invention sets QoS strategies according to different business types and module conditions to ensure the service quality of QKDN.

Description

Technical Field

[0001] The present invention relates to the field of quantum computing and algorithms, and in particular to a storage area QoS allocation system based on quantum computing. Background Art

[0002] QoS (Quality of Service) refers to a network's ability to use various basic technologies to provide better service capabilities for specified network communications. It is a network security mechanism and a technology used to solve problems such as network delays and congestion.

[0003] At present, there are quantum computer host types such as IBM, Google and Benyuan at home and abroad. Some cloud leveling methods have been proposed. The QoS allocation method of the network in the cloud host of quantum computing adopts the form of cloud host to provide allocation services. The server side divides the storage unit for each computer user, and then divides the storage unit into two new units to process system data and quantum computer user data respectively. Different QoS values ​​are set for the two storage units to ensure that the operating system can run with a higher QoS. At the same time, the access speed of the data is reduced, reducing the resource consumption of the system for full-speed reading and writing of quantum computer user data.

[0004] The above method completely restricts resource allocation. All quantum computer user data uses a QoS value, and the QoS value is fixed and cannot be dynamically adjusted.

[0005] Therefore, it is necessary to improve the existing technology and propose a QoS allocation system that dynamically modifies its parameters according to business conditions to achieve priority allocation of different functions. Summary of the invention

[0006] In order to solve the above technical problems, a QoS allocation system is proposed which can dynamically modify its parameters according to the business situation to realize the priority allocation of different functions.

[0007] To achieve the above-mentioned object, the technical solution adopted by the present invention is as follows: a storage area QoS allocation system based on quantum computing, comprising a cloud host, a QKDN and a plurality of quantum computing device network elements, wherein the plurality of quantum computing device network elements are connected to the cloud host through the QKDN;

[0008] Any of the quantum computing device network elements sends a resource application request to the cloud host via QKDN;

[0009] The cloud host is used to verify the identity of the quantum computing device network element; if the verification is successful, system resources are allocated to the quantum computing device network element, and cloud storage area space is allocated to the quantum computing device network element in the cloud host;

[0010] The cloud storage area space is divided into multiple independent memory spaces according to the business modules of the quantum computing device network element, and each business module corresponds to an independent memory space;

[0011] The cloud host uses a dual-speed dual-bucket token bucket to limit the traffic of each business module, and each business module sets the same CIR rate and token bucket capacity as the CBS bucket and the EBS bucket;

[0012] The token bucket parameters are adaptively and dynamically adjusted for each independent service module according to the actual service volume.

[0013] Preferably, the service module at least includes a service module for acquiring device data, setting key generation rate parameters, querying key error rate parameters and starting inspection strategy.

[0014] Preferably, in step 6, the conditions for the adaptive dynamic adjustment are as follows:

[0015] The CBS bucket and the EBS bucket are set to have the same bucket capacity;

[0016] The same CIR rate is set for the CBS bucket and the EBS bucket.

[0017] Preferably, the adaptive dynamic adjustment also satisfies the following conditions:

[0018] Each business module records the size of the data packet A for each communication i , before sending a new data packet, update the current business module maximum data packet B max , and calculate the new average packet The new average packet The calculation process is as follows:

[0019]

[0020] C E桶 =B max -C c桶

[0021] in, is the average packet size, C c桶 is the CBS barrel capacity, C E桶 Indicates the EBS bucket capacity.

[0022] Preferably, the quantum computing device network element is configured with bandwidth.

[0023] Preferably, the service module calculates the CIR rate before sending data, and restores to the default CIR rate after the data is sent. The calculation method of the CIR rate and the default CIR rate is as follows:

[0024] CIR rate = (service frequency × 40% +) × bandwidth;

[0025] Default CIR rate = (current function module weight / total weight) × bandwidth.

[0026] Preferably, after the quantum computing device network element QKMS completes the two-way authentication, the device is connected to the network and a storage area is allocated on the QKMS side.

[0027] A storage device stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing the above-mentioned steps of a storage area QoS allocation system based on quantum computing.

[0028] An intelligent terminal includes a processor for executing various instructions and a storage device for storing multiple instructions, wherein the instructions are suitable for being loaded by the processor and executing the above-mentioned storage area QoS allocation system step operation based on quantum computing.

