this book contains the combined proceedings of the 4thinternationalconference on Ubiquitous computing Application and Wireless Sensor Network (UCAWSN-15) and the 16thinternationalconference on parallel and Distrib...
ISBN:
(数字)9789811000683
ISBN:
(纸本)9789811000676;9789811000683
this book contains the combined proceedings of the 4thinternationalconference on Ubiquitous computing Application and Wireless Sensor Network (UCAWSN-15) and the 16thinternationalconference on parallel and distributedcomputing, applications and technologies (PDCAT-15). the combined proceedings present peer-reviewed contributions from academic and industrial researchers in fields including ubiquitous and context-aware computing, context-awareness reasoning and representation, location awareness services, and architectures, protocols and algorithms, energy, management and control of wireless sensor networks. the book includes the latest research results, practical developments and applications in parallel/distributed architectures, wireless networks and mobile computing, formal methods and programming languages, network routing and communication algorithms, database applications and data mining, access control and authorization and privacy preserving computation.
Summary form only given. After a brief review on the current status of HPC research and development in China, this talk will introduce the plan of HPC development under the new Key R&D Program of China in the 13th...
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ISBN:
(纸本)9781509050826
Summary form only given. After a brief review on the current status of HPC research and development in China, this talk will introduce the plan of HPC development under the new Key R&D Program of China in the 13th 5-year plan. the motivation of developing the exa-scale computer and the need for establishing an eco-system for high performance computing in China will be presented. the major challenges in developing the exa-scale computer will be discussed. the major R&D activities of the new key project on HPC in the next 5 years will also be presented.
In the last years not only a growth of data-intensive storage has been observed, but also compute-intensive workloads need a high computing power and high parallelism with good performance and great scalability. Many ...
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ISBN:
(纸本)9783319495835;9783319495828
In the last years not only a growth of data-intensive storage has been observed, but also compute-intensive workloads need a high computing power and high parallelism with good performance and great scalability. Many distributed filesystem have focused in how to distribute data across multiple processing nodes, but one of the main problem to solve is the management of the ever-greater number of metadata requests. In fact, some studies have identified that an optimized metadata management is a key factor to achieve good performance. applications in high performance computing usually require filesystems able to provide a huge amount of operations per second to achieve the required level of performance. Although the metadata storage is smaller than data storage, metadata operations consume large CPU cycles, so a single metadata server cannot be longer sufficient. In this paper we define a completely distributed method that provides efficient metadata management and seamlessly adapts to general purpose and scientific computing filesystem workloads. the throughput performance is measured by a metadata benchmark and compared with several distributed filesystems. the results show great scalability in creating operations on a single directory accessed by multiple clients.
the Aho-Corasick algorithm is a multiple patterns searching algorithm running sequentially in various applications like network intrusion detection and bioinformatics for finding several input strings within a given l...
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Withthe development of modern network technology, user demand for power quality is increasing day by day. the paper studies on evaluation of voltage sag exposed areas (VSEA) based on main feeder zone method in large ...
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ISBN:
(纸本)9781509051540
Withthe development of modern network technology, user demand for power quality is increasing day by day. the paper studies on evaluation of voltage sag exposed areas (VSEA) based on main feeder zone method in large scale complex distribution network (DN), which provides analysis basis for feasibility analysis of suffering from voltage sag effects on sensitive load. According to the structure of DN, the theory of the main feeder zone is to partition the network into independent sub networks and coordinate withthe others by the contact line. the zoning principle for each partition is that the size should be equal and the number of contact lines can't be too much. When calculating and analyzing the DN, each partition does it independently and parallelly. After that, relevant parameters of the coordination are sent to a coordination server. then, it calculates relevant parameters of the coordination and sends them to each partition. Short-circuit calculation is the key step in the analysis of VSEA. On the basis of partitioning, short-circuit calculation for VSEA in DN is divided into two parts. One is that when fault point is located in medium voltage power network and another is that when the fault point is located in a single feeder. Experiments have been made on an IEEE 33 test case and a 500 feeders system and the effectiveness of the algorithm is verified.
