This paper proposes a cooperative distributed natural language understanding model that does syntactic, semantic, and pragmatic *** independently and in parallel, unifying analysis results (logical forms) with those o...
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In this paper, we introduce graph theory into transient stability analysis in power system. In the weighted graph, Vertex weight represents node's parallel computing workload and edge weight represents serial comp...
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ISBN:
(纸本)3540297693
In this paper, we introduce graph theory into transient stability analysis in power system. In the weighted graph, Vertex weight represents node's parallel computing workload and edge weight represents serial computing workload on the border of regions, which reflects the degree of parallelism of computing and improves speed-up ration of system. In order to reduce communication time wastage induced by CSMA protocol in TCP/IP based LAN, asynchronous message passing is used in our method. Simulation results show that it achieves better performance.
作者：
Navarro, Jose A.CERCA
CTTC Av Carl Friedrich Gauss7 Bldg B4 Castelldefels 08860 Spain
This paper presents the first experiences of the author with GEE (Google Earth Engine). A C++ image processing algorithm, still under development, was migrated to this new environment using GEE's web interface and...
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ISBN:
(纸本)9789897582523
This paper presents the first experiences of the author with GEE (Google Earth Engine). A C++ image processing algorithm, still under development, was migrated to this new environment using GEE's web interface and the JavaScript language. The idea is to discover the problems that might arise when migrating to this environment as well as to assess the presumable performance boost that should be achieved. A reduced-more didactic-version of the aforementioned algorithm is presented in a step-by-step way along with a brief description of the advantages and drawbacks-from the authors standpoint-of GEE.
Data replication can be used to reduce bandwidth consumption and access latency in the distributed system where users require remote access to large data objects. In this paper, according to the intrinsic characterist...
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ISBN:
(纸本)3540297693
Data replication can be used to reduce bandwidth consumption and access latency in the distributed system where users require remote access to large data objects. In this paper, according to the intrinsic characteristic of distributed storage system, the parallel replication algorithm NBPRA (Network-Bandwidth-based parallel Replication Algorithm) is proposed. In the NBPRA, according to the network state, several replicas of a data object are selected, which are of the least access cost;then the different parts of the data object are transferred from these replicas, and they are used to make a new replica. The results of performance evaluation show that the NBPRA can utilize the network bandwidth efficiently, provide high data replication efficiency and substantially better access efficiency, and the improvement of system performance is related to the number of different data objects accessed by jobs.
The size of the databases used in today's enterprises has been growing at exponential rates day by day. Simultaneously, the need to process and analyze the large volumes of data for business decision making has al...
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ISBN:
(纸本)9781467317191;9781467317207
The size of the databases used in today's enterprises has been growing at exponential rates day by day. Simultaneously, the need to process and analyze the large volumes of data for business decision making has also increased. In several business and scientific applications, there is a need to process terabytes of data in efficient manner on daily bases. This has contributed to the big data problem faced by the industry due to the inability of conventional database systems and software tools to manage or process the big data sets within tolerable time limits. processing of data can include various operations depending on usage like culling, tagging, highlighting, indexing, searching, faceting, etc operations. It is not possible for single or few machines to store or process this huge amount of data in a finite time period. This paper reports the experimental work on big data problem and its optimal solution using Hadoop cluster, Hadoop distributed File System (HDFS) for storage and using parallelprocessing to process large data sets using Map Reduce programming framework. We have done prototype implementation of Hadoop cluster, HDFS storage and Map Reduce framework for processing large data sets by considering prototype of big data application scenarios. The results obtained from various experiments indicate favorable results of above approach to address big data problem.
This article presents a method for evaluating the CPU power, independently from the system used, in heterogeneous networks of work stations. It is based on the use of Java language in order to ensure application porta...
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ISBN:
(纸本)0769522106
This article presents a method for evaluating the CPU power, independently from the system used, in heterogeneous networks of work stations. It is based on the use of Java language in order to ensure application portability and more particularly on the mechanism of thread CPU processing time measurement introduced in the version 1.5 of Sun Java. That tool will be integrated into the load balancing mechanism which is totally written in Java and that we developed in the LIFL project ADAJ. We show how to evaluate the potential power of the CPU with a software totally written in Java. Moreover, we will justify the results provided by our approach. We will also analyse the exploitation of the calibration tool in order to improve the execution time of parallel and distributedapplications in the context of load balancing in a network of workstations.
Decision support systems are characterized by large data sets and complex queries with multi-way joins, aggregation and nesting. SQLmpp is a highly parallel database server designed to efficiently support these applic...
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Decision support systems are characterized by large data sets and complex queries with multi-way joins, aggregation and nesting. SQLmpp is a highly parallel database server designed to efficiently support these applications. SQLmpp's query processing strategy is driven by three principal goals: 1) data parallelism in all operations, 2) maximal use of any relevant indexes, and 3) minimal processing of complete relations. This paper describes the general query processing techniques and the specific operations used to achieve these goals.
Managing distributed ontologies is a challenging issue in the Semantic Web area. Different to most current distributed ontologies management researches, which focus on ontologies maintenance, evolutions, and versionin...
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ISBN:
(纸本)3540297693
Managing distributed ontologies is a challenging issue in the Semantic Web area. Different to most current distributed ontologies management researches, which focus on ontologies maintenance, evolutions, and versioning, this paper proposes a new distributed ontologies management framework based on the function-oriented perspective, and its goal is to bring multiple distributed ontologies together to provide more powerful capabilities. Ontology mapping is the key factor for manage distributed ontologies. This management framework also proposes a novel approach to eliminate the redundancies and errors of mappings in distributed ontologies.
Computing paradigms are introduced for solving complex problems by analyzing, designing and implementing by complex systems. Computing can be defined as the effective use of computer or computer technology to solve ta...
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ISBN:
(纸本)9781665428644
Computing paradigms are introduced for solving complex problems by analyzing, designing and implementing by complex systems. Computing can be defined as the effective use of computer or computer technology to solve tasks that are goal oriented. Computing is used in development of producing scientific studies, building intelligent systems, channeling different media for communication. Over the last few years, internet became so popular which lead to the increase in computer processing capacity, data storage and communication with one another. Computing has evolved from one technology to another in its field and formed a robust framework over the years. In this paper a survey on different computing paradigms like evergreen computing is cloud computing, to deal with basic scheduling is grid computing, for multi task handing is parallel computing, to handle smart phone data's that is mobile computing, cluster computing, and distributed computing is carried out. These technologies improved the way computing functions and made it easier to the computer world. The applications and research issues of the most of the computing paradigms are discussed in this article. The recent research issues in computing platform are scheduling and security. The scheduling is dealing with data processing from one computing platform to other computing device. Security is one of the important research issues.
The proceedings contains 35 papers. Topics discussed include databases, parallelprocessing systems, distributed computer systems, data processing, large scale systems, data transfer, data storage, storage allocation,...
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The proceedings contains 35 papers. Topics discussed include databases, parallelprocessing systems, distributed computer systems, data processing, large scale systems, data transfer, data storage, storage allocation, information management, computer architectures, computer operating systems and data structures.
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