A two-phase monadic approach is presented for monadically slicing programs with procedures. In the monadic slice algorithm for interprocedural programs, phase 1 initializes the slice table of formal parameters in a pr...
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A two-phase monadic approach is presented for monadically slicing programs with procedures. In the monadic slice algorithm for interprocedural programs, phase 1 initializes the slice table of formal parameters in a procedure with the given labels, and then captures the callees＇ influence on callers when analyzing call statements. Phase 2 captures the callees＇ dependence on callers by replacing all given labels appearing in the corresponding sets of formal parameters. By the introduction of given labels, this slice method can obtain similar summary information in system-dependence-graph（SDG）-based algorithms for addressing the calling-context problem. With the use of the slice monad transformer, this monadic slicing approach achieves a high level of modularity and flexibility. It shows that the monadic interprocedural algorithm has less complexity and it is not less precise than SDG algorithms.
Based on the monitoring and discovery service 4 （MDS4） model, a monitoring model for a data grid which supports reliable storage and intrusion tolerance is designed. The load characteristics and indicators of comput...
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Based on the monitoring and discovery service 4 （MDS4） model, a monitoring model for a data grid which supports reliable storage and intrusion tolerance is designed. The load characteristics and indicators of computing resources in the monitoring model are analyzed. Then, a time-series autoregressive prediction model is devised. And an autoregressive support vector regression（ ARSVR） monitoring method is put forward to predict the node load of the data grid. Finally, a model for historical observations sequences is set up using the autoregressive （AR） model and the model order is determined. The support vector regression（SVR） model is trained using historical data and the regression function is obtained. Simulation results show that the ARSVR method can effectively predict the node load.
针对云计算环境下的安全性和隐私性问题,在CP-ABE的基础上提出MAH-ABE(Multiple and Hierarchical Attribute Based Encryption)访问控制模型,划分了公共领域和私人领域,私人领域采用CP,ABE密文访问控制,公共领域采用等级多信任机构来...
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针对云计算环境下的安全性和隐私性问题,在CP-ABE的基础上提出MAH-ABE(Multiple and Hierarchical Attribute Based Encryption)访问控制模型,划分了公共领域和私人领域,私人领域采用CP,ABE密文访问控制,公共领域采用等级多信任机构来管理属性和密钥,减少了管理复杂度.同时,该模型引入失效时间属性来执行属性更新操作.最后给出模型的安全性证明和仿真,表明该模型是高效灵活,细粒度并且安全的.
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