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data flow management and Compliance in Cloud Computing

IEEE CLOUD COMPUTING 2015年第4期2卷 24-32页

作者： Singh, Jatinder Powles, Julia Pasquier, Thomas Bacon, Jean Univ Cambridge Comp Lab Cambridge CB2 1TN England Univ Cambridge Ctr Intellectual Property & Informat Law Cambridge CB2 1TN England Univ Cambridge Opera Res Grp Distributed Syst Cambridge CB2 1TN England

As cloud computing becomes an increasingly dominant means of providing computing resources, the legal and regulatory issues associated with data in the cloud become more pronounced. These issues derive primarily from four areas: contract, data protection, law enforcement, and regulatory and common law protections for particularly sensitive domains such as health, finance, fiduciary relations, and intellectual property assets. From a technical perspective, these legal requirements all impose information management obligations on data sharing and transmission within cloud-hosted applications and services. They might restrict how, when, where, and by whom data may flow and be accessed. These issues must be managed not only between applications, but also through the entire, potentially global, cloud supply chain.

关键词： Cloud Computing Contracts Law data flow management Cloud Computing Legal Issue Regulatory Issue Contract data Protection Law Enforcement Common Law Protections Legal Requirements Information management Obligations data Sharing Cloud Hosted Applications Cloud Supply Chain Law Cloud Computing Context Access Control Cloud Security Privacy Information flow Control Regulatory Issues Compliance data Protection

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Optimized data flow management in Event Driven Wireless Sensor Networks A Case Study on Landslide Surveillance 7

Optimized Data Flow Management in Event Driven Wireless Sens...

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7th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (IEEE UEMCON)

作者： Petrisor, Daniel Zet, Cristian Fosalau, Cristian Gheorghe Asachi Tech Univ Iasi Fac Elect Engn Iasi Romania

ISBN: (纸本)9781509014965

In this paper, we are presenting a data flow and fault management architecture, developed for an event driven wireless sensor network used in landslide surveillance. Our concept system collects landslide data using a dedicated wireless sensor network. The WSN was configured with tree architecture and contains one gateway, relay nodes, and multiple end nodes. The WSN components were distributed in an array configuration inside the surveyed area. Each WSN component acquired landslide data by means of measurement points mounted on sensing rods and placed in the earth at specific depths. Relay nodes use local data gathered from multiple end nodes to compute a local data trend and evaluate possible alerts. The gateway acquires data from the WSN, manages the data flow and analyzes the global evolution of data in order to issue alerts and warnings related to landslide activity. Also, it verifies the responses of all landslide sensors in order to ensure data consistency and fault management in the entire network. Our proposed data flow management scheme is centered on the possible events that could drive the change of network response time. These events are handled by assessing local and global data trends with respect to predefined markers of landslide data. Once a local or global event is confirmed it triggers the adjustment of system response. Dynamic landslide events require a fast system response in order to ensure precise surveillance. The concept integrates a fault tolerant architecture that uses diagnostic fault codes to ensure data consistency and a flexible data path for all end nodes.

关键词： wireless sensor network event driven WSN data flow management landslide surveillance system data communication

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Programming with Implicit flows

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IEEE SOFTWARE 2014年第5期31卷 52-59页

作者： Salvaneschi, Guido Mezini, Mira Eugster, Patrick Tech Univ Darmstadt Darmstadt Germany Univ Lancaster Lancaster LA1 4YW England Purdue Univ W Lafayette IN 47907 USA

Modern software differs significantly from traditional computer applications that mostly process reasonably small amounts of static input data-sets in batch mode. Modern software increasingly processes massive amounts of data, whereby it is also often the case that new input data is produced and/or existing data is modified on the fly. Consequently, programming models that facilitate the development of such software are emerging. What characterizes them is that data, respectively changes thereof, implicitly flow through computation modules. The software engineer declaratively defines computations as compositions of other computations without explicitly modeling how data should flow along dependency relations between data producer and data consumer modules, letting the runtime to automatically manage and optimize data flows.

