CN-122027580-A - Multichannel state-dense task scheduling method and system based on dynamic priority

CN122027580ACN 122027580 ACN122027580 ACN 122027580ACN-122027580-A

Abstract

The invention provides a multichannel national encryption task scheduling method and system based on dynamic priority, and belongs to the technical field of information security. The method comprises the steps of determining an initial urgency factor according to the remaining time of the national density task from the deadline, determining a dynamic enhancement factor by adopting a self-adaptive immune optimization enhancement algorithm to correct the initial urgency factor to obtain a final urgency factor, generating a new value of a posterior mean vector and a new value of a posterior covariance matrix by using a Bayesian linear regression model corresponding to a Bayesian updating channel, determining a basic suitability factor according to the new value of the posterior mean vector, correcting the basic suitability factor according to the new value of the posterior covariance matrix to obtain a final suitability factor, multiplying the dynamic enhancement factor, the final urgency factor and the final suitability factor to obtain the priority of the national density task, constructing a global optimal allocation model according to the priority of the national density task, and solving to obtain the national density task scheduling strategy. The invention improves the utilization efficiency of system resources.

Inventors

WU PO
GONG CANFENG
REN PENGLING
WANG BINGQIAN
GAO XIANG
Ruan chong
WANG DAN
HU YUFEI
LIU YAJIE
JI ZHONGHAO
Song Yanlou
ZHANG JIANGNAN
LIU HUI

Assignees

国网河南省电力公司电力科学研究院
南京南瑞信息通信科技有限公司
国网河南省电力公司
国家电网有限公司

Dates

Publication Date: 20260512
Application Date: 20260306

Claims (10)

