This paper presents a novel methodology, called COPP, to estimate available bandwidth over a given network path. COPP deploys a particular probe scheme, namely chirp of packet pairs, which is composed of several packe...
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Based on the characteristics of evolution, autonomy and diversity of Internet resources, researchers recently proposed to realize the publication and query of Internet resource information through common DHT (distribu...
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Based on the characteristics of evolution, autonomy and diversity of Internet resources, researchers recently proposed to realize the publication and query of Internet resource information through common DHT (distributed Hash table) information services. However, current research on resource information services is insufficient in generality, usability and adaptability. Aiming at the needs of iVCE (Internet-based virtual computing environment) for resource aggregation, the SDIRIS (scalable distributed resource information service) is proposed to construct. First, the adaptive DHT (A-FissionE) infrastructure is presented, which supports to adapt to different system scale and stability transparently. Second, the MR-FissionE, which is an efficient multiple-attribute range query algorithm, is presented based on A-FissionE. Theoretical analysis and experimental results prove that SDIRIS can realize resource information publication and query efficiently.
We here devise a new method for detecting and assessing RNA secondary structure by using multiple sequence alignment. The central idea of the method is to first detect conserved stems in the alignment using a special ...
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ISBN:
(纸本)1595934804;9781595934802
We here devise a new method for detecting and assessing RNA secondary structure by using multiple sequence alignment. The central idea of the method is to first detect conserved stems in the alignment using a special matrix and then assess them by evaluating the ratio of the signal to the noise. We tested the method on data sets composed of pairwise and three-way alignments of known ncRNAs. For the pairwise tests, our method has sensitivity 61.42% and specificity 97.05% for structural alignments, and sensitivity 42.05% and specificity 98.15% for BLAST alignments. For the three-way tests, our method has sensitivity 65.17% and specificity 97.96% for structural alignments, and sensitivity 40.70% and specificity 97.87% for CLUSTALW alignments. Our method can detect conserved secondary structures in gapped or ungapped RNA alignments. Copyright 2007 ACM.
Given the multi-rate option in most 802.11 standards, rate adaptation based on dynamic channel condition is crucial to the system performance. This paper presents an efficient rate adaptation mechanism at MAC layer, c...
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Given the multi-rate option in most 802.11 standards, rate adaptation based on dynamic channel condition is crucial to the system performance. This paper presents an efficient rate adaptation mechanism at MAC layer, called ERA, to improve the transport layer throughput. Such scheme raises the transmission rate aggressively, e.g., upon only a few consecutive successful transmissions. In opposite, we reduce the transmission rate more cautiously only when the station encounters severe consecutive frame losses or relatively high loss ratio at MAC layer. ERA also attempts to protect the performance under steady condition without losing the ability to respond to the channel variation quickly. We evaluate ERA using NS-2 simulations and find that it performs better than or at least similarly with many other proposals in various scenarios. ERA is a sender-based method and requires minor modification at sender side only, thus completely standard-compliant and very easy to be implemented and deployed.
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.
Given the multi-rate option in most 802.11 standards, rate adaptation based on dynamic channel condition is crucial to the system performance. This paper presents an efficient self-learning rate adaptation mechanism a...
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Given the multi-rate option in most 802.11 standards, rate adaptation based on dynamic channel condition is crucial to the system performance. This paper presents an efficient self-learning rate adaptation mechanism at MAC layer, called SLRA. SLRA takes both the temporal or spatial correlation and cha- nge into account. The rate selection has two steps: one is to evaluate the performance of current rate and decide whether to adjust the rate;the second is to calib- rate the decision according to the historical experiments of rate adjustment at similar channel status. We evaluate SLRA in 802.11 network and find that it can choose the right rate at most time and performs better than other sender-side adaptation schemes.
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.
Feature (gene) selection is a frequently used preprocessingtechnology 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 preprocessingtechnology 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.
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