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International Conference on Soft-Computing and Network Security (ICSNS)

作者： Daniel, Alfred Paul, Anand Ahmad, Awais Kyungpook Natl Univ Daegu South Korea

ISBN: (纸本)9781479917532

In this cutthroat era of 21st Century Traffic information is considered as one of the prominent valuable resources in vehicular networks for big data analysis. In order to effectively utilize the acquired resources, big data analysis in near real time will be an appropriate way to produce valuable information from raw data. In order to exhibit the importance of big data investigation, an efficient architecture has been proposed for near real time big data analysis in vehicular networks, which indeed will keep pace with the latest trends and development with respect to emerging big-data paradigm. The proposed architecture, comprises centralized data storage mechanism for batch processing and distributed data storage mechanism for streaming processing in real time analysis. Furthermore a work flow model has also been designed for big data architecture to examine streaming data in near real time process. Furthermore, an algorithm is designed for organizing the vehicle flow in a particular location or place. The proposed system model is for optimal utilization of the massive data set, meant for streaming data in near real time process intended for ITS (Intelligent Transportation System) in a vehicular environment.

关键词： Centralized data storage distributed data storage batch processing stream processing ITS

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BF-MapReduce : A bloom filter Based Efficient Lightweight Search 1

BF-MapReduce : A bloom filter Based Efficient Lightweight Se...

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IEEE Conference Collaboration Internet Computing

作者： Tan, Zi-long Zhou, Ke-ren Zhang, Hao Zhou, Wei Yunnan Univ Sch Software Kunming Peoples R China

ISBN: (纸本)9781509000890

MapReduce is an attractive programming model for large-scale data-parallel applications. However, the original MapReduce framework also needs some optimizations to improve its performance. In this paper, we propose a novel bloom filter based lightweight MapReduce index (BF-MapReduce). Instead of scanning the whole dataset, our approach uses an auxiliary index to quickly skip unnecessary data segments, which can efficiently degrade the processing cost at map phase. Moreover, in order to deal with multi-dimension dataset, a converting schema is proposed. It can map multi-dimension data into one-dimension index. The experimental results show that our approach is efficient and lightweight. It can reduce the task running time dramatically with a little storage and maintenance cost.

关键词： MapReduce Bloom Filter distributed data storage

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Adaptive Services with Cloud Architecture for Telemedicine 6

Adaptive Services with Cloud Architecture for Telemedicine

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6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom 2015)

作者： Garai, Abel Pentek, Istvan Univ Debrecen Dept Informat Technol Debrecen Hungary

ISBN: (纸本)9781467381291

Telemedicine embraces telecommunication and information technologies in order to serve health care at remote locations outside of the premises of medical institutions. These systems produce and process dynamically growing amount of data to keep the pace with this exponential process. Moreover, they need to support real time processing in some cases which requires a dynamically scalable and fault tolerant architecture. Based on the large amount of data we propose for these telemedicine systems an extensible architecture which uses distributed and disjoint databases as an anonymized storage in order to support data analytics. Utilizing services, these methods could help us to create a system which could derive new medical information from the collected data that could be used to find possible treatments for illnesses and discover hitherto unknown correlations between different risk factors, thus involving cognitive aspects in our outlined solution. The future of adaptive telemedicine systems should be based on the successful application of distributed data processing with services in order to produce high value-added structured information flows and innovative knowledge base.

关键词： Telemedicine Systems Cloud Computing Architecture distributed data storage Web service

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Social BIMCloud: a distributed cloud-based BIM platform for object-based lifecycle information exchange

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Visualization in Engineering 2015年第1期3卷 1-20页

作者： Das, Moumita Cheng, Jack Cp Kumar, Srinath S Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

Background: The architecture, engineering and construction (AEC) industry lacks a framework for capturing, managing, and exchanging project, product, and social information over the lifecycle of a building. The current tools have various limitations, such as lack of interoperability, slow to transfer huge building model files, and possibility of data inconsistency. Methods: In this paper, we present a cloud-based BIM server framework namely Social BIMCloud that facilitates BIM information exchange through dynamic merging and splitting of building models. The data model of Social BIMCloud is based on but not limited to IFC. The data model of Social BIMCloud was further extended to accommodate social interactions, by studying the formal modes of communication in the AEC industry. An object-based approach to capture and manage social interactions in AEC projects through a BIM-based visual user interface was also developed and demonstrated. Results: Social BIMCloud addresses the issues of inefficient data transfer speed and data inconsistency in a distributed environment by facilitating the storage and partial exchange of integrated nD BIM models. data interoperability is facilitated through open BIM standards such as IFC and direct integration with construction software. High performance, scalability, fault tolerance, and cost effectiveness are facilitated through data partitioning, data replication strategies, multi-node structures, and pay-per-use tariff systems, respectively, through a cloud-based NoSQL database. Conclusion: The Social BIMCloud framework helps to develop and exchange BIM models, which are rich in project information such as social interactions, cost, and energy analyses. This framework improves the communication efficiency between project participants, leading to better designs and less rework. The information captured by this framework could also be useful to determine important metrics such as industry trends, relationships among project participa