[0029] The beneficial technical effects of the present invention are as follows: by applying for services for each quantum computing device network element in the cloud host, allocating storage space for it, separating it from each business module, and independently setting QoS policies, the system dynamically adjusts QoS according to business conditions. When QKMS provides services for the entire QKDN, QoS policies are set for network elements connected to QKDN, and QoS policies are set according to different business types and business module weights, thereby ensuring the service quality of QKDN. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is the overall structural diagram of the present invention;

[0031] Figure 2 This is a flowchart of the steps of a storage area QoS allocation system based on quantum computing in the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments, but the scope of protection claimed in the present invention is not limited to the following specific embodiments.

[0033] like Figure 1 As shown, a storage area QoS allocation system based on quantum computing uses a cloud host, a QKDN, and multiple quantum computing device network elements (network elements with quantum computing functions and independent transmission functions). The method includes the following steps:

[0034] Step 1: Any quantum computing device network element sends a resource application request to the cloud host through QKDN (quantum secure communication network);

[0035] Step 2: The cloud host verifies the network element identity of the quantum computing device;

[0036] If the verification is successful, proceed to step 3;

[0037] If the verification fails, the process returns to step 1, where the identity verification adopts the traditional digital certificate authentication method.

[0038] Step 3: The cloud host allocates system resources to the quantum computing device network element, and allocates cloud storage area space to the quantum computing device network element in the cloud host;

[0039] Step 4: Divide the cloud storage area space into multiple independent memory spaces according to the business modules of the quantum computing device network element, and each business module corresponds to an independent memory space. Here, the quantum computing device network element is composed of multiple modules, and the combination of multiple modules forms the complete function of the quantum computing device network element;

[0040] Step 5: Use the dual-rate dual-bucket token bucket to limit the traffic of each service module, and set the same CIR rate and token bucket capacity for the CBS bucket and the EBS bucket for each service module;

[0041] Specifically, the token bucket can be regarded as a container for storing tokens, with a preset capacity. The system puts tokens into the bucket at a given rate. When the bucket is full, the excess tokens overflow.

[0042] The two-rate two-bucket token bucket uses the two-rate three-color marker trTCM (Two Rate Three Color Marker) algorithm to evaluate traffic and color-mark packets according to the evaluation results, namely green, yellow, and red.

[0043] CIR (Committed Information Rate) is a parameter of the dual-rate dual-bucket token bucket: the committed information rate, which indicates the rate at which tokens are put into bucket C, that is, the average rate at which bucket C allows packets to be transmitted or forwarded.

[0044] Step 6: The token bucket parameters are adaptively and dynamically adjusted for each independent business module according to the actual business volume to ensure that the overall system consumption remains unchanged.

[0045] The service modules described in this embodiment at least include obtaining device data, setting key generation rate parameters, querying key bit error rate parameters and starting inspection strategy service modules.

[0046] Preferably, in step 6, the conditions for the adaptive dynamic adjustment are as follows:

[0047] The CBS bucket and the EBS bucket are set to have the same bucket capacity;

[0048] The same CIR rate is set for the CBS bucket and the EBS bucket.

[0049] Preferably, the adaptive dynamic adjustment also satisfies the following conditions:

[0050] During the communication process, each service module of the quantum computing device network element records the size of the data packet A for each communication. i , before sending a new data packet, update the current business module maximum data packet B max , and calculate the new average packet The new average packet The calculation process is as follows:

[0051]

[0052] C E桶 =B max -C c桶

[0053] in, is the average packet size, C c桶 is the CBS barrel capacity, C E桶 Indicates the EBS bucket capacity.

[0054] Preferably, the quantum computing device network element is allocated with bandwidth (bandwidth refers to network bandwidth, which indicates the amount of data that can be transmitted per unit time (generally 1 second)), and the bandwidth here is set according to the actual communication speed requirements.

[0055] Preferably, the service module calculates the CIR rate before sending data, and restores to the default CIR rate after the data is sent. The calculation method of the CIR rate and the default CIR rate is as follows:

[0056] CIR rate = (service frequency × 40% +) × bandwidth;

[0057] Default CIR rate = (current module weight / total weight) × bandwidth.

