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检索条件"任意字段=8th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2012"

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A Secure and Reliable Construction Scheme for Enterprise Value Chain Networks

A Secure and Reliable Construction Scheme for Enterprise Val...

引用

ieee international conference on High Performance computing and Communications (HPCC)

作者： Chaoxia Qin Bing Guo Yuting Zhao Yan Shen College of Computer Science Sichuan University Chengdu China School of Computer Science Chengdu University of Information Technology Chengdu China

A value chain optimizes the economic benefit of an enterprise alliance by integrating the cooperation relationships among the upstream and downstream companies. Nevertheless, the absence of information security mechanisms within the value chain limits the horizontal cooperation between competing enterprises. the paper proposes a scheme for building an enterprise value chain network based on an alliance blockchain. In the scheme, a distributed authentication technology and cross-chain transaction technology are introduced into the value chain, which enhances the security and reliability of value chain information and facilitates horizontal cooperation among companies. Using Hyperledger Fabric platform, we simulate and extensively evaluate an enterprise value chain network. Experimental results demonstrate the feasibility of the proposed scheme, which can serve as a guide for the construction of enterprise value chain networks in the real world.

关键词： Economics distributed ledger Buildings Authentication Information security Focusing Companies

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Demonstration abstract: Globally interconnected WSAN testbeds

Demonstration abstract: Globally interconnected WSAN testbed...

引用

ieee Annual conference on Pervasive computing and Communications Workshops (PerCom)

作者： Lasse thiem Gabriele Goldacker Mario Schuster thomas Luckenbach Byung Kyu Kim Fraunhofer Institute for Open Communication Systems Berlin Germany National Information and Society Agency Seoul South Korea

this demonstration presents the ongoing development of a framework for a global wireless sensor / actuator network (GWSAN). this GWSAN is formed through the interconnection of about 10 WSAN testbeds currently mainly located in Asia and Europe. GWSANs are one of the enabler for the Internet of things and thus the Web of things. Similar to the beginning of the Internet in the late 70s this GWSAN is a research network. Topics of the joint research and development activities include management, maintenance and interoperability. therefore algorithms and autonomous / automatic configuration mechanisms are implemented and tested as well as remote software updates in distributed WSANs. Furthermore, graphical interfaces for the management and the interaction with GWSAN are part of the development.

关键词： Testing Wireless sensor networks Actuators Asia Europe Internet IP networks Research and development Research and development management Software algorithms

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Practical RF fingerprints for Wireless sensor Network authentication

Practical RF fingerprints for Wireless Sensor Network authen...

引用

international Wireless Communications and Mobile computing conference, IWCMC

作者： D. A. Knox T. Kunz Systems and Computer Engineering Carleton University Ottawa Canada

We demonstrate empirically a physical layer authentication method that uses the physical attributes of OQPSK RF signals transmitted from ieee 802.15.4 WSN nodes, collecting data with a USRP1 software-defined radio platform. We present simple training and classification algorithm alternatives and measure and analyze the performance of the overall combination. We improve classification performance using a simple method at the receiver that discards samples using preamble `PN chip' error information and estimates a phase offset between the transmitting node's RF clock and the receiver's sampling clock.

关键词： Radio frequency Wireless sensor networks Training Classification algorithms Fingerprint recognition Receivers Algorithm design and analysis

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An Expanded distributed Address Assignment Mechanism for Large scale Wireless sensor Network

An Expanded Distributed Address Assignment Mechanism for Lar...

引用

8th international conference on Wireless Communications, Networking and Mobile computing (WiCOM)

作者： Hakchol, Hwang Deng Qingxu Jin Xi Kijun, Kim Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China

ISBN: (纸本)9781612846835;9781612846828

Now the address assignment mechanism of wireless sensor network has a limitation on supporting large scale sensor network that is consisted of more than hundreds of nodes. A distributed address assignment that is indicated in ZigBee Alliance, the standard group related to WSN is a method assigning the address by dividing address area of 16bit into regular blocks according to the depth. But this method has a limitation on expanding network or effective usage of address because it assigns the address uniformly according to the value given at first. this essay comes up with an idea to effectively use reserved address of 16bit address area, which is excluded from the initial value and shows the result with simulation analysis.

关键词： WSN ZigBee Address

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the Influence-Maximizing Node Selection Algorithm Based on Local Isolated Centrality in Large-scale networks Implemented by distributed Graph computing

The Influence-Maximizing Node Selection Algorithm Based on L...

