909 resultados para indigenous knowledge systems
Resumo:
Various avours of a new research field on (socio-)physical or personal analytics have emerged, with the goal of deriving semantically-rich insights from people's low-level physical sensing combined with their (online) social interactions. In this paper, we argue for more comprehensive data sources, including environmental (e.g. weather, infrastructure) and application-specific data, to better capture the interactions between users and their context, in addition to those among users. To illustrate our proposed concept of synergistic user <-> context analytics, we first provide some example use cases. Then, we present our ongoing work towards a synergistic analytics platform: a testbed, based on mobile crowdsensing and the Internet of Things (IoT), a data model for representing the different sources of data and their connections, and a prediction engine for analyzing the data and producing insights.
Resumo:
Spurred by the consumer market, companies increasingly deploy smartphones or tablet computers in their operations. However, unlike private users, companies typically struggle to cover their needs with existing applications, and therefore expand mobile software platforms through customized applications from multiple software vendors. Companies thereby combine the concepts of multi-sourcing and software platform ecosystems in a novel platform-based multi-sourcing setting. This implies, however, the clash of two different approaches towards the coordination of the underlying one-to-many inter-organizational relationships. So far, however, little is known about impacts of merging coordination approaches. Relying on convention theory, we addresses this gap by analyzing a platform-based multi-sourcing project between a client and six software vendors, that develop twenty-three custom-made applications on a common platform (Android). In doing so, we aim to understand how unequal coordination approaches merge, and whether and for what reason particular coordination mechanisms, design decisions, or practices disappear, while new ones emerge.
Resumo:
Information-centric networking (ICN) enables communication in isolated islands, where fixed infrastructure is not available, but also supports seamless communication if the infrastructure is up and running again. In disaster scenarios, when a fixed infrastructure is broken, content discovery algorit hms are required to learn what content is locally available. For example, if preferred content is not available, users may also be satisfied with second best options. In this paper, we describe a new content discovery algorithm and compare it to existing Depth-first and Breadth-first traversal algorithms. Evaluations in mobile scenarios with up to 100 nodes show that it results in better performance, i.e., faster discovery time and smaller traffic overhead, than existing algorithms.
Resumo:
Information-centric networking (ICN) is a promising approach for wireless communication because users can exploit the broadcast nature of the wireless medium to quickly find desired content at nearby nodes. However, wireless multi-hop communication is prone to collisions and it is crucial to quickly detect and react to them to optimize transmission times and a void spurious retransmissions. Several adaptive retransmission timers have been used in related ICN literature but they have not been compared and evaluated in wireless multi-hop environments. In this work, we evaluate existing algorithms in wireless multi-hop communication. We find that existing algorithms are not optimized for wireless communication but slight modificati ons can result in considerably better performance without increasing the number of transmitted Interests.
Resumo:
Today many business processes are based on IT systems. These systems are exposed to different threats, which may lead to failures of critical business pro-cesses. Thus, enterprises prepare themselves against threats and failures of critical IT systems by means of Business Continuity Management (BCM). The phe-nomenon of outsourcing introduces a new dimension to BCM. In an outsourcing relationship the client organization is still responsible for the continuity of its processes but does not have full control over the implemented business continuity measures. In this paper we build a research model based on institutional and assimilation theories to describe and explain how and why BCM is assimilated in outsourcing relationships. In our case studies we found evidence that primarily coercive and normative pressures influence the assimilation of BCM in outsourcing relationships and support the explanation of variation across enterprises. Mimetic pressures seem to influence the assimilation but do not explain variations.
Resumo:
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
Resumo:
This thesis covers a broad part of the field of computational photography, including video stabilization and image warping techniques, introductions to light field photography and the conversion of monocular images and videos into stereoscopic 3D content. We present a user assisted technique for stereoscopic 3D conversion from 2D images. Our approach exploits the geometric structure of perspective images including vanishing points. We allow a user to indicate lines, planes, and vanishing points in the input image, and directly employ these as guides of an image warp that produces a stereo image pair. Our method is most suitable for scenes with large scale structures such as buildings and is able to skip the step of constructing a depth map. Further, we propose a method to acquire 3D light fields using a hand-held camera, and describe several computational photography applications facilitated by our approach. As the input we take an image sequence from a camera translating along an approximately linear path with limited camera rotations. Users can acquire such data easily in a few seconds by moving a hand-held camera. We convert the input into a regularly sampled 3D light field by resampling and aligning them in the spatio-temporal domain. We also present a novel technique for high-quality disparity estimation from light fields. Finally, we show applications including digital refocusing and synthetic aperture blur, foreground removal, selective colorization, and others.
Resumo:
Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.
Resumo:
Neolithic and Bronze Age wetland sites around the Alps (so called pile-dwellings, Pfahlbauten or palafittes in German/French) are of outstanding universal value (UNESCO-world heritage since 2011). Typical sites are in lakes, rivers and bogs, dating between 5300 and 800 BC. Of common character is the perfect conservation of wood, textiles from plant fabrics and many other organic materials. Larger quantities of sub-fossilized wood, as in the peri-alpine sites, offer the possibility of high-precision dating by dendrochronology. Research in these wetland sites started in the mid-19th century. Through large scale rescue excavations since the 1970s and the evolution of underwater archaeology in the same period the Swiss accumulated a thorough experience with these specific sites. Research in wetland sites is shared between cantonal institutions and universities and led to a worldwide unique accumulation of knowledge. Comparable sites exist outside of the Alpine area, but in much smaller quantities. Regions like Russia (small lakes in NW-Russia) and Macedonia (medium size lakes in the border zone of Macedonia, Albania and Greece) have a high scientific potential; rivers in Ukraine are supposed to have the same type of sites.
