878 resultados para Data-Information-Knowledge Chain


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Cloud Computing is an enabler for delivering large-scale, distributed enterprise applications with strict requirements in terms of performance. It is often the case that such applications have complex scaling and Service Level Agreement (SLA) management requirements. In this paper we present a simulation approach for validating and comparing SLA-aware scaling policies using the CloudSim simulator, using data from an actual Distributed Enterprise Information System (dEIS). We extend CloudSim with concurrent and multi-tenant task simulation capabilities. We then show how different scaling policies can be used for simulating multiple dEIS applications. We present multiple experiments depicting the impact of VM scaling on both datacenter energy consumption and dEIS performance indicators.

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In this paper, we describe dynamic unicast to increase communication efficiency in opportunistic Information-centric networks. The approach is based on broadcast requests to quickly find content and dynamically creating unicast links to content sources without the need of neighbor discovery. The links are kept temporarily as long as they deliver content and are quickly removed otherwise. Evaluations in mobile networks show that this approach maintains ICN flexibility to support seamless mobile communication and achieves up to 56.6% shorter transmission times compared to broadcast in case of multiple concurrent requesters. Apart from that, dynamic unicast unburdens listener nodes from processing unwanted content resulting in lower processing overhead and power consumption at these nodes. The approach can be easily included into existing ICN architectures using only available data structures.

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Information-centric networking (ICN) has been proposed to cope with the drawbacks of the Internet Protocol, namely scalability and security. The majority of research efforts in ICN have focused on routing and caching in wired networks, while little attention has been paid to optimizing the communication and caching efficiency in wireless networks. In this work, we study the application of Raptor codes to Named Data Networking (NDN), which is a popular ICN architecture, in order to minimize the number of transmitted messages and accelerate content retrieval times. We propose RC-NDN, which is a NDN compatible Raptor codes architecture. In contrast to other coding-based NDN solutions that employ network codes, RC-NDN considers security architectures inherent to NDN. Moreover, different from existing network coding based solutions for NDN, RC-NDN does not require significant computational resources, which renders it appropriate for low cost networks. We evaluate RC-NDN in mobile scenarios with high mobility. Evaluations show that RC-NDN outperforms the original NDN significantly. RC-NDN is particularly efficient in dense environments, where retrieval times can be reduced by 83% and the number of Data transmissions by 84.5% compared to NDN.

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BACKGROUND Parents' knowledge about cancer, treatment, potential late effects and necessary follow-up is important to reassure themselves and motivate their child to participate in regular follow-up. We aimed to describe (i) parents' perception of information received during and after treatment; (ii) parents' current needs for information today, and to investigate; and (iii) associations between information needs and socio-demographic and clinical characteristics. METHODS As part of the Swiss Childhood Cancer Survivor Study, a follow-up questionnaire was sent to parents of survivors, diagnosed < 16 years and after 1990, and aged 11-17 years at study. We assessed parents' perception of information received and information needs, concerns about consequences of the cancer and socio-demographic information. Information on clinical data was available from the Swiss Childhood Cancer Registry. RESULTS Of 309 eligible parents, 189 responded (67%; mean time since diagnosis: 11.3 years, SD = 2.5). Parents perceived to have received verbal information (on illness: verbal 91%, written 40%; treatment: verbal 88%, written 46%; follow-up: verbal 85% written 27%; late effects: verbal 75%, written 19%). Many parents reported current information needs, especially on late effects (71%). The preferred source was written general (28%) or verbal information (25%), less favored was online information (12%). Information needs were associated with migration background (P = 0.039), greater concerns about consequences of cancer (P = 0.024) and no information received (P = 0.035). CONCLUSION Parents reported that they received mainly verbal information. However, they still needed further information especially about possible late effects. Individual long-term follow-up plans, including a treatment summary, should be provided to each survivor, preferably in written format.

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The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.

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Information-centric networking (ICN) addresses drawbacks of the Internet protocol, namely scalability and security. ICN is a promising approach for wireless communication because it enables seamless mobile communication, where intermediate or source nodes may change, as well as quick recovery from collisions. In this work, we study wireless multi-hop communication in Content-Centric Networking (CCN), which is a popular ICN architecture. We propose to use two broadcast faces that can be used in alternating order along the path to support multi-hop communication between any nodes in the network. By slightly modifying CCN, we can reduce the number of duplicate Interests by 93.4 % and the number of collisions by 61.4 %. Furthermore, we describe and evaluate different strategies for prefix registration based on overhearing. Strategies that configure prefixes only on one of the two faces can result in at least 27.3 % faster data transmissions.