1.A multichannel state-dense task scheduling method based on dynamic priority is characterized by comprising the following steps: Determining an initial urgency factor according to the remaining time of the national password task from the deadline; Adopting a self-adaptive immune optimization enhancement algorithm, determining a dynamic enhancement factor according to the national density task characteristics, and correcting an initial urgency factor according to the dynamic enhancement factor to obtain a final urgency factor; Using a Bayes linear regression model corresponding to the Bayes updating channel to generate a new value of a posterior mean value vector and a new value of a posterior covariance matrix, determining the affinity of the national secret task and the channel according to the new value of the posterior mean value vector, determining a basic adaptability factor according to the affinity of the national secret task and the multiple channels, and correcting the basic adaptability factor according to the new value of the posterior covariance matrix to obtain a final adaptability factor; Multiplying the dynamic enhancement factor, the final urgency factor and the final suitability factor to obtain the priority of the national encryption task; and constructing a global optimal allocation model according to the priority of the national density task, and solving to obtain a national density task scheduling strategy.
2. The multi-channel state-dense task scheduling method based on dynamic priority as claimed in claim 1, wherein the method comprises the following steps: determining an initial urgency factor from a remaining time of the national password task from the deadline includes: If the country is close to the rest of the task If the value is less than or equal to 0, marking the task as a timeout state, and finally, taking the value of the urgency factor as 1; if the remaining time of the national density task from the deadline is more than 0, calculating the time attenuation urgency, If the security event flag bit is equal to 1 and the national security task uses the secret key in the security event, calculating the security urgency parameter according to the time attenuation urgency and the national security task security level, and if the security event flag bit is equal to 1 and the national security task uses the secret key in the security event, enabling the security urgency parameter to be equal to the time attenuation urgency, If the key remains valid for less than 2 times Determining an initial urgency factor according to the security urgency parameter and the key remaining effective time, if the key remaining effective time is more than or equal to 2 times Let the initial urgency factor equal to the safety urgency parameter.
3. The multi-channel state-dense task scheduling method based on dynamic priority as claimed in claim 2, wherein the method comprises the following steps: determining an initial urgency factor according to the security urgency parameter and the key remaining effective time, wherein the initial urgency factor is expressed by the following formula: In the formula, Representing the initial urgency factor of the ith national cryptographic task at time t, Represents a safety urgency parameter, max represents a maximum value, The representation takes the minimum value of the value, Indicating that the key remains valid for a time, The remaining time from the deadline for the national cipher task is represented.
4. The multi-channel state-dense task scheduling method based on dynamic priority as claimed in claim 1, wherein the method comprises the following steps: determining the dynamic enhancement factor includes: determining an immune enhancing factor according to the matching degree of the antigen and the immune system; Determining memory enhancement factors according to the most similar antibodies in the immune memory bank of the optimal antibodies and the antigens corresponding to the national density task; Determining the average load rate of the system according to the congestion index of the national secret task in each channel, and determining an immunoregulation factor according to the average load rate of the system, the proportion of the emergency task to the total task and the safety event zone bit; the dynamic enhancement factor is obtained by multiplying the immune enhancement factor, the memory enhancement factor and the immune regulation factor.
5. The multi-channel state-dense task scheduling method based on dynamic priority as claimed in claim 4, wherein the method comprises the following steps: An immunomodulatory factor represented by the formula: In the formula, Represents the load regulation factor, Indicating the emergency task adjustment factor(s), Indicating the safety adjustment coefficient of the vehicle, Indicating the average load factor of the system, Indicating the proportion of urgent tasks to the total tasks, A flag bit representing a security event is set, Indicating that no security event has occurred, Indicating that a security event has occurred.
6. The multi-channel state-dense task scheduling method based on dynamic priority as claimed in claim 1, wherein the method comprises the following steps: Correcting the initial urgency factor based on the dynamic enhancement factor, expressed as: In the formula, Which represents the final urgency factor of the vehicle, Representing the correlation correction coefficient(s), A dynamic enhancement factor representing an ith cryptographic task, Represents the average value of all national cryptographic tasks dynamic enhancement factors, Representing the largest dynamic enhancement factor in all national cryptographic tasks, Representing the smallest dynamic enhancement factor among all national cryptographic tasks.
7. The multi-channel state-dense task scheduling method based on dynamic priority as claimed in claim 1, wherein the method comprises the following steps: Using a Bayes linear regression model corresponding to the Bayes updating channel to generate new values of the posterior mean value vector and new values of the posterior covariance matrix, and expressing the new values by the following formula: In the formula, Representing the new values of the posterior covariance matrix, Representing the old values of the posterior covariance matrix, A precision parameter representing the observed noise, Representing the new value of the posterior mean vector, Representing the old value of the posterior mean vector, The transpose is represented by the number, The national cipher task-channel joint feature vector representing the ith national cipher task on the jth channel comprises an algorithm type independent thermal code, a normalized value of the national cipher task security level, a channel hardware type independent thermal code, a load factor and a performance stability factor, Representing the actual performance observations of the ith cryptographic task at the jth lane.
8. The multi-channel state-dense task scheduling method based on dynamic priority as claimed in claim 1, wherein the method comprises the following steps: And determining a basic suitability factor according to the affinity of the national encryption task and the multiple channels, wherein the basic suitability factor is expressed by the following formula: In the formula, The basic suitability factor of the ith cryptographic task at the jth lane representing time t, , , Indicating the affinity of the ith cryptographic task to the jth channel, The load factor representing the time t is represented, Represents the security matching degree of the ith cryptographic task and the jth channel, Representing the performance stability factor of the jth channel.
9. The multi-channel state-dense task scheduling method based on dynamic priority as claimed in claim 8, wherein: Correcting the basic suitability factor according to the new value of the posterior covariance matrix, wherein the basic suitability factor is expressed by the following formula: In the formula, Representing the final suitability factor as such, Representing the coefficient of the correction intensity and, Represents the standard deviation of the affinity of the ith national cryptographic task to the jth channel, Representing a preset maximum acceptable prediction uncertainty threshold.
10. A multichannel national cryptographic task scheduling system based on dynamic priority, running a multichannel national cryptographic task scheduling method based on dynamic priority as in any one of claims 1-9, characterized in that: The initial emergency factor generation module is used for determining an initial emergency factor according to the residual time of the national password task distance deadline; The initial emergency factor correction module is used for determining dynamic enhancement factors according to the national density task characteristics by adopting a self-adaptive immune optimization enhancement algorithm, correcting the initial emergency factors according to the dynamic enhancement factors, and obtaining final emergency factors; The final suitability factor generation module is used for generating a new value of a posterior mean vector and a new value of a posterior covariance matrix by using a Bayes linear regression model corresponding to the Bayes updating channel, determining the affinity of the national secret task and the channel according to the new value of the posterior mean vector, determining a basic suitability factor according to the affinity of the national secret task and the multiple channels, and correcting the basic suitability factor according to the new value of the posterior covariance matrix to obtain a final suitability factor; the priority solving module is used for multiplying the dynamic enhancement factor, the final emergency factor and the final suitability factor to obtain the priority of the national cipher task; and the strategy generation module is used for constructing a global optimal allocation model according to the priority of the national secret task and solving to obtain the national secret task scheduling strategy.

