Content-Aware Delivery of Scalable Video in Network Coding Enabled Named Data Networks

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

The challenge of applying Geographic Information Systems to Sustainable Mountain Development

In recent years, Geographic Information Systems (GIS) have increasingly been used in a wide array of application contexts for development cooperation in lowlands and mountain areas. When used for planning, implementation, and monitoring, GIS is a versatile and highly efficient tool, particularly in mountain areas characterized by great spatial diversity and inaccessibility. However, the establishment and application of GIS in mountain regions generally presents considerable technical challenges. Moreover, it is necessary to address specific institutional and organizational issues regarding implementation.

Passively Track WiFi Users with an Enhanced Particle Filter using Power-based Ranging

Passive positioning systems produce user location information for third-party providers of positioning services. Since the tracked wireless devices do not participate in the positioning process, passive positioning can only rely on simple, measurable radio signal parameters, such as timing or power information. In this work, we provide a passive tracking system for WiFi signals with an enhanced particle filter using fine-grained power-based ranging. Our proposed particle filter provides an improved likelihood function on observation parameters and is equipped with a modified coordinated turn model to address the challenges in a passive positioning system. The anchor nodes for WiFi signal sniffing and target positioning use software defined radio techniques to extract channel state information to mitigate multipath effects. By combining the enhanced particle filter and a set of enhanced ranging methods, our system can track mobile targets with an accuracy of 1.5m for 50% and 2.3m for 90% in a complex indoor environment. Our proposed particle filter significantly outperforms the typical bootstrap particle filter, extended Kalman filter and trilateration algorithms.

Functional and discrete digital sustainability within the sustainable development goals

The Sustainable Development Goals (SDGs) present the new global agenda by the United Nations for the next 15 years from 2016 to 2030. In this research paper we examine how digital resources may contribute to the achievement of the SDGs. Based on a broad literature review we argue functional digital sustainability supports the SDGs while discrete digital sustainability is required to create and progress knowledge necessary to advance the SDGs. First we explain the perspectives of functional and discrete sustainability; secondly we map the two perspectives onto the 17 SDGs with examples incorporating both perspectives of digital sustainability. We conclude that digital sustainability should encompass both perspectives in order to exploit the full potential of information systems in regard to sustainability transformations.

Inseparable, incapable, or invisible: Why public organizations award no-bid contracts

No-bid contracting is a highly prevalent practice in public procurement of technology services. Alt-hough no-bid contracting is a substantial problem since it reduces competition and welfare, the litera-ture lacks theoretical explanations and empirical tests for why public organizations award no-bid con-tracts. In this paper, we propose three theoretical explanations for no-bid contracting, drawing on transaction cost economics, organizational learning, and institutional theory. We also present how we test these explanations using a comprehensive sample of public procurement transactions. We expect to contribute theoretical explanations for no-bid contracting and practical implications for policy-makers.

Sampling in Open Source Software Development: The case for using the Debian GNUILinux Distribution

Research on open source software (OSS) projects often focuses on the SourceForge collaboration platform. We argue that a GNU/Linwr distribution, such as Debian, is better suited for the sampling ofprojects because it avoids biases and contains unique information only available in an integrated environment. Especially research on the reuse of components can build on dependency information inherent in the Debian GNU/Linux packaging system. This paper therefore contributes to the practice of sampling methods in OSS research and provides empirical data on reuse dependencies in Debian.

Content and Context Aware Strategies for QoS Support in VANETs

The increasing interest in autonomous coordinated driving and in proactive safety services, exploiting the wealth of sensing and computing resources which are gradually permeating the urban and vehicular environments, is making provisioning of high levels of QoS in vehicular networks an urgent issue. At the same time, the spreading model of a smart car, with a wealth of infotainment applications, calls for architectures for vehicular communications capable of supporting traffic with a diverse set of performance requirements. So far efforts focused on enabling a single specific QoS level. But the issues of how to support traffic with tight QoS requirements (no packet loss, and delays inferior to 1ms), and of designing a system capable at the same time of efficiently sustaining such traffic together with traffic from infotainment applications, are still open. In this paper we present the approach taken by the CONTACT project to tackle these issues. The goal of the project is to investigate how a VANET architecture, which integrates content-centric networking, software-defined networking, and context aware floating content schemes, can properly support the very diverse set of applications and services currently envisioned for the vehicular environment.

WEAVE: Efficient Geographical Routing in Large-Scale Networks

We propose WEAVE, a geographical 2D/3D routing protocol that maintains information on a small number of waypoints and checkpoints for forwarding packets to any destination. Nodes obtain the routing information from partial traces gathered in incoming packets and use a system of checkpoints along with the segments of routes to weave end-to-end paths close to the shortest ones. WEAVE does not generate any control traffic, it is suitable for routing in both 2D and 3D networks, and does not require any strong assumption on the underlying network graph such as the Unit Disk or a Planar Graph. WEAVE compares favorably with existing protocols in both testbed experiments and simulations.

The Impact of Human Asset Specificity on the Sourcing of Application Services

The question concerning the circumstances under which it is advantageous for a company to outsource certain information systems functions has been a controversial issue for the last decade. While opponents emphasize the risks of outsourcing based on the loss of strategic potentials and increased transaction costs, proponents emphasize the strategic benefits of outsourcing and high potentials of cost-savings. This paper brings together both views by examining the conditions under which both the strategic potentials as well as savings in production and transaction costs of developing and maintaining software applications can better be achieved in-house as opposed to by an external vendor. We develop a theoretical framework from three complementary theories and test it empirically based on a mail survey of 139 German companies. The results show that insourcing is more cost efficient and advantageous in creating strategic benefits through IS if the provision of application services requires a high amount of firm specific human assets. These relationships, however, are partially moderated by differences in the trustworthiness and intrinsic motivation of internal versus external IS professionals. Moreover, capital shares with an external vendor can lower the risk of high transaction costs as well the risk of loosing the strategic opportunities of an IS.

Forecasting Intraday Stock Price Trends with Text Mining Techniques

In this paper, we describe NewsCATS (news categorization and trading system), a system implemented to predict stock price trends for the time immediately after the publication of press releases. NewsCATS consists mainly of three components. The first component retrieves relevant information from press releases through the application of text preprocessing techniques. The second component sorts the press releases into predefined categories. Finally, appropriate trading strategies are derived by the third component by means of the earlier categorization. The findings indicate that a categorization of press releases is able to provide additional information that can be used to forecast stock price trends, but that an adequate trading strategy is essential for the results of the categorization to be fully exploited.