关键词： Building information modeling Cloud computing distributed data storage Partial information exchange Social interaction

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Towards energy-efficient, fault-tolerant, and load-balanced mobile cloud

Towards energy-efficient, fault-tolerant, and load-balanced ...

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作者： Chen, Chien-An Texas A&M University

学位级别：Ph.D.

Recent advances in mobile technologies have enabled a new computing paradigm in which large amounts of data are generated and accessed from mobile devices. However, running resource-intensive applications (e.g., video/image storage and processing or map-reduce type) on a single mobile device still remains off bounds since it requires large computation and storage capabilities. Computer scientists overcome this issue by exploiting the abundant computation and storage resources from traditional cloud to enhance the capabilities of end-user mobile devices. Nevertheless, the designs that rely on remote cloud services sometimes underlook the available resources (e.g., storage, communication, and processing) on mobile devices. In particular, when the remote cloud services are unavailable (due to service provider or network issues) these smart devices become unusable. For mobile devices deployed in an infrastructureless network where nodes can move, join, or leave the network dynamically, the challenges on energy-efficiency, reliability, and load-balance are still largely unexplored. This research investigates challenges and proposes solutions for deploying mobile application in such environments. In particular, we focus on a distributed data storage and data processing framework for mobile cloud. The proposed mobile cloud computing (MCC) framework provides data storage and data processing services to MCC applications such as video storage and processing or map-reduce type. These services ensure the mobile cloud is energy-efficient, fault-tolerant, and load-balanced by intelligently allocating and managing the stored data and processing tasks accounting for the limited resources on mobile devices. When considering the load-balance, the framework also incorporates the heterogeneous characteristics of mobile cloud in which nodes may have various energy, communication, and processing capabilities. All the designs are built on the k-out-of-n computing theoretical foundation. T

关键词： Mobile Cloud Mobile Computing k-out-of-n distributed data storage distributed data processing energy-efficient fault-tolerant load-balanced Thesis

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Web-Service Development of the Grid-Cloud Simulation Tools

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Procedia Computer Science 2015年 66卷 533-539页

作者： Vladimir Korenkov Andrey Nechaevskiy Gennadiy Ososkov Darya Pryahina Vladimir Trofimov Alexander Uzhinskiy Nikita Balashov Joint Institute for Nuclear Research Dubna Russian Federation Plekhanov Russian University of Economics Moscow Russia

A new system for grid and cloud services simulation is presented. The system is focused on improving efficiency of the grid/cloud systems development by using quality indicators of some real system to design and predict its evolution. For this purpose the simulation program are combined with real monitoring system of the grid/cloud service through a special database. The database development and web interface are described.

关键词： Simulation distributed data storage Grid Cloud Computing Big data Optimization Monitoring

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Region-Based Fault-Tolerant distributed File storage System Design in Networks

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NETWORKS 2015年第4期66卷 380-395页

作者： Sen, Arunabha Mazumder, Anisha Banerjee, Sujogya Das, Arun Zhou, Chenyang Shirazipourazad, Shahrzad Arizona State Univ Sch Comp Informat & Decis Syst Engn Comp Sci & Engn Program Tempe AZ 85287 USA

distributed storage of data files in different nodes of a network enhances its fault tolerance capability by offering protection against node and link failures. Reliability is often achieved through redundancy in one of the following two ways: (i) storage of multiple copies of the entire file at different locations (nodes) or (ii) storage of file segments (not entire files) at different node locations. In the (N, K) file distribution scheme, N file segments from a file F are created in such a way that it is possible to reconstruct the entire file, just by accessing any K = N segments. For the reconstruction scheme to work, it is essential that the K segments of the file are stored in nodes that are connected in the network. However, in the event of node/link failures, the network might become disconnected (i.e.,split into several connected components). We focus on node failures that are spatially correlated or region based. Such failures are often encountered in disaster situations or natural calamities where only the nodes in the disaster zone are affected. The first goal of this research is to design a least cost file storage scheme to ensure that no matter which region is destroyed;resulting in fragmentation of the network, a largest connected component of the residual network will have enough file segments with which to reconstruct the entire file. In case the least cost to ensure this objective is within the allocated budget, the storage design will be all region fault-tolerant (ARFT). In case the least cost exceeds the allocated budget, design of an ARFT file storage system design is impossible. The second goal of this research is to design file storage schemes that will be maximum region fault-tolerant within the allocated budget. The third goal of this research is to investigate the impact of the coding parameters N and K on storage requirements for ensuring all region or maximum region fault-tolerant design. We provide approximation algorithms for the probl

