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Research on Identification and Addressing of the Internet of Things

Research on Identification and Addressing of the Internet of...

引用

international conference on P2P, parallel, grid, cloud and Internet computing (3PGCIC)

作者： Rui Ma Yue Liu Chun Shan Xiao Lin Zhao Xu An Wang School of Software Beijing Institute of Technology Beijing China Key Laboratory of Information and Network Security Engineering University of Chinese Armed Police Force Xi'an Shanxi China

ISBN: (纸本)9781467394741

It is a key issue that identification and addressing the entity which access the Internet through the wireless network with various short distance transmission protocols. To solve the problem, combining with the existing identification and addressing technology of the Internet and the IOT, this paper proposes a method based on distributed ID. This method can be divided into two stages. It first designs the structure of distributed ID. Using the distributed address allocation algorithm, it implements the automatic allocation of the distributed ID as well as the distributed ID resolution among the global IOT. After that, an addressing scheme is designed to meet demands of the IOT addressing. It first defines the structure of addressing and then implements the routing addressing algorithm which combines Cluster-Tree with Ad-hoc On-demand Distance Vector Routing. This scheme could improve the routing efficiency as well as achieve lower cost, lower energy consumption and higher reliability of the addressing. By the simulation on NS-2 platform, the experimental results highlight the feasibility and effectiveness of the proposed method from three aspects: the correctness of identification allocation, the effectiveness of addressing scheme, and the stability of data transmission.

关键词： Routing Resource management Clustering algorithms Internet Encoding Protocols Ad hoc networks

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Efficiency-Aware Workload Optimizations of Heterogeneous cloud computing for Capacity Planning in Financial Industry

Efficiency-Aware Workload Optimizations of Heterogeneous Clo...

引用

IEEE international conference on Cyber Security and cloud computing (CScloud)

作者： Keke Gai Zhihua Du Meikang Qiu Hui Zhao Department of Computer Science Pace University New York NY USA Faculty of Information Engineering Shenzhen University Shenzhen China Software School Henan University Kaifeng Henan China

ISBN: (纸本)9781467393010

The broad implementation of cloud computing has brought a dramatic change to multiple industries, which derives from the development of the Internet-related technologies. This trend has enabled global enterprises to apply distributed computing techniques to reach many benefits. An effective risk management approach is required for service deliveries and a capacity planning is considered one of the convincing methods for financial industry. However, executing a capacity planning is still encountering a great challenge from bottlenecks of the Web server capacities. The unstable service demands often result in service delays, which embarrasses the competitivenesses of the enterprises. This paper addresses this issue and proposes an approach, named Efficiency-aware cloud-based Workload Optimization (ECWO) Model, using greedy programming to predict server workloads of heterogeneous cloud computing in financial industry. The main algorithms used in the proposed model are Task Mapping Algorithm (TMA) and Efficiency-Aware Task Assignment (EATA) Algorithm. Our experimental evaluations have examined the performance of the proposed scheme.

关键词： cloud computing Servers Capacity planning Industries Computational modeling Prediction algorithms Optimization

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An Effective Strategy for Improving Small File Problem in distributed File System

An Effective Strategy for Improving Small File Problem in Di...

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international conference on Information Science and Control engineering (ICISCE)

作者： Tao Wang Shihong Yao Zhengquan Xu Lian Xiong Xin Gu Xiping Yang Mapping and Remote Sensing Wuhan University Wuhan China

ISBN: (纸本)9781467368513

distributed file systems, such as HDFS, DFS, etc, are adopted to support cloud storage and are designed for optimizing large files access. But unfortunately, the problem of massive small files is neglected and seriously restricts the performance of distributed file systems. To improve and even solve the small file problem, in this paper, user access task is defined. The correlations among the access tasks, applications and access files are constructed by the improved PLSA, and the research object is transferred from file-level to task-level. Then, an effective strategy is proposed to improving small file problem in distributed file system. The strategy merges small files in term of access tasks and selects perfecting targets based on the transition probability of the tasks. Finally, the system efficiency analysis model is established and experimental results, compared with original HDFS, HAR and the schemes of Dong, demonstrate that the proposed strategy effectively reduce the MDS workload and the request response delay.

关键词： Prefetching Delays File systems Servers Merging cloud computing Correlation

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Development of smart cloud management system for photovoltaic generation

Development of smart cloud management system for photovoltai...

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international Future Energy Electronics conference (IFEEC)

作者： Kuo-Hsiung Tseng Yun-Fei Lien Chin-Liang Hiseh Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan R.O.C.