引用

ieee international conference on High Performance computing and Communications (HPCC)

作者： Piaoyang Chen Rong Lei Mingsen Deng School of Information Guizhou University of Finance and Economics Guiyang China

Identifying influence-maximizing (IM) nodes is an effective strategy for designing efficient communication networks or contain the spreading of information for rumors and epidemics with limited budgets. With the growing of the sizes of the social networks, finding solutions to the problem of intfuence − maximizing vertices becomes more and more challenging. Tra-ditionally, the number of users finally affected was the focus. However, the information diffusion speed was becoming a bottle-neck of IM problems. In this paper, we proposed a locality-aware vertex selection strategy based on local isolation centrality (LIC), while the information diffusion experiments used the Independent Cascade (IC) model. the computing scheme was implemented by a distributed graph computing framework. the superiority of the LIC algorithm was confirmed by evaluated on three real-world datasets. It was indistinguishable from algorithms such as K-shell, H-index, degree centrality (DC), local centrality (LC), and VoteRank at the diffusion cascade scale. But it showed better superiority in diffusion speed. More importantly, by comparing LIC with the VoteRank algorithm, which was the closest algorithm on diffusion speed to that of LIC, the huge advantage of the LIC algorithm in terms of time cost was found. We believe that the locality-aware LIC algorithm was more suitable for the influence-maximization problem in very large-scale social networks.

关键词： Epidemics Costs Social networking (online) Computational modeling Communication networks Integrated circuit modeling

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Hybrid Parameter Update: Alleviating Imbalance Impacts for distributed Deep Learning

Hybrid Parameter Update: Alleviating Imbalance Impacts for D...

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ieee international conference on High Performance computing and Communications (HPCC)

作者： Hongliang Li Dong Xu Zhewen Xu Xiang Li College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Changchun China

Nowadays, data parallelism has been widely applied to train large datasets on distributed deep learning clusters, but it has suffered from costly global parameter updates at batch barriers. Performance imbalance among worker instances, introduced by uneven workload partitioning or biased resource allocation, can cause straggly workers, which can lead to severe impacts on both training speed and result accuracy. this paper studies the issue focusing on the tradeoff between training speed and result accuracy. We propose Cooperate Grouping Parallel (CGP), a hybrid parameter update solution that allows the flexibility of both synchronous and asynchronous update schemes. We introduce a novel Cooperate Worker Grouping Problem (CWGP) that seeks a task grouping configuration that leads to maximum model accuracy and holds customized training speed guarantees. We propose an evolution-based Pareto local searching algorithm to compute efficient worker grouping configurations. Comprehensive evaluation results are presented to demonstrate the effectiveness of CGP under both persistent and fluctuant imbalances. the proposed method alleviates the imbalance impacts without introducing extra adjustment over-heads.

关键词： Training Deep learning Computational modeling Focusing distributed databases Parallel processing Resource management

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ReSLB: Load Balanced Workflow for distributed Deep Learning Mass Spectrometry Database

ReSLB: Load Balanced Workflow for Distributed Deep Learning ...

引用

ieee international conference on High Performance computing and Communications (HPCC)

作者： Li Mocheng Liu Yang Ou Yang Chen Zhiguang Xiao Nong Chen Tao Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha China College of Computer National University of Defense Technology Changsha China School of Computer Sun Yat-sen University Guangzhou China State Key Laboratory of Proteomics Beijing Proteome Research Center National Center for Protein Sciences(Beijing) Beijing Institute of Lifeomics Beijing China

the proteomics data analysis pipeline based on the shotgun method requires efficient data processing methods. the parallel algorithm of mass spectrometry database search faces the problems of rapidly expanding database size but low scalability. the heterogeneous database search algorithm based on deep learning is an effective way to solve this problem. Still, the deep learning-based distributed parallel database search algorithm is lacking. this paper analyzes the database searching computational load using a neural network and designs ReSLB, a workflow for the restricted search of mass spectrometry data based on GPU cluster and neural network scoring algorithm. this work aims to ensure the high scalability of future deep learning-based mass spectrometry distributed databases. In the performance estimation of 256 GPUs, the load imbalance of less than 30% and the parallel efficiency of 60% are achieved. Compared with state-of-the-art, the time cost is reduced by 75%, and the parallel efficiency from 1 to 256 GPUs is 3.6x higher than that.

关键词： Deep learning Scalability Neural networks Data preprocessing distributed databases Graphics processing units Clustering algorithms

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3DS: An Efficient DPDK-based Data Distribution Service for distributed Real-time Applications

3DS: An Efficient DPDK-based Data Distribution Service for D...