关键词： distributed data storage region-based faults fault tolerance ( N,K) coding budget constraints connected components

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A distributed data storage Scheme for Sensor Networks

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1st International ICST Conference, MobiSec 2009

作者： Parakh, Abhishek Kak, Subhash Oklahoma State Univ Dept Comp Sci Stillwater OK 74075 USA

ISBN: (纸本)9783642044335

We present a data storage scheme for sensor networks that achieves the targets of encryption and distributed storage simultaneously. We partition the data to be stored into numerous pieces such that at least a specific number of them have to be brought together to recreate the data. The procedure for creation of partitions does not use any encryption key and the pieces are implicitly secure. These pieces are then distributed over random sensors for storage. Capture or malfunction of one or more (less than a threshold number of sensors) does not compromise the data. The scheme provides protection against compromise of data in specific sensors due to physical capture or malfunction.

关键词： distributed data storage sensor networks

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Asynchronous replication of metadata across multi-master servers in distributed data storage systems

Asynchronous replication of metadata across multi-master ser...

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作者： Akturk, Ismail Louisiana State University

学位级别：硕士

In recent years, scientific applications have become increasingly data intensive. The increase in the size of data generated by scientific applications necessitates collaboration and sharing data among the nation's education and research institutions. To address this, distributed storage systems spanning multiple institutions over wide area networks have been developed. One of the important features of distributed storage systems is providing global unified name space across all participating institutions, which enables easy data sharing without the knowledge of actual physical location of data. This feature depends on the ``location metadata'' of all data sets in the system being available to all participating institutions. This introduces new challenges. In this thesis, we study different metadata server layouts in terms of high availability, scalability and performance. A central metadata server is a single point of failure leading to low availability. Ensuring high availability requires replication of metadata servers. A synchronously replicated metadata servers layout introduces synchronization overhead which degrades the performance of data operations. We propose an asynchronously replicated multi-master metadata servers layout which ensures high availability, scalability and provides better performance. We discuss the implications of asynchronously replicated multi-master metadata servers on metadata consistency and conflict resolution. Further, we design and implement our own asynchronous multi-master replication tool, deploy it in the state-wide distributed data storage system called PetaShare, and compare performance of all three metadata server layouts: central metadata server, synchronously replicated multi-master metadata servers and asynchronously replicated multi-master metadata servers.

关键词： distributed data storage metadata replication asynchronous multi-master replication

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Region based Fault-tolerant distributed File storage System Design Under Budget Constraint 6

Region based Fault-tolerant Distributed File Storage System ...

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6th International Workshop on Reliable Networks Design and Modeling

作者： Mazumder, Anisha Das, Arun Zhou, Chenyang Sen, Arunabha Arizona State Univ Sch Comp Informat & Decis Syst Engn Tempe AZ 85287 USA

ISBN: (纸本)9781479970407

Two independent lines of research, (i) erasure code based file storage system design, and (ii) fault-tolerant network design for spatially correlated (or region-based) failures, have received considerable attention in the networking research community in recent times. A recently proposed (N, K)-coding based distributed file storage scheme ensures complete reconstruction of a file after network fragmentation due to any single region-based fault. For every region of the network, it stores K distinct file segments in one of the largest connected component that results from the fragmentation of the network due to the failure of a region. This distribution scheme provides an all-region fault-tolerant storage system, in the sense that no matter which region of the network fails, a largest connected component of the fragmented network will still have enough distinct file segments with which to reconstruct the file. However, the storage requirement and the associated cost for such an all-region-fault-tolerant storage system may be quite high. As such, with a limited budget it may not be possible to realize such an all-region fault-tolerant storage system. We consider a budget constrained distributed file system design problem and provide solutions that maximizes the number of regions that can be made fault-tolerant, within the specified budget. We show that the problem is NP-complete, and provide an approximation algorithm for the problem. The performance of the approximation algorithm is evaluated through simulation on two real networks. The simulation results demonstrate that the worst case experimental performance is significantly better than the worst case theoretical bound. Moreover, the approximation algorithm almost always produce near optimal solution in a fraction of time needed to find the optimal solution.

关键词： region-based faults (N, K) coding approximation algorithm budget distributed data storage

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