Emergent behavior is an essential feature in multi-agent systems and plays a significant role in the applications of agent technology. Because of the huge gap between individual agents' behaviors and those of the ...
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Emergent behavior is an essential feature in multi-agent systems and plays a significant role in the applications of agent technology. Because of the huge gap between individual agents' behaviors and those of the whole system, specifying and reasoning about emergent behaviors are notoriously difficult. Simulation has been the essential method to study emergent behaviors in multi-agent systems. In this paper, we report an experimental study of the emergent behaviors of self-organized agent communities, in which emergent behaviors play a crucial role. The experiments confirmed the results of a theoretical analysis of agent communities using a formal theory called scenario calculus. It further provided insight into the dynamic features of the system that were very difficult to obtain by using formal logic, such as the speed of convergence to the emergent states and the relationships between the convergence time and various parameters of self-organized agent communities systems.
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.
As an innovative distributed computing technique for sharing the memory resources in high-speed network, RAM Grid exploits the distributed free nodes, and provides remote memory for the nodes which are short of memory...
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As an innovative distributed computing technique for sharing the memory resources in high-speed network, RAM Grid exploits the distributed free nodes, and provides remote memory for the nodes which are short of memory. One of the RAM Grid systems named DRACO, tries to provide cooperative caching to improve the performance of the user node which has mass disk I/O but lacks local memory. However, the performance of DRACO is constrained with the network communication cost. In order to hide the latency of remote memory access and improve the caching performance, we proposed using push- based prefetching to enable the caching providers to push the potential useful memory pages to the user nodes. Specifically, for each caching provider, it employs sequential pattern mining techniques, which adapts to the characteristics of memory page access sequences, on locating useful memory pages for prefetching. We have verified the effectiveness of the proposed method through system analysis and trace-driven simulations.
Searching in large-scale unstructured peer-to-peer networks is challenging due to the lack of effective hint information to guide queries. In this paper, we propose POP, a parallel, collaborative and Probabilistic sea...
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Searching in large-scale unstructured peer-to-peer networks is challenging due to the lack of effective hint information to guide queries. In this paper, we propose POP, a parallel, collaborative and Probabilistic search mechanism, in which query messages are viewed as search units to collaborate with each other and aggregate the distributed hints during the search process. A scheme called distributed Bloom filter (DBF) is presented to propagate the hints with a bandwidth-aware manner, in which a node divides the received Bloom filter vector into subvectors and disseminates the fragments to its neighbors according to their bandwidth capacity. The effectiveness of POP is demonstrated through theoretical analysis and extensive simulations.
As an instance of Internet resource sharing based virtual computing environment, iVCE (Internet based virtual computing environment) for Memory try to solve the problem of memory resource sharing and utilization. Due ...
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As an instance of Internet resource sharing based virtual computing environment, iVCE (Internet based virtual computing environment) for Memory try to solve the problem of memory resource sharing and utilization. Due to the special properties of memory resource, traditional resource management approaches can not be adapted easily. A clustering based resource aggregation scheme is proposed under the background of iVCE for Memory, which can reduce the problem scale efficiently. With analogy to the force field and potential energy theory in physics, the basic model, force field-potential energy model and corresponding distributed algorithms are proposed respectively. The models and algorithms are also evaluated by real network topology based simulation.
In wireless ad hoc networks, the flooding operation is an important utility function. To solve the broadcast storm problem, some efficient flooding schemes have been proposed. However, there also exist many problems i...
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In wireless ad hoc networks, the flooding operation is an important utility function. To solve the broadcast storm problem, some efficient flooding schemes have been proposed. However, there also exist many problems in these schemes, such as signal collision. In this paper, we propose an efficient flooding algorithm called EFDA based on the algorithm proposed in [1] (we reference the algorithm as EF1). Through theoretical analysis, our algorithm doesn't affect the local optimality gained by EF1. We have implemented our algorithm in ns-2 simulator, and the results show that exploiting directional antenna can reduce the number of signal collisions and our algorithm achieves better performance than pure flooding and EF1 due to smaller number of signal collisions.
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.
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