Description

Multichannel state-dense task scheduling method and system based on dynamic priority Technical Field The invention belongs to the technical field of information security, and particularly relates to a multichannel national encryption task scheduling method and system based on dynamic priority. Background Along with the continuous increase of the complexity of the network information system, the cryptographic technology is widely applied to key fields such as government affairs, finance, medical treatment, industrial Internet and the like as a core means for guaranteeing data security, identity authentication and communication confidentiality. In order to meet the demands of high concurrency and high real-time password calculation, a multi-channel concurrent execution architecture is generally adopted in the current system, and different types of password tasks are distributed to a plurality of software and hardware channels for processing, so that the overall throughput capacity of the system is improved. However, existing multi-channel cryptographic task scheduling mechanisms still present challenges in terms of efficiency and robustness. The conventional scheduling method is generally based on a static priority strategy or a polling allocation mode, and cannot dynamically adjust a resource scheduling scheme according to the emergency degree of a task, the complexity of an algorithm and the current load of a channel. This static mechanism results in high priority tasks that may be delayed to execute, and even blocked for long periods of time when resources are scarce, severely impacting system response time and quality of service. Furthermore, existing scheduling schemes often lack a fine sense of channel capability, failing to fully utilize high performance channels. Under the background that the system load continuously grows and the task types are increasingly diversified, the resource competition of task scheduling is also more vigorous. However, the conventional static scheduling mechanism shows obvious limitations in the actual environments of dynamic change of task types, fluctuation of resource use states and obvious security level difference, and often cannot reasonably allocate resources, timely respond to high-priority tasks, and even cause the problems of low channel resource utilization rate, out-of-control task delay and the like. Prior art document 1 (CN 116418544B) discloses a high-speed encryption and decryption engine and an encryption and decryption implementation method. The technical scheme mainly focuses on hardware architecture optimization and key management optimization of a cryptographic operation execution engine, and although multi-channel cryptographic service call and multi-stage parallel flow processing are realized, an intelligent task scheduling mechanism is lacked. In the scheduling layer, the service interface state is queried only by adopting a simple polling mode, and the calling instruction is processed according to a fixed sequence, so that dynamic priority adjustment cannot be performed according to multi-dimensional characteristics such as the emergency degree, the safety level, the time sensitivity and the like of the task, and the task cannot be adaptively allocated according to the states such as the real-time load, the performance stability and the safety matching degree of the channel. When high concurrent and multi-type national secret tasks are faced, the static scheduling strategy easily causes the problems of delayed high-priority tasks, uneven channel load, low resource utilization efficiency and the like. Prior art document 2 (CN 107171800B) discloses a scheduling system for a multi-channel cryptographic algorithm. The method has the defects that the scheduling strategy priority setting of the technical scheme only depends on the single characteristic of 'data packet length', the complex requirements of national security tasks on safety, timeliness and the like cannot be comprehensively reflected, and secondly, the channel selection strategy is based on preset and fixed rules, and the channel real-time performance, such as the current throughput deviation, the queue length, the algorithm affinity and the fine consideration of safety level matching, is lacked. Finally, the scheme does not have learning and self-adaption capability, cannot optimize a decision strategy according to the historical scheduling effect, and is difficult to cope with complex and changeable actual scenes. Prior art document 3 (CN 117527881 a) discloses a dynamic crypto-engine scheduling system and scheduling method. The technical scheme does not relate to fine-grained task scheduling of a plurality of computing channels owned by a single cipher machine or a cipher engine, and even if the scheme distributes a cipher machine with excellent performance for an application system, task accumulation and delay still can be caused if the plurality of channels inside the cipher machine are