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In this work, we propose a novel network coding enabled NDN architecture for the delivery of scalable video. Our scheme utilizes network coding in order to address the problem that arises in the original NDN protocol, where optimal use of the bandwidth and caching resources necessitates the coordination of the forwarding decisions. To optimize the performance of the proposed network coding based NDN protocol and render it appropriate for transmission of scalable video, we devise a novel rate allocation algorithm that decides on the optimal rates of Interest messages sent by clients and intermediate nodes. This algorithm guarantees that the achieved flow of Data objects will maximize the average quality of the video delivered to the client population. To support the handling of Interest messages and Data objects when intermediate nodes perform network coding, we modify the standard NDN protocol and introduce the use of Bloom filters, which store efficiently additional information about the Interest messages and Data objects. The proposed architecture is evaluated for transmission of scalable video over PlanetLab topologies. The evaluation shows that the proposed scheme performs very close to the optimal performance

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Quality data are not only relevant for successful Data Warehousing or Business Intelligence applications; they are also a precondition for efficient and effective use of Enterprise Resource Planning (ERP) systems. ERP professionals in all kinds of businesses are concerned with data quality issues, as a survey, conducted by the Institute of Information Systems at the University of Bern, has shown. This paper demonstrates, by using results of this survey, why data quality problems in modern ERP systems can occur and suggests how ERP researchers and practitioners can handle issues around the quality of data in an ERP software Environment.

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Project justification is regarded as one of the major methodological deficits in Data Warehousing practice. As reasons for applying inappropriate methods, performing incomplete evaluations, or even entirely omitting justifications, the special nature of Data Warehousing benefits and the large portion of infrastructure-related activities are stated. In this paper, the economic justification of Data Warehousing projects is analyzed, and first results from a large academiaindustry collaboration project in the field of non-technical issues of Data Warehousing are presented. As conceptual foundations, the role of the Data Warehouse system in corporate application architectures is analyzed, and the specific properties of Data Warehousing projects are discussed. Based on an applicability analysis of traditional approaches to economic IT project justification, basic steps and responsibilities for the justification of Data Warehousing projects are derived.

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Several theories assume that successful team coordination is partly based on knowledge that helps anticipating individual contributions necessary in a situational task. It has been argued that a more ecological perspective needs to be considered in contexts evolving dynamically and unpredictably. In football, defensive plays are usually coordinated according to strategic concepts spanning all members and large areas of the playfield. On the other hand, fewer people are involved in offensive plays as these are less projectable and strongly constrained by ecological characteristics. The aim of this study is to test the effects of ecological constraints and player knowledge on decision making in offensive game scenarios. It is hypothesized that both knowledge about team members and situational constraints will influence decisional processes. Effects of situational constraints are expected to be of higher magnitude. Two teams playing in the fourth league of the Swiss Football Federation participate in the study. Forty customized game scenarios were developed based on the coaches’ information about player positions and game strategies. Each player was shown in ball possession four times. Participants were asked to take the perspective of the player on the ball and to choose a passing destination and a recipient. Participants then rated domain specific strengths (e.g., technical skills, game intelligence) of each of their teammates. Multilevel models for categorical dependent variables (team members) will be specified. Player knowledge (rated skills) and ecological constraints (operationalized as each players’ proximity and availability for ball reception) are included as predictor variables. Data are currently being collected. Results will yield effects of parameters that are stable across situations as well as of variable parameters that are bound to situational context. These will enable insight into the degree to which ecological constraints and more enduring team knowledge are involved in decisional processes aimed at coordinating interpersonal action.

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The shift from host-centric to information-centric networking (ICN) promises seamless communication in mobile networks. However, most existing works either consider well-connected networks with high node density or introduce modifications to {ICN} message processing for delay-tolerant Networking (DTN). In this work, we present agent-based content retrieval, which provides information-centric {DTN} support as an application module without modifications to {ICN} message processing. This enables flexible interoperability in changing environments. If no content source can be found via wireless multi-hop routing, requesters may exploit the mobility of neighbor nodes (called agents) by delegating content retrieval to them. Agents that receive a delegation and move closer to content sources can retrieve data and return it back to requesters. We show that agent-based content retrieval may be even more efficient in scenarios where multi-hop communication is possible. Furthermore, we show that broadcast communication may not be necessarily the best option since dynamic unicast requests have little overhead and can better exploit short contact times between nodes (no broadcast delays required for duplicate suppression).

