An Efficient Stream Data Processing Model for Multiuser Cryptographic Service

Abstract

In view of the demand for high-concurrency massive data encryption and decryption application services in the security field, this paper proposes a dual-channel pipeline parallel data processing model (DPP) according to the characteristics of cryptographic operations and realized cryptographic operations of cross-data streams with different service requirements in a multiuser environment. By encapsulating cryptographic operation requirements in job packages, the input data flow is divided by the dualchannel mechanism and job packages parallel scheduling, which ensures the synchronization between the processing of the dependent job packages and parallel packages and hides the processing of the independent job package in the processing of the dependent job package. Prototyping experiments prove that this model can realize the correct and rapid processing of multiservice cross-data streams. Increasing the pipeline depth and improving the processing performance in each stage of the pipeline are the key to improving the system performance.

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“…Modified first-fit based run time aware data stream scheduling strategy was designed by Sun et al [13]. Dual channel pipeline parallel data processing model was designed in [14]. Yet another method based on double level hybrid genetic algorithm and ant colony optimization was presented by Xu et al [15] to address dynamic simultaneous scheduling problem.…”