Master node fault-tolerance is the topic that is often dimmed in the discussion of big data processing technologies. Although failure of a master node can take down the whole data processing pipeline, this is consider...
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ISBN:
(纸本)9783319421087
Master node fault-tolerance is the topic that is often dimmed in the discussion of big data processing technologies. Although failure of a master node can take down the whole data processing pipeline, this is considered either improbable or too difficult to encounter. the aim of the studies reported here is to propose rather simple technique to deal with master-node failures. this technique is based on temporary delegation of master role to one of the slave nodes and transferring updated state back to the master when one step of computation is complete. that way the state is duplicated and computation can proceed to the next step regardless of a failure of a delegate or the master (but not both). We run benchmarks to show that a failure of a master is almost "invisible" to other nodes, and failure of a delegate results in recomputation of only one step of data processing pipeline. We believe that the technique can be used not only in Big Data processing but in other types of applications.
the Finite Element Method is widely used in the industry, how is mentioned in [4]. In this method most of the analysis require huge meshes to discretize the geometry into finite elements. Such meshes are processed slo...
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ISBN:
(纸本)9783319322438;9783319322421
the Finite Element Method is widely used in the industry, how is mentioned in [4]. In this method most of the analysis require huge meshes to discretize the geometry into finite elements. Such meshes are processed slowly in a single modern computer due to the limits on memory and processing units. the problem is tackled by dividing the mesh into several sub-meshes with an algorithm similar to the mentioned in [2], this procedure is known as domain segmentation and it is considered a complex problem by itself, because the segmentation requires to maintain a balanced number of nodes for each sub-domain, while minimizing the number of edges in the boundaries of such domains like in [3]. this is made in order to decrease the intercommunication of process when solving FEM problems in a distributed memory scheme. In this work we parallelize the spectral bisection algorithm proposed in [1]. the output of this algorithm could be used for two purposes, (1) to segment the domain and (2) to enumerate the nodes of the mesh in order to reduce the fill-in of the LU decomposition, this enumeration is also know as labelling.
Geographically Weighted Regression (GWR) is a local version of spatial regression that captures spatial dependency in regression analysis. GWR has many application in practice as a visualization and prediction tool fo...
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ISBN:
(纸本)9781467389297
Geographically Weighted Regression (GWR) is a local version of spatial regression that captures spatial dependency in regression analysis. GWR has many application in practice as a visualization and prediction tool for spatial exploration (e.g in climate, economy, medical). However, this locally regression model is slow in process upon the volume of calculations and the spatial getting bigger. Improving performance of GWR is a critical issue, but their distributed implementations have not been studied. Recently, withthe advent of Spark as well MapReduce framework, the development of machine learning applications and parallel programming becomes easier. In this article, we propose several large-scale implementations of distributed GWR, leveraging Spark framework. We implemented and evaluated these approaches with large datasets. To our best knowledge, this is the first work addressing GWR at large-scale.
In this paper, a construction of distributed multi-user, multi-key searchable encryptions is proposed and analyzed. Our scheme leverages a combination of the Shamir’s threshold secret key sharing, the Pohlig-Hellman ...
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Frequent items in high-speed streaming data are important to many applications like network monitoring and anomaly detecting. To deal with high arrival rate of streaming data, it is desirable that such systems be capa...
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ISBN:
(纸本)9781509007691
Frequent items in high-speed streaming data are important to many applications like network monitoring and anomaly detecting. To deal with high arrival rate of streaming data, it is desirable that such systems be capable of supporting high processing throughput with tight guarantees on errors. In this paper, we address the problem of finding frequent and top-k items, and present a parallel version of the Space Saving algorithm in the context of the open source distributedcomputing system. Based on the theoretical analysis, the errors are restrictively bounded in our algorithm, and our parallel design could achieve high throughput. Taking advantage of the distributedcomputing resources, our evaluation reveals that such design delivers linear speedup with remarkable scalability.
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