Resumo:
Content-Centric Networking (CCN) naturally supports multi-path communication, as it allows the simultaneous use of multiple interfaces (e.g. LTE and WiFi). When multiple sources and multiple clients are considered, the optimal set of distribution trees should be determined in order to optimally use all the available interfaces. This is not a trivial task, as it is a computationally intense procedure that should be done centrally. The need for central coordination can be removed by employing network coding, which also offers improved resiliency to errors and large throughput gains. In this paper, we propose NetCodCCN, a protocol for integrating network coding in CCN. In comparison to previous works proposing to enable network coding in CCN, NetCodCCN permit Interest aggregation and Interest pipelining, which reduce the data retrieval times. The experimental evaluation shows that the proposed protocol leads to significant improvements in terms of content retrieval delay compared to the original CCN. Our results demonstrate that the use of network coding adds robustness to losses and permits to exploit more efficiently the available network resources. The performance gains are verified for content retrieval in various network scenarios.
Resumo:
Information-centric networking (ICN) is a new communication paradigm that aims at increasing security and efficiency of content delivery in communication networks. In recent years, many research efforts in ICN have focused on caching strategies to reduce traffic and increase overall performance by decreasing download times. Since caches need to operate at line-speed, they have only a limited size and content can only be stored for a short time. However, if content needs to be available for a longer time, e.g., for delay-tolerant networking or to provide high content availability similar to content delivery networks (CDNs), persistent caching is required. We base our work on the Content-Centric Networking (CCN) architecture and investigate persistent caching by extending the current repository implementation in CCNx. We show by extensive evaluations in a YouTube and webserver traffic scenario that repositories can be efficiently used to increase content availability by significantly increasing the cache hit rates.
Resumo:
During the last decade wireless mobile communications have progressively become part of the people’s daily lives, leading users to expect to be “alwaysbest-connected” to the Internet, regardless of their location or time of day. This is indeed motivated by the fact that wireless access networks are increasingly ubiquitous, through different types of service providers, together with an outburst of thoroughly portable devices, namely laptops, tablets, mobile phones, among others. The “anytime and anywhere” connectivity criterion raises new challenges regarding the devices’ battery lifetime management, as energy becomes the most noteworthy restriction of the end-users’ satisfaction. This wireless access context has also stimulated the development of novel multimedia applications with high network demands, although lacking in energy-aware design. Therefore, the relationship between energy consumption and the quality of the multimedia applications perceived by end-users should be carefully investigated. This dissertation addresses energy-efficient multimedia communications in the IEEE 802.11 standard, which is the most widely used wireless access technology. It advances the literature by proposing a unique empirical assessment methodology and new power-saving algorithms, always bearing in mind the end-users’ feedback and evaluating quality perception. The new EViTEQ framework proposed in this thesis, for measuring video transmission quality and energy consumption simultaneously, in an integrated way, reveals the importance of having an empirical and high-accuracy methodology to assess the trade-off between quality and energy consumption, raised by the new end-users’ requirements. Extensive evaluations conducted with the EViTEQ framework revealed its flexibility and capability to accurately report both video transmission quality and energy consumption, as well as to be employed in rigorous investigations of network interface energy consumption patterns, regardless of the wireless access technology. Following the need to enhance the trade-off between energy consumption and application quality, this thesis proposes the Optimized Power save Algorithm for continuous Media Applications (OPAMA). By using the end-users’ feedback to establish a proper trade-off between energy consumption and application performance, OPAMA aims at enhancing the energy efficiency of end-users’ devices accessing the network through IEEE 802.11. OPAMA performance has been thoroughly analyzed within different scenarios and application types, including a simulation study and a real deployment in an Android testbed. When compared with the most popular standard power-saving mechanisms defined in the IEEE 802.11 standard, the obtained results revealed OPAMA’s capability to enhance energy efficiency, while keeping end-users’ Quality of Experience within the defined bounds. Furthermore, OPAMA was optimized to enable superior energy savings in multiple station environments, resulting in a new proposal called Enhanced Power Saving Mechanism for Multiple station Environments (OPAMA-EPS4ME). The results of this thesis highlight the relevance of having a highly accurate methodology to assess energy consumption and application quality when aiming to optimize the trade-off between energy and quality. Additionally, the obtained results based both on simulation and testbed evaluations, show clear benefits from employing userdriven power-saving techniques, such as OPAMA, instead of IEEE 802.11 standard power-saving approaches.
Resumo:
The overarching objective of this dissertation is to uncover why and how individually experienced fits and misfits translate into different outcomes of user behavior and satisfaction and whether these individual fit/misfit outcomes are in line with organizational intent. In search of patterns and possible archetype users in the context of ES PIPs, this dissertation is the first study that specifically links the theoretical concepts of the aggregated individual fit experiences with the individual and organizational outcome of these experiences (i.e. behavioral reaction, user satisfaction, and alignment with organizational intent). The case study’s findings provide preliminary support for four archetype users characterized by specific fit/misfit experience-outcome patterns.