This study proposed using the existing structure of parallel-type PV system data acquisition and monitoring technology in National Taipei University of Technology (NTUT) to construct a smart cloud maintenance and management system. At the project node computer end (central database configuration tool web server), the functions of smart cloud maintenance and management are added, such as historical records, reporting records, reporting summary, supplementary alarm, video, reports generation, and scheduling. Currently, besides being implemented at NUTU, the parallel-type PV system in National Longtan Senior High School is connected to the project node, and uses maintenance and management functions. The management system of this project can connect all public PV systems to the smart cloud maintenance and management system for information sharing, coordinated control, and update of PV data, thus achieve resource sharing.

关键词： Maintenance engineering Monitoring History Databases Servers cloud computing Converters

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UNIO: A unified I/O system framework for hybrid scientific workflow 2nd

UNIO: A unified I/O system framework for hybrid scientific w...

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2nd international conference on cloud computing and Big Data, cloudCom-Asia 2015

作者： Huang, Dan Yin, Jiangling Wang, Jun Zhang, Xuhong Zhang, Junyao Zhou, Jian Department of Electrical and Computer Engineering University of Central Florida Orlando United States

ISBN: (纸本)9783319284293

Recent years have seen an increasing number of Hybrid Scientific Applications. They often consist of one HPC simulation program along with its corresponding data analytics programs. Unfortunately, current computing platform settings do not accommodate this emerging workflow very well. This is mainly because HPC simulation programs store output data into a dedicated storage cluster equipped with parallel File System (PFS). To perform analytics on data generated by simulation, data has to be migrated from storage cluster to compute cluster. This data migration could introduce severe delay which is especially true given an ever-increasing data size. While the scale-up supercomputers equipped with dedicated PFS storage cluster still represent the mainstream HPC, ever increasing scale- out small-medium sized HPC clusters have been supplied to facilitate hybrid scientific workflow applications in fast-growing cloud computing infrastructures such as Amazon cluster compute instances. Different from traditional supercomputer setting, the limited network bandwidth in scale-out HPC clusters makes the data migration prohibitively expensive. To attack the problem, we develop a Unified I/O System Framework (UNIO) to avoid such migration overhead for scale-out small-medium sized HPC clusters. Our main idea is to enable both HPC simulation programs and analytics programs to run atop one unified file system, e.g. data-intensive file system (DIFS in brief). In UNIO, an I/O middle-ware component allows original HPC simulation programs to execute direct I/O operations over DIFS without any porting effort, while an I/O scheduler dynamically smoothes out both disk write and read traffic for both simulation and analysis programs. By experimenting with a real-world scientific workflow over a 46-node UNIO prototype, we found that UNIO is able to achieve comparable read/write I/O performance in small-medium sized HPC clusters equipped with parallel file system. More importantly, since UNIO c

关键词： Supercomputers

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A Dependable Service Path Searching Method in distributed Virtualized Environment Using Adaptive Bonus-Penalty Micro-Canonical Annealing

A Dependable Service Path Searching Method in Distributed Vi...

引用

IEEE international conference on Cyber Security and cloud computing (CScloud)

作者： Huiqiang Wang Shichen Zou Junyu Lin Guangsheng Feng Hongwu Lv Coll. of Comput. Sci. & Technol. Harbin Engineering University Harbin Heilongjiang CN

In distributed Virtualized Environment, service components on a dependable service path will be selected to implement service composition. Searching for the optimal dependable service path is the key to implement dependability assurance, which is a Multi-Constrained Optimal Path problem. However, the existing algorithms have disadvantages of high complexity and low performance, and lacking the consideration of trust relationships and evidence spread among service components during service construction and composition. We proposed the concept of QoD, the Quality of Dependability, introducing some attributes(e.g. component intimacy) to describe and restrict the dependable service path searching in distributed virtualized environment. We also applied Adaptive Bonus-Penalty Micro-canonical Annealing(ABP-MA) to dependable service path searching, and chose service components on the optimal dependable service path to satisfy users' demands for service dependability. The experimental results showed that ABP-MA has the advantages of fast convergence and high search success rate.

关键词： Software Quality of service Algorithm design and analysis Heuristic algorithms Classification algorithms Virtualization Approximation algorithms

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Split-System: The New Frontier of cloud computing

Split-System: The New Frontier of Cloud Computing

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IEEE international conference on Cyber Security and cloud computing (CScloud)

作者： Bharat S. Rawal Ramesh K. Karne Quiang Duan Department of Information Sciences and Technology Penn State Abington Abington PA USA Department of Computer and Information Sciences Towson University Towson MD USA