[0058] The service frequency is obtained according to the actual service type frequency, and the weight of the current module is assigned by QKMS according to the type of service module. The weights of each service module are arranged from large to small as follows: obtaining device data service, setting key generation rate parameter service, querying key error rate parameter service, and enabling inspection strategy service. The total weight is the sum of the weights of all modules.

[0059] According to the above adaptive dynamic adjustment calculation results, it can be ensured that important modules (modules with high weights) can preferentially process services, while ensuring that other service modules can process services normally.

[0060] Preferably, after the quantum computing device network element QKMS completes the two-way authentication, the device is connected to the network and a storage area is allocated on the QKMS side.

[0061] A storage device stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing the above-mentioned steps of a storage area QoS allocation system based on quantum computing.

[0062] An intelligent terminal includes a processor for executing various instructions and a storage device for storing multiple instructions, wherein the instructions are suitable for being loaded by the processor and executing the above-mentioned storage area QoS allocation system step operation based on quantum computing.

[0063] The beneficial technical effects of the present invention are as follows: by applying for services for each quantum computing device network element in the cloud host, allocating storage space for it, separating it from each business module, and independently setting QoS policies, the system dynamically adjusts QoS according to business conditions. When QKMS provides services for the entire QKDN, QoS policies are set for network elements connected to QKDN. QoS policies are set according to different business types and block weights, thereby ensuring the service quality of QKDN.

[0064] According to the disclosure and teaching of the above description, those skilled in the art to which the present invention belongs may also make changes and modifications to the above embodiments. Therefore, the present invention is not limited to the specific embodiments disclosed and described above, and some modifications and changes to the invention should also fall within the scope of protection of the claims of the present invention. In addition, although some specific terms are used in this specification, these terms are only for the convenience of description and do not constitute any limitation to the invention.

Claims

1. A storage area QoS allocation system based on quantum computing, characterized in that: The method comprises applying a cloud host, a QKDN and a plurality of quantum computing device network elements, wherein the plurality of quantum computing device network elements are connected to the cloud host through the QKDN; Any of the quantum computing device network elements sends a resource application request to the cloud host via QKDN; The cloud host is used to verify the network element identity of the quantum computing device; If the verification is successful, system resources are allocated to the quantum computing device network element, and cloud storage area space is allocated to the quantum computing device network element in the cloud host; The cloud storage area space is divided into multiple independent memory spaces according to the business modules of the quantum computing device network element, and each business module corresponds to an independent memory space; The cloud host uses a dual-speed dual-bucket token bucket to limit the traffic of each business module, and each business module sets the same CIR rate and token bucket capacity as the CBS bucket and the EBS bucket; The token bucket parameters are adaptively and dynamically adjusted for each independent service module according to the actual service volume; The business module at least includes obtaining device data, setting key generation rate parameters, querying key error rate parameters and opening inspection strategy business modules; The conditions for the adaptive dynamic adjustment of the business module are as follows: The CBS bucket and the EBS bucket are set to have the same bucket capacity; The same CIR rate is set for the CBS bucket and the EBS bucket; The adaptive dynamic adjustment of the business module also meets the following conditions: Each business module records the size of the data packet A for each communication i , before sending a new data packet, update the current business module maximum data packet B max , and calculate the new average packet The new average packet The calculation process is as follows: C E桶 =B max -C c桶 in, is the average packet size, C c桶 is the CBS barrel capacity, C E桶 is the EBS bucket capacity; The weight of the current module is assigned by QKMS according to the type of business module. The weight of each business module is arranged in the following order from large to small: get device data business, set key generation rate parameter business, query key error rate parameter business and start inspection strategy business. The total weight is the sum of all module weights. According to the above adaptive dynamic adjustment calculation results, it is ensured that the modules with high weights process services first, while ensuring that the other service modules process services normally.

2. A storage area QoS allocation system based on quantum computing as claimed in claim 1, characterized in that: The quantum computing device network element is configured with bandwidth.

3. A storage area QoS allocation system based on quantum computing as claimed in claim 2, characterized in that: After the quantum computing device network element QKMS completes the two-way authentication, the device is connected to the network and a storage area is allocated on the QKMS side.

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