关键词： Software Engineering Implicit flows Programming Static Input data Sets Programming Models Software Development Computation Modules data Producer Module data Consumer Module data flow management data flow Optimization Programming Big data Computational Modeling Runtime Software Engineering data Models Market Research Reactive Programming Event Stream Big data data flow Programming Languages Software Engineering

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CCoDaMiC: A framework for Coherent Coordination of data Migration and Computation platforms

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2020年 109卷 1-16页

作者： Dehury, Chinmaya Kumar Srirama, Satish Narayana Chhetri, Tek Raj Univ Tartu Inst Comp Sci Mobile & Cloud Lab EE-50090 Tartu Estonia

The amount of data generated by millions of connected IoT sensors and devices is growing exponentially. The need to extract relevant information from this data in modern and future generation computing system, necessitates efficient data handling and processing platforms that can migrate such big data from one location to other locations seamlessly and securely, and can provide a way to preprocess and analyze that data before migrating to the final destination. Various data pipeline architectures have been proposed allowing the data administrator/user to handle the data migration operation efficiently. However, the modern data pipeline architectures do not offer built-in functionalities for ensuring data veracity, which includes data accuracy, trustworthiness and security. Furthermore, allowing the intermediate data to be processed, especially in the serverless computing environment, is becoming a cumbersome task. In order to fill this research gap, this paper introduces an efficient and novel data pipeline architecture, named as CCoDaMiC (Coherent Coordination of data Migration and Computation), which brings both the data migration operation and its computation together into one place. This also ensures that the data delivered to the next destination/pipeline block is accurate and secure. The proposed framework is implemented in private OpenStack environment and Apache Nifi. (C) 2020 The Authors. Published by Elsevier B.V.

关键词： data pipeline data flow management Serverless computing data migration TOSCA

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New cost-effective VLSI implementation of 2-D discrete cosine transform and its inverse

New cost-effective VLSI implementation of 2-D discrete cosin...

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Conference on Visual Communications and Image Processing 2001

作者： Gong, DN He, Y Tsing Hua Univ Dept Elect Engn State Key Lab Microwave & Digital Commun Beijing 100084 Peoples R China

ISBN: (纸本)0819439886

The two dimensional discrete cosine transform (2-D DCT) has been chosen as the basis in almost all of the recent international image and video coding standards. This paper first categorized the 2-D DCT and inverse DCT (IDCT) architectures. Then a new VLSI architecture for 2-D DCT/IDCT without transpose memory was proposed. The proposed 2-D DCT/IDCT architecture eliminates special transpose circuits and uses general memory modules to store the intermediate results after row-wise transform. The row-wise and column-wise transforms are performed with the different data flow provided by the configurable computation units and data alignment module. The accuracy testing system is set up to search the optimum word-length parameters. Based on the accuracy testing system, the proposed architecture has achieved the smallest word-length compared with reported 2-D DCT architectures.

关键词： discrete cosine transform VLSI row-column method data flow management accuracy analysis

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On combining iteration space tiling with data space tiling for scratch-pad memory systems 05

On combining iteration space tiling with data space tiling f...

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10th Asia and South Pacific Design Automation Conference

作者： Zhang, Chunhui Kurdahi, Fadi Univ Calif Irvine Dept EECS Irvine CA 92697 USA

ISBN: (纸本)0780387368

Most previous studies on tiling concentrate on iteration space only for cache-based memory systems. However, more and more real-time embedded systems are adopting Scratch-Pad Memories (SPMs) which emphasize on the management of data flow through data-oriented tiling. In this paper, we analyze the relationships between iteration space I and data space D, proposing a preliminary classification based on subscript functions. An important real-life application, matrix multiply, is selected to illustrate how we combine the mismatched iteration space tiling with data space tiling for optimal solutions.

