Dynamic Services for Assisted Living Environments

Software technologies for assisted living systems can be derived from the more mature domain of pervasive computing and the relative emerging ambient intelligence field. We present herein our position about the need for interoperability enablers extending the software service paradigm and for dependability as key elements of assisted living software systems

Roaming Real-Time Applications - Mobility Services in IPv6 Networks

Emerging mobility standards within the next generation Internet Protocol, IPv6, promise to continuously operate devices roaming between IP networks. Associated with the paradigm of ubiquitous computing and communication, network technology is on the spot to deliver voice and videoconferencing as a standard internet solution. However, current roaming procedures are too slow, to remain seamless for real-time applications. Multicast mobility still waits for a convincing design. This paper investigates the temporal behaviour of mobile IPv6 with dedicated focus on topological impacts. Extending the hierarchical mobile IPv6 approach we suggest protocol improvements for a continuous handover, which may serve bidirectional multicast communication, as well. Along this line a multicast mobility concept is introduced as a service for clients and sources, as they are of dedicated importance in multipoint conferencing applications. The mechanisms introduced do not rely on assumptions of any specific multicast routing protocol in use.Comment: 15 pages, 5 figure

Bayesian Quadrature for Multiple Related Integrals

Bayesian probabilistic numerical methods are a set of tools providing posterior distributions on the output of numerical methods. The use of these methods is usually motivated by the fact that they can represent our uncertainty due to incomplete/finite information about the continuous mathematical problem being approximated. In this paper, we demonstrate that this paradigm can provide additional advantages, such as the possibility of transferring information between several numerical methods. This allows users to represent uncertainty in a more faithful manner and, as a by-product, provide increased numerical efficiency. We propose the first such numerical method by extending the well-known Bayesian quadrature algorithm to the case where we are interested in computing the integral of several related functions. We then prove convergence rates for the method in the well-specified and misspecified cases, and demonstrate its efficiency in the context of multi-fidelity models for complex engineering systems and a problem of global illumination in computer graphics.Comment: Proceedings of the 35th International Conference on Machine Learning (ICML), PMLR 80:5369-5378, 201

Intelligent Computing: The Latest Advances, Challenges and Future

Computing is a critical driving force in the development of human civilization. In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications. Intelligent computing has greatly broadened the scope of computing, extending it from traditional computing on data to increasingly diverse computing paradigms such as perceptual intelligence, cognitive intelligence, autonomous intelligence, and human-computer fusion intelligence. Intelligence and computing have undergone paths of different evolution and development for a long time but have become increasingly intertwined in recent years: intelligent computing is not only intelligence-oriented but also intelligence-driven. Such cross-fertilization has prompted the emergence and rapid advancement of intelligent computing. Intelligent computing is still in its infancy and an abundance of innovations in the theories, systems, and applications of intelligent computing are expected to occur soon. We present the first comprehensive survey of literature on intelligent computing, covering its theory fundamentals, the technological fusion of intelligence and computing, important applications, challenges, and future perspectives. We believe that this survey is highly timely and will provide a comprehensive reference and cast valuable insights into intelligent computing for academic and industrial researchers and practitioners

Poster Abstract: Resource Aware Placement of Data Stream Analytics Operators on Fog Infrastructure for Internet of Things Applications

While cloud computing led the path towards a revolutionary change in the modern day computing aspects, further developments gave way to the Internet of Things and its own range of highly interactive applications. While such a paradigm is more distributed in reach, it also brings forth its own set of challenges in the form of latency sensitive applications, where a quick response highly contributes to efficient usage and QoS (Quality of Service). Fog computing, which is the answer to all such challenges, is rapidly changing the distributed computing landscape by extending the cloud computing paradigm to include widespread resources located at the network edge. While the fog paradigm makes use of edge-ward devices capable of computing, networking and storage, one of the key impending challenges is to determine where to place the data analytic operators for maximum efficiency and least costs for the network and its traffic, the efficient algorithmic solution to which we seek to propose by way of this work underway

On the suitability of time-randomized processors for secure and reliable high-performance computing

Time-randomized processor (TRP) architectures have been shown as one of the most promising approaches to deal with the overwhelming complexity of the timing analysis of high complex processor architectures for safety-related real-time systems. With TRPs the timing analysis step mainly relies on collecting measurements of the task under analysis rather than on complex timing models of the processor. Additionally, randomization techniques applied in TRPs provide increased reliability and security features. In this thesis, we elaborate on the reliability and security properties of TRPs and the suitability of extending this processor architecture design paradigm to the high-performance computing domain