【摘要】 针对云密码服务系统中服务请求多样、数据依赖性作业流与非数据依赖性作业流随机交叉并发等问题,为了避免处理节点之间关联数据的交互而带来的系统通信性能开销和数据安全性威胁,设计一种基于关联数据本地化的云密码作业流调度算法。首先通过任务请求密码功能的映射,保障多作业流请求密码功能的正确实现;然后对于具有相同请求密码功能的各任务中不同工作模式交叉问题,在提出任务优先级计算方法以促进多作业流调度公平性的基础上,采用分类调度的方法,在实现关联数据本地化的同时,保障了调度系统的整体性能。仿真结果表明,该算法不仅可以有效减少系统任务完成时间,提高资源利用率和公平性,并且具有良好的稳定性。更多还原

【Abstract】 Aiming at the problems that there are various service requests and data dependent job streams and non-data-dependent job streams are randomly cross-concurred in the cloud cipher service system, in order to avoid the system communication performance overhead and data security threats caused by the interaction of associated data between computing nodes, a cloud cipher job stream sche-duling algorithm based on association data localization is designed. Firstly, the mapping of cryptographic function of the task request is used to ensure the correct implementation of the multi-job streams request function. Secondly, for the problem of different working modes crossing in different tasks with the same request cryptographic function, on the basis of the proposed task priority calculation method to promote the fairness of multi job streams scheduling, the classified scheduling method is adopted to realize the localization of associated data and guarantee the overall performance of the scheduling system. The simulation results show that the algorithm can not only effectively reduce the task completion time and improve resource utilization and fairness, but also has good stability.更多还原