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This paper presents a conceptual approach to enhance knowledge management by synchronizing mind maps and fuzzy cognitive maps. The use of mind maps allows taking advantage of human creativity, while the application of fuzzy cognitive maps enables to store information expressed in natural language. By applying cognitive computing, it makes possible to gather and extract relevant information out of a data pool. Therefore, this approach is supposed to give a framework that enhances knowledge management. To demonstrate the potential of this framework, a use case concerning the development of a smart city app is presented.

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Information-centric networking (ICN) is a new communication paradigm that has been proposed to cope with drawbacks of host-based communication protocols, namely scalability and security. In this thesis, we base our work on Named Data Networking (NDN), which is a popular ICN architecture, and investigate NDN in the context of wireless and mobile ad hoc networks. In a first part, we focus on NDN efficiency (and potential improvements) in wireless environments by investigating NDN in wireless one-hop communication, i.e., without any routing protocols. A basic requirement to initiate informationcentric communication is the knowledge of existing and available content names. Therefore, we develop three opportunistic content discovery algorithms and evaluate them in diverse scenarios for different node densities and content distributions. After content names are known, requesters can retrieve content opportunistically from any neighbor node that provides the content. However, in case of short contact times to content sources, content retrieval may be disrupted. Therefore, we develop a requester application that keeps meta information of disrupted content retrievals and enables resume operations when a new content source has been found. Besides message efficiency, we also evaluate power consumption of information-centric broadcast and unicast communication. Based on our findings, we develop two mechanisms to increase efficiency of information-centric wireless one-hop communication. The first approach called Dynamic Unicast (DU) avoids broadcast communication whenever possible since broadcast transmissions result in more duplicate Data transmissions, lower data rates and higher energy consumption on mobile nodes, which are not interested in overheard Data, compared to unicast communication. Hence, DU uses broadcast communication only until a content source has been found and then retrieves content directly via unicast from the same source. The second approach called RC-NDN targets efficiency of wireless broadcast communication by reducing the number of duplicate Data transmissions. In particular, RC-NDN is a Data encoding scheme for content sources that increases diversity in wireless broadcast transmissions such that multiple concurrent requesters can profit from each others’ (overheard) message transmissions. If requesters and content sources are not in one-hop distance to each other, requests need to be forwarded via multi-hop routing. Therefore, in a second part of this thesis, we investigate information-centric wireless multi-hop communication. First, we consider multi-hop broadcast communication in the context of rather static community networks. We introduce the concept of preferred forwarders, which relay Interest messages slightly faster than non-preferred forwarders to reduce redundant duplicate message transmissions. While this approach works well in static networks, the performance may degrade in mobile networks if preferred forwarders may regularly move away. Thus, to enable routing in mobile ad hoc networks, we extend DU for multi-hop communication. Compared to one-hop communication, multi-hop DU requires efficient path update mechanisms (since multi-hop paths may expire quickly) and new forwarding strategies to maintain NDN benefits (request aggregation and caching) such that only a few messages need to be transmitted over the entire end-to-end path even in case of multiple concurrent requesters. To perform quick retransmission in case of collisions or other transmission errors, we implement and evaluate retransmission timers from related work and compare them to CCNTimer, which is a new algorithm that enables shorter content retrieval times in information-centric wireless multi-hop communication. Yet, in case of intermittent connectivity between requesters and content sources, multi-hop routing protocols may not work because they require continuous end-to-end paths. Therefore, we present agent-based content retrieval (ACR) for delay-tolerant networks. In ACR, requester nodes can delegate content retrieval to mobile agent nodes, which move closer to content sources, can retrieve content and return it to requesters. Thus, ACR exploits the mobility of agent nodes to retrieve content from remote locations. To enable delay-tolerant communication via agents, retrieved content needs to be stored persistently such that requesters can verify its authenticity via original publisher signatures. To achieve this, we develop a persistent caching concept that maintains received popular content in repositories and deletes unpopular content if free space is required. Since our persistent caching concept can complement regular short-term caching in the content store, it can also be used for network caching to store popular delay-tolerant content at edge routers (to reduce network traffic and improve network performance) while real-time traffic can still be maintained and served from the content store.

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An effective solution to model and apply planning domain knowledge for deliberation and action in probabilistic, agent-oriented control is presented. Specifically, the addition of a task structure planning component and supporting components to an agent-oriented architecture and agent implementation is described. For agent control in risky or uncertain environments, an approach and method of goal reduction to task plan sets and schedules of action is presented. Additionally, some issues related to component-wise, situation-dependent control of a task planning agent that schedules its tasks separately from planning them are motivated and discussed.