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ieee international conference on High Performance computing and Communications (HPCC)

作者： Tianyu Xu Xianzhang Chen Changze Wu Jiapin Wang Rongwei Zheng Duo Liu Yujuan Tan Ao Ren Jian Li College of Computer Science Chongqing University Chongqing China School of Big Data and Software Engineering Chongqing University Chongqing China School of Electrical Engineering Chongqing University Chongqing China

Data Distribution Service (DDS) is a widely-used middleware for data transmission in distributed real-time applications, such as autonomous vehicles and robotics. However, the communication of existing DDS middlewares generally relies on the network stacks of the operating system, which brings long latency to the real-time applications. In this paper, we propose a DPDK-based DDS, dubbed 3DS, to improve the performance of communication of DDS middlewares. First, 3DS reduces the latency of communication between distributed real-time applications by avoiding the latency of kernel. Second, 3DS reduces the overhead of dynamic memory allocation and deallocation by a reserved memory pool. Finally, 3DS adopts a thread-exclusive CPU model to reduce the resource contention between threads. We implement and evaluate 3DS on real systems running Linux. the experimental results show that 3DS reduces 44% of the communication latency over FastDDS, which is the state-of-the-art DDS middleware used by ROS2. Moreover, the throughput of data transfer in 3DS can be 1.51 times that of FastDDS.

关键词： three-dimensional displays Smart cities Instruction sets distributed databases throughput Real-time systems Virtual machining

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A programming model for context-aware applications in large-scale pervasive systems

A programming model for context-aware applications in large-...

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ieee international conference on Wireless and Mobile computing, Networking And Communications (WiMob)

作者： Sanjin Sehic Fei Li Stefan Nastic Schahram Dustdar Distributed Systems Group Information Systems Institute University of Technology Vienna Vienna Austria

In recent years, new business and research opportunities have been increasingly emerging in the field of large-scale context-aware pervasive systems (e.g. pervasive health-care, city traffic monitoring, environmental monitoring, smart grids). these large-scale pervasive systems are characterized by the need to employ large number of context sources, process massive amounts of real-time context data, provide services to numerous context-aware applications, and cope with higher volatility of the environment. this paper proposes the Origins Model - a programming model for context-aware applications in large-scale pervasive systems. In the Origins Model, an origin is an abstraction of any source of context information. Origins are universal, discoverable, composable, migratable, and replicable components that are associated with type and meta-information. they create an adequate foundation for the development of context-aware applications. Based on them, four processing operations are defined in the Origins Model: filter, infer, aggregate, and compose. As such, these operations provide a powerful mechanism to express a rich set of processing schemes in context-aware applications. Based on the Origins Model, we present the Origins Toolkit - a proof-of-concept implementation developed using the Scala programming language and the Akka toolkit to provide a distributed, scalable, and fault-tolerant solution.

关键词： Context Context-aware services Context modeling Programming Computational modeling sensors Monitoring

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Weak Network Oriented Mobile distributed Storage: A Hybrid Fault-Tolerance Scheme Based on Potential Replicas

Weak Network Oriented Mobile Distributed Storage: A Hybrid F...

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ieee international conference on High Performance computing and Communications (HPCC)

作者： Xinlei Wei Yujuan Tan Duo Liu Daitao Wu Yu Wu Xianzhang Chen Jian Li College of Computer Science Chongqing University Chongqing China School of Big Data & Software Engineering Chongqing University Chongqing China School of Electrical Engineering Chongqing University Chongqing China

Node failure is one of the most typical issues in distributed storage systems. the classic fault-tolerance methods can meet the fault tolerance needs of systems deployed in edge storage, 5G IoT, and other high-performance data centers. However, mobile distributed systems contend with inconsistent network signals and relatively low bandwidth in weak network environments. the traditional fault-tolerance schemes have difficulty ensuring distributed storage and data repair simultaneously, posing a considerable challenge to data storage reliability. To address this problem, we proposed a hybrid fault-tolerance scheme based on potential replicas, called HFPR, which trades off storage overhead and performance for weak network mobile distributed storage systems. HFPR first stores data with the erasure code redundancy and then gradually increases data redundancy by reserving potential replicas, enabling the system to disperse network transmission pressure and reduce network transmission. To maximize replica utilization and control the storage overhead of potential replicas, we design a node state prediction mechanism and a file lifecycle management mechanism. Evaluation results show that, compared with the traditional hybrid fault-tolerant scheme with the same storage overhead, HFPR achieves better replica-level repair efficiency in data repair and a reduced probability of degraded reads by approximately 50%. During data distribution, HFPR can minimize data write amplification by up to 1.1× and additional network transfers by up to 77.5%.

关键词： Data centers Fault tolerant systems Redundancy distributed databases Memory Bandwidth Maintenance engineering

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