Abstract:

Objective: The popularity of network technology makes more and more enterprises and individuals join the wave of the Internet, and data presents an explosive exponential growth trend.With the increasing demand for data security transmission and fine-grained authentication, the use of cryptographic services in various applications is becoming more frequent. How to deal with random cross and large peak difference cryptographic service requests has gradually become a bottleneck problem restricting various network security applications.A model of cryptographic service scheduling system is proposed to explore the differential dynamic on-demand scheduling of cryptographic service resources.

Methods: Optimized entropy method and cryptographic resource reconstruction technology were used to provide dynamic and extensible cryptographic service resources for users and devices accessing service system. Firstly, the evaluation method of cryptographic device service ability is proposed. By obtaining the operating state information such as the utilization rate of cryptographic resources and network throughput of cryptographic devices,the optimized entropy method is used to process the data. Combined with the cryptographic resource allocation of cryptographic devices, the cryptographic service ability provided by cryptographic devices is described,which provides support for cryptographic job scheduling.Then, an efficient on-demand cryptographic job scheduling strategy is proposed, and the cryptographic service request expectation is proposed. By calculating the load distance of the cryptographic device to determine whether to meet the requirements of the cryptographic service, the cryptographic job scheduling strategy is generated. In addition,the cryptographic devices can be reconstructed according to the scheduling algorithm to meet the differentiated needs of cryptographic services in terms of service quality and service efficiency.

Results:The enhanced Min-Min load balancing algorithm,the cluster load balancing algorithm based on dynamic consistent hashing and the proposed on-demand scheduling algorithm are used for comparison. By sending cryptographic service requests, the maximum completion time of cryptographic operations, the number of serviceable requests per unit time and the average load of FPGA(field programmable gate array)cryptographic computing unit of the three scheduling algorithms are tested respectively.Fig.7 shows that when the number of cryptographic service requests is small,the difference among the three scheduling algorithms is not obvious.However, with the increase of the number of cryptographic service requests,the load of FPGA computing unit gradually increases. The other two scheduling algorithms do not consider the migration of cryptographic jobs and the dynamic configuration of FPGA computing unit, and the queuing time of cryptographic jobs increases significantly, and the gap between the other two scheduling algorithms and the on-demand scheduling algorithm is getting bigger and bigger.Fig.8 shows that when the number of cryptographic service requests is small, the difference of the three scheduling algorithms is not obvious,which can meet most of the cryptographic service requests. However, with the increase of the number of cryptographic service requests, the number of service requests per unit time of the three scheduling algorithms reaches the peak.Because the on-demand scheduling algorithm realizes the cryptographic job migration and the dynamic configuration of FPGA computing units, the number of service requests per unit time is higher than the other two scheduling algorithms.Fig. 9 shows that under the premise of minimizing the migration of cryptographic operations and the reconstruction of FPGA computing units, the on-demand scheduling algorithm prioritizes the cryptographic operations to the same FPGA computing unit.Therefore,only one FPGA computing unit has load when the number of cryptographic service requests is small, and with the increase of the number of cryptographic service requests, the number of FPGA computing units working also increases. Figs. 10 – 11 show that the FPGA load of the other two algorithms is relatively balanced.When the number of cryptographic service requests is large, the load of each FPGA is high.When the new cryptographic service request arrives,the residual calculation ability of FPGA calculation unit is insufficient to meet the cryptographic service demand because the migration of cryptographic jobs and the dynamic configuration of FPGA calculation unit are not considered.

Conclusions: An efficient on-demand scheduling scheme for cryptographic service resources is proposed. The description and dynamic monitoring of cryptographic service capability are realized by using the normalized evaluation model of cryptographic devices based on optimized entropy method. At the same time, a cryptographic job scheduling strategy suitable for different requirements is proposed, and combined with the cryptographic resource reconstruction strategy,the differential configuration and scheduling of cryptographic resources are realized. The dynamic and extensible cryptographic service resources are provided to users and devices of any access service system.

Key words: cryptographic resource, demand-based resource scheduling, high throughput, evaluation model