Mining log pattern to analyze the faults in large scale distributed system is affected by the existence of redundant and ambiguous noisy error logs. While existing works try to compress logs in a coarse granularity fr...
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Research communities from high energy physics to humanities utilised grid infrastructures to support and accelerate their research. their computations can be executed by different grid technologies: Grids of cluster s...
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ISBN:
(纸本)9783893367504
Research communities from high energy physics to humanities utilised grid infrastructures to support and accelerate their research. their computations can be executed by different grid technologies: Grids of cluster systems, like the German D-Grid, grids of supercomputers, like the distributed European Infrastructure for Supercomputing Applications (DEISA), or desktop grids consolidated in the international Desktop Grid Federation (IDGF). UNICORE is one of the three grid middleware environments supported by the European Middleware Initiative (EMI) for managing a set of cluster or supercomputers, but desktop grids are currently unsupported. this work fills this gap enabling UNICORE to support all three kinds of grid technologies of the European Grid Infrastructure (EGI). this unified interface enables European scientists to access web services, portals, and applications on all grid technologies in the same way.
this paper proposes integration of secure agents with a secure communication infrastructure in order to provide rapid information gathering platform from various information sources and actors participating in a crisi...
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Due to the recent technological improvement of the next-generation sequencers, reading genome sequence of individual DNA becomes popular in biology and medical study. the amount of data produced by next generation seq...
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ISBN:
(纸本)9783642257308
Due to the recent technological improvement of the next-generation sequencers, reading genome sequence of individual DNA becomes popular in biology and medical study. the amount of data produced by next generation sequencers is enormous. Today, more than 10,000 people's DNAs are sequenced in the world and tera-bytes of data are being produced in a daily basis. the types of genome information also vary according to the biological experiments used for preparing DNA samples. Biologists and medical scientists are now facing to manage these huge volumes of data with variety of types. Existing DBMS, whose major targets are business applications, is not suited to managing these biological data because storing such large data to DBMS is time-consuming, and also current database queries cannot accommodate various types of bioinformatics tools written in various programming languages. Processing bioinformatics workflows in parallel and distributed manner is also a challenging problem. In this paper, in hope of recruiting database researchers into this rapidly progressing biology and medical research area, we introduce several challenges in genome informatics from the viewpoint of using existing DBMS for processing next-generation sequencer data.
Mining log pattern to analyze the faults in large scale distributed system is affected by the existence of redundant and ambiguous noisy error logs. While existing works try to compress logs in a coarse granularity fr...
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Mining log pattern to analyze the faults in large scale distributed system is affected by the existence of redundant and ambiguous noisy error logs. While existing works try to compress logs in a coarse granularity from temporal and spatial view to remove the redundancy, they fail to reserve those ambiguous logs that might truly relate to a fault, which misleads the fault characterizing result. By modeling error logs as time series and examining the similarity between trash error log template and target error log, the ambiguous error logs are kept and the affected patterns can be effectively removed. Experiments in a practical complex service-based storage show that up to 92% of the affected patterns can be filtered.
Due to its applicability to numerous types of data, including telephone records, web documents, and click streams, the data stream model has recently attracted attention. For analysis of such data, it is crucial to pr...
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this paper proposes a modified parallel turbo structure based on embedding the unequal error protection concepts in parallel concatenated convolutional codes. these concepts may be required for compressed data packets...
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this paper proposes a modified parallel turbo structure based on embedding the unequal error protection concepts in parallel concatenated convolutional codes. these concepts may be required for compressed data packets transmission whose sensitivities to channel errors are not uniformly distributed. We develop a new method for obtaining turbo gains for unequally protected classes of bits by using a parallel concatenation of encoders separated by increasing size interleavers. A progressive and hierarchical encoding of the decreasing priority bits of one data frame is performed through consecutive partial rate-1 dimensions projections. the result is one data frame whose bits are encoded in a number of dimensions proportional to their respective priority in terms of channel sensitivity to errors. the iterative decoding algorithm is modified in consequence; turbo gains are consistent for all priority subframes during iterations and a noticeable increased gain is obtained for lower level bits. Performances for a two priority data frame are given in comparison withthe classical structure of parallel turbo codes and recursive systematic convolutional code.
Recognized as great works of world literature, Shakespeare's poems and plays have been translated into dozens of languages for over 300 years. Also, there are many re-translations into the same language, for examp...
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Context-based communication allows for the dissemination of messages to mobile users with a specified context, i.e. at a location and with certain attribute values. this enables, e.g., a message to students on campus ...
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Context-based communication allows for the dissemination of messages to mobile users with a specified context, i.e. at a location and with certain attribute values. this enables, e.g., a message to students on campus attending a certain class, with information about a study group for an upcoming exam. An overlay network of context-aware routers efficiently disseminate the messages to all matching receivers. Directed forwarding of such messages requires that the routers maintain knowledge about the contexts of connected users. Global knowledge, i.e., each router knowing about every user, scales poorly, though, because of the necessary updates.
Recent phylogenetic studies reveal that Horizontal Gene Transfer (HGT) events are likely ubiquitous in the Tree of Life. However, our knowledge of HGT's role in evolution and biological organization is very limite...
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ISBN:
(纸本)9783642212598
Recent phylogenetic studies reveal that Horizontal Gene Transfer (HGT) events are likely ubiquitous in the Tree of Life. However, our knowledge of HGT's role in evolution and biological organization is very limited, mainly due to the difficulty tracing HGT events experimentally, and lack of computational models that can capture its dynamics. Here, we present a novel, multi-scale model of microbial populations withthe capacity to study the effect of HGT on complex traits and regulatory network evolution. We describe a parallel load-balancing framework, which was developed to overcome the innate challenges of simulating evolving populations of such magnitude and complexity. Supercomputer simulations of in silico cells that mutate, compete, and evolve, show that HGT can significantly accelerate, but also disrupt, the emergence of advantageous traits in microbial populations. We show that HGT leaves a lasting imprint to gene regulatory networks when it comes to their size and sparsity. In any given experiment, we observed phenotypic variability that can be explained by individual gain and loss of function during evolution. Analysis of the fossil mutational and HGT event record, both for evolved and non-evolved populations, reveals that the distribution of fitness effect for HGT has different characteristics in terms of symmetry, shape and bias from its mutational counterpart. Interestingly, we observed that evolution can be accelerated when populations are exposed in correlated environments of increased complexity, especially in the presence of HGT.
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