关键词： embedded systems storage management memory cards data flow analysis iteration space tiling data space tiling scratch-pad memory systems cache-based memory systems real-time embedded systems data flow management data-oriented tiling subscript functions real-life application matrix multiply memory cards data flow analysis Tile Store management Embedded systems Cache Memory System Notepads iterative methods real-time systems

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One year with the COVID-19 pandemic - Lessons learnt? Intersectoral collaboration measures established during the crisis could benefit capacity and patient flow management in daily clinical practice

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JOURNAL OF HEALTH ORGANIZATION AND management 2022年第2期36卷 141-148页

作者： Hiller, Maike Bracht, Hendrik Schroeder, Stefan Erasmus MC Dept Intens Care Med Rotterdam Netherlands Philips Medizinsysteme Boblingen GmbH Dept Clin Serv Boblingen Germany Univ Hosp Ulm Anesthesiol Intens Care Med & Cent Emergency Med Ulm Germany Hosp Dueren Anesthesiol & Intens Care Med Duren Germany

Purpose The COVID-19 pandemic has changed the way hospitals work. Strategies that were detached from the boundaries of departments and responsibilities in the COVID-19 pandemic have proven themselves under extreme conditions and show a beneficial influence on patient flow and resource management as well as on the communication culture. The continuation of closer interdisciplinary and cross-sectoral co-operation in a "new clinical routine" could have a positive impact on personnel concepts, communication strategies, and the management of acute care capacities and patient pathways. Design/methodology/approach The aim of the paper is to critically discuss the knowledge gained in the context of the COVID-19 pandemic from the various approaches in patient flow and capacity management as well as interdisciplinary co-operation. More recent research has evaluated patient pathway management, personnel planning and communication measures with regard to their effect and practicability for continuation in everyday clinical practice. Findings Patient flows and acute care capacities can be more efficiently managed by continuing a culture change towards closer interdisciplinary and intersectoral co-operation and technologies that support this with telemedicine functionalities and regional healthcare data interoperability. Together with a bi-directional, more frequent and open communication and feedback culture, it could form a "new clinical routine". Originality/value This paper discusses a holistic approach on the way away from silo thinking towards cross-departmental collaboration.

关键词： COVID-19 Intensive care capacity management Patient flow management data flow management Communication culture Intersectoral collaboration

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TOSCAdata: Modeling data pipeline applications in TOSCA✩

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JOURNAL OF SYSTEMS AND SOFTWARE 2022年 186卷 111164-111164页

作者： Dehury, Chinmaya Kumar Jakovits, Pelle Srirama, Satish Narayana Giotis, Giorgos Garg, Gaurav Univ Tartu Inst Comp Sci Mobile & Cloud Lab EE-50090 Tartu Estonia Univ Hyderabad Sch Comp & Informat Sci Hyderabad 500046 India Athens Technol Ctr SA Athens 15233 Greece

The serverless platform allows a customer to effectively use cloud resources and pay for the exact amount of used resources. A number of dedicated open source and commercial cloud data management tools are available to handle the massive amount of data. Such modern cloud data management tools are not enough matured to integrate the generic cloud application with the serverless platform due to the lack of mature and stable standards. One of the most popular and mature standards, TOSCA (Topology and Orchestration Specification for Cloud Applications), mainly focuses on application and service portability and automated management of the generic cloud application components. This paper proposes the extension of the TOSCA standard, TOSCAdata, that focuses on the modeling of data pipeline-based cloud applications. Keeping the requirements of modern data pipeline cloud applications, TOSCAdata provides a number of TOSCA models that are independently deployable, schedulable, scalable, and re-usable, while effectively handling the flow and transformation of data in a pipeline manner. We also demonstrate the applicability of proposed TOSCAdata models by taking a web-based cloud application in the context of tourism promotion as a use case scenario. (c) 2021 Elsevier Inc. All rights reserved.

关键词： data pipeline data flow management Serverless computing data migration TOSCA DevOps

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