ISBN: (纸本)9781467393010

Split-protocol computing paradigm uses web services on geographically distributed Web servers. A network of large Split-servers that form the cloud to handles computing and storage task that would otherwise create a heavy CPU utilization for the traditional individual server. The split-protocol concept was devised for load balancing and faster data transmission. Connection and data communication phases are clearly divided between servers without involving the client or the central controlling mechanism, like a dispatcher or a load balancer. In an earlier paper, we demonstrated that the application Split-protocol produces higher performance compared to traditional clusters. Based on the need, different types of split configurations are implemented for throughput, response time, and connection time. The observed throughput improvement was within the range 6.5% - 25% over non-split systems. This paper first time examines the empirical results of Split-system to understand its analytical behavior and compares with traditional non-split systems. Also, this paper prepares the groundwork for the scientific understanding of Split-systems. The split-system technique with given sets of constraints can produce better throughput than conventional equivalent server systems. The performance improvement resulted because of the Split-system operates as a fine-grained pipeline of the parallel system.

关键词： Servers Protocols cloud computing Decision support systems Computer architecture Pipelines Load management

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OSIA: Open Source Intelligence Analysis System Based on cloud computing and Domestic Platform

OSIA: Open Source Intelligence Analysis System Based on Clou...

引用

international conference on Information Science and Control engineering (ICISCE)

作者： Shi-Wei Zhao Ze-Wen Cao Wen-Sen Liu Science and Technology on Information System Engineering Laboratory National University of Defense Technology Hunan China

ISBN: (纸本)9781467368513

Information safety is significant for state security, especially for intelligence service. OSIA (open source intelligence analyzing) system based on cloud computing and domestic platform is designed and implemented in this paper. For the sake of the security and utility of OSIA, all of the middleware and involved OS are compatible with domestic software. OSIA system concentrates on analyzing open source text intelligence and adopts self-designed distributed crawler system so that a closed circle is formed from intelligence acquisition to analysis process and push service. This paper also illustrates some typical applications of anti-terrorist, such as the "organizational member discovery" based on Stanford parser and cluster algorithm, the "member relation exhibition" based on paralleled PageRank algorithm and the like. The results of experiences show that the OSIA system is suitable for large scale textual intelligence analysis.

关键词： Operating systems Security Text mining Servers Artificial intelligence Algorithm design and analysis Crawlers

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Massive Intelligent Power Consumption Information Mining Research

Massive Intelligent Power Consumption Information Mining Res...

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2nd international conference on Simulation and Modeling Methodologies,Technologies and Applications(SMTA 2015)

作者： H.L.Sun J.Ye X.M.Chen H.F.Luo State Grid Chongqing Electric Power Research Institute School of Electrical Engineering Chongqing University

With the development of national unified strong smart grid construction, intelligent community are developing positively, which made various information systems comprehensive on-line. There will be a large number of electrical terminal equipment and new energy access in electricity consumption link at the end of the grid, which will surely generate a lot of basic electricity information and data. Electricity consumption data of smart home in intelligent community is the conduct result of the daily life of each family, which can exactly reflect the user‘s real information needs. The history electrical behavior of user is hidden behind the information. How to transform information into knowledge is the most important issue faced recently. This paper analyzed the intelligent power consumption data mining scope, built the framework of data mining based on cloud computing, proposed by the improved clustering algorithm for parallel data mining.

关键词： Electric intelligent information Price Data mining cloud computing Improved clustering algorithm

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MR-Graph: A Customizable GPU MapReduce

MR-Graph: A Customizable GPU MapReduce

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IEEE international conference on Cyber Security and cloud computing (CScloud)

作者： Zhi Qiao Shuwen Liang Hai Jiang Song Fu Department of Computer Science and Engineering University of North Texas Department of Computer Science Arkansas State University

ISBN: (纸本)9781467393010

The MapReduce programming model has been widely used in Big Data and cloud applications. Criticism on its inflexibility when being applied to complicated scientific applications recently emerges. Several techniques have been proposed to enhance its flexibility. However, some of them exert special requirements on applications, while others fail to support the increasingly popular coprocessors, such as Graphics Processing Unit (GPU). In this paper, we propose MR-Graph, a customizable and unified framework for GPU-based MapReduce, which aims to improve the flexibility, scalability and performance of MapReduce. MR-Graph addresses the limitations and restrictions of the traditional MapReduce execution paradigm. The three execution modes integrated in MR-Graph facilitates users to write their applications in a more flexible fashion by defining a Map and Reduce function call graph. MR-Graph efficiently explores the memory hierarchy in GPUs to reduce the data transfer overhead between execution stages and accommodate big data applications. We have implemented a prototype of MR-Graph and experimental results show the effectiveness of using MR-Graph for flexible and scalable GPU-based MapReduce computing.

关键词： Graphics processing units Programming parallel processing Computational modeling Big data cloud computing Data models

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