Particle swarm optimization （PSO） is a new heuristic algorithm which has been applied to many optimization problems successfully. Attribute reduction is a key studying point of the rough set theory, and it has been ...Particle swarm optimization （PSO） is a new heuristic algorithm which has been applied to many optimization problems successfully. Attribute reduction is a key studying point of the rough set theory, and it has been proven that computing minimal reduc- tion of decision tables is a non-derterministic polynomial （NP）-hard problem. A new cooperative extended attribute reduction algorithm named Co-PSAR based on improved PSO is proposed, in which the cooperative evolutionary strategy with suitable fitness func- tions is involved to learn a good hypothesis for accelerating the optimization of searching minimal attribute reduction. Experiments on Benchmark functions and University of California, Irvine （UCI） data sets, compared with other algorithms, verify the superiority of the Co-PSAR algorithm in terms of the convergence speed, efficiency and accuracy for the attribute reduction.展开更多
In an object-based storage system,a novel scheme named EAP(extending attributes page) is presented to enhance the metadata reliability of the system by adding the user object file information attributes page for each ...In an object-based storage system,a novel scheme named EAP(extending attributes page) is presented to enhance the metadata reliability of the system by adding the user object file information attributes page for each user object and storing the file-related attributes of each user object in object-based storage devices.The EAP scheme requires no additional hardware equipments compared to a general method which uses backup metadata servers to improve the metadata reliability.Leveraging a Markov chain,this paper compares the metadata reliability of the system using the EAP scheme with that using only metadata servers to offer the file metadata service.Our results demonstrate that the EAP scheme can dramatically enhance the reliability of storage system metadata.展开更多
基金supported by the National Natural Science Foundation of China (60873069 61171132)+3 种基金the Jiangsu Government Scholarship for Overseas Studies (JS-2010-K005)the Funding of Jiangsu Innovation Program for Graduate Education (CXZZ11 0219)the Open Project Program of Jiangsu Provincial Key Laboratory of Computer Information Processing Technology (KJS1023)the Applying Study Foundation of Nantong (BK2011062)
文摘Particle swarm optimization （PSO） is a new heuristic algorithm which has been applied to many optimization problems successfully. Attribute reduction is a key studying point of the rough set theory, and it has been proven that computing minimal reduc- tion of decision tables is a non-derterministic polynomial （NP）-hard problem. A new cooperative extended attribute reduction algorithm named Co-PSAR based on improved PSO is proposed, in which the cooperative evolutionary strategy with suitable fitness func- tions is involved to learn a good hypothesis for accelerating the optimization of searching minimal attribute reduction. Experiments on Benchmark functions and University of California, Irvine （UCI） data sets, compared with other algorithms, verify the superiority of the Co-PSAR algorithm in terms of the convergence speed, efficiency and accuracy for the attribute reduction.
基金supported by the National Natural Science Foundation of China (No.60873028)the National Basic Research Program (973) of China (No.2004CB318201)+1 种基金the Program for New Century Excellent Talents in University (No.NCET-04-0693)the Innovational Group Project (No.IRT0725),China
文摘In an object-based storage system,a novel scheme named EAP(extending attributes page) is presented to enhance the metadata reliability of the system by adding the user object file information attributes page for each user object and storing the file-related attributes of each user object in object-based storage devices.The EAP scheme requires no additional hardware equipments compared to a general method which uses backup metadata servers to improve the metadata reliability.Leveraging a Markov chain,this paper compares the metadata reliability of the system using the EAP scheme with that using only metadata servers to offer the file metadata service.Our results demonstrate that the EAP scheme can dramatically enhance the reliability of storage system metadata.
