Peer-to-Peer (P2P) computing systems are rapidly growing in importance as the medium of choice for the mass storage. Peers in the most P2P systems randomly choose logical neighbors without any knowledge about underlyi...
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This paper proposes an optimistic data consistency method according to the question about data dependence in data consistency. In the method, data object is partitioned into data blocks by fixed size as the basic unit...
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This paper proposes an optimistic data consistency method according to the question about data dependence in data consistency. In the method, data object is partitioned into data blocks by fixed size as the basic unit of data management. Updates are compressed by Bloom filter technique and propagated in double-path. Negotiation algorithms detect and reconcile update conflicts, and dynamic data management algorithms accommodate dynamic data processing. The results of the performance evaluation show that it is an efficient method to achieve consistency, good dynamic property, and strong robustness when choosing the size of data block appropriately. At the same time, a feasible way is put forward on how to choose appropriate data block size.
The features of simple description, small updates item and weak dependence are the main characteristics of updates of key-attributes in P2P systems. Accordingly, an optimistic data consistency maintenance method based...
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The features of simple description, small updates item and weak dependence are the main characteristics of updates of key-attributes in P2P systems. Accordingly, an optimistic data consistency maintenance method based on key-attributes is proposed. In the method, the update of key-attributes is separated from user update requests. key-Updates are propagated by latency-overlay update propagation model, that is, updates are always propagated to the nodes having maximum or minimum latency, and assured and uncertain propagation paths of updates are all taken into account. Based on classifying key-update conflicts, a double-level reconciling mechanism including buffer preprocessing and update-log processing is applied to detect and reconcile conflicts, and then conflicts are solved by policies as last-writer-win and divide-and-rule. Lastly, update-log management method and maintenance method brought by node failure and network partitioning are discussed for the above is deployed based on the information storied in update-log. Delaying key-attributes updates cannot occur by the optimistic disposal method, and then it cannot depress efficiency of resource location based on key-attributes, which adapts well to P2P systems for Internet. The simulation results show that it is an effective optimistic data consistency maintenance method, achieving good consistency overhead, resource location and resource access overhead, and having strong robustness.
Due to the characteristics of stream applications and the insufficiency of conventional processors when running stream programs, stream processors which support data-level parallelism become the research hotspot. This...
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Due to the characteristics of stream applications and the insufficiency of conventional processors when running stream programs, stream processors which support data-level parallelism become the research hotspot. This paper presents two means, stream partition (SP) and stream compression (SC), to optimize streams on Imagine. The results of simulation show that SP and SC can make stream applications take full advantage of the parallel clusters, pipelines and three-level memory hierarchy of the Imagine processor, and then reduce the execution time of stream programs.
UML dynamic models are important for software analysis and design. Verifying UML dynamic models to find design errors earlier is a key issue for ensuring software quality. Because of the characteristics such as concur...
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UML dynamic models are important for software analysis and design. Verifying UML dynamic models to find design errors earlier is a key issue for ensuring software quality. Because of the characteristics such as concurrency and hierarchy, model checking of UML Statecharts and collaboration diagrams faces the problem of state explosion. In this paper, UML Statecharts is firstly structurally expressed by hierarchical automata and its semantics for open systems is introduced. Then, the synchronization composition of objects in UML collaboration diagrams is expatiated, based on which the global system behaviors can be constructed. Based on hierarchical automata and simulation relation between semantics structures, the compositional rules for verifying concurrent object systems are proposed. It makes possible that the construction of global state space will be unnecessary in model checking of UML collaboration diagrams. The hierarchical structures of UML Statecharts are also brought into the compositional verification, which makes the model checking of implementation models can be carried out through replacing detailed components by abstract specifications.
Feature (gene) selection is a frequently used preprocessing technology for successful cancer classification task in microarray gene expression data analysis. Widely used gene selection approaches are mainly focused on...
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Feature (gene) selection is a frequently used preprocessing technology for successful cancer classification task in microarray gene expression data analysis. Widely used gene selection approaches are mainly focused on the filter methods. Filter methods are usually considered to be very effective and efficient for high-dimensional data. This paper reviews the existing filter methods, and shows the performance of the representative algorithms on microarray data by extensive experimental study. Surprisingly, the experimental results show that filter methods are not very effective on microarray data. We analyze the cause of the result and provide the basic ideas for potential solutions.
With the never-ending growth of the complexity of modern hardware and software systems, more and more sophisticated methods of verification are required. Model checking has been proved to be an effective approach to g...
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With the never-ending growth of the complexity of modern hardware and software systems, more and more sophisticated methods of verification are required. Model checking has been proved to be an effective approach to guaranteeing the correctness of design and implementation of software and hardware system. Model and temporal logics are used as specification languages in software and hardware verification. Modal μ-calculus is an extremely popular and important one among these logics. It is succinct in syntax and powerful in expressiveness. Since Kozen's paper on modal μ-calculus, it has received ever growing interest in both theoretical and application aspects. Based on the focus game theory, Lange and Stirling proposed the axiom systems for LTL and CTL. This paper extends that idea to that for modal μ-calculus. A game-theoretic approach is presented to test the satisfiability of modal μ-calculus formulas. In addition, this approach converts the satisfiability problem for μ-calculus into a solving problem for focus games. Consequently, based on these game rules, an axiom system for μ-calculus is developed, and the completeness of this deductive system can be proved via the game based satisfiability testing procedure. By comparison, this axiom system is much more intuitive and succinct than the existing μ-calculus axiom systems.
In this paper, according to the resource management problems brought by a large number of replicas, a multi-replica clustering management method based on limited-coding is proposed. In this method, according to the pr...
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In this paper, according to the resource management problems brought by a large number of replicas, a multi-replica clustering management method based on limited-coding is proposed. In this method, according to the process of creating new replicas from existent single replica, replicas are partitioned into different hierarchies and clusters. Then replicas are coded and managed based on the user-defined limited-coding rule consisting of replica hierarchy and replica sequence, which can also dispose the alteration of clusters caused by dynamic adjustments on replicas (replica addition or replica removal) effectively. After that, a management model of centralization in local and peer to peer in wide area is adopted to organize replicas, and the cost of reconciling consistency can be greatly depressed combining with defined minimal-time of update propagation. The relevance between the coding rule and the number of replicas, and the solutions to replica failure and replica recover are discussed. The results of the performance evaluation show that the clustering method is an efficient way to manage a large number of replicas, achieving good scalability, not sensitive to moderate node failure, and adapting well to applications with frequent updates.
Data replication introduces well-known consistency issues. This paper puts forward the question about data dependence in data consistency, which embodies pseudo-conflict updates and update dependency. According to tha...
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Rough set theory has been widely and successfully used in data mining, especially in classification field. But most existing rough set based classification approaches require computing optimal attribute reduction, whi...
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