SensorCloud: Towards the Interdisciplinary Development of a Trustworthy Platform for Globally Interconnected Sensors and Actuators

Although Cloud Computing promises to lower IT costs and increase users' productivity in everyday life, the unattractive aspect of this new technology is that the user no longer owns all the devices which process personal data. To lower scepticism, the project SensorCloud investigates techniques to understand and compensate these adoption barriers in a scenario consisting of cloud applications that utilize sensors and actuators placed in private places. This work provides an interdisciplinary overview of the social and technical core research challenges for the trustworthy integration of sensor and actuator devices with the Cloud Computing paradigm. Most importantly, these challenges include i) ease of development, ii) security and privacy, and iii) social dimensions of a cloud-based system which integrates into private life. When these challenges are tackled in the development of future cloud systems, the attractiveness of new use cases in a sensor-enabled world will considerably be increased for users who currently do not trust the Cloud.Comment: 14 pages, 3 figures, published as technical report of the Department of Computer Science of RWTH Aachen Universit

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

3D GANs and Latent Space: A comprehensive survey

Generative Adversarial Networks (GANs) have emerged as a significant player in generative modeling by mapping lower-dimensional random noise to higher-dimensional spaces. These networks have been used to generate high-resolution images and 3D objects. The efficient modeling of 3D objects and human faces is crucial in the development process of 3D graphical environments such as games or simulations. 3D GANs are a new type of generative model used for 3D reconstruction, point cloud reconstruction, and 3D semantic scene completion. The choice of distribution for noise is critical as it represents the latent space. Understanding a GAN's latent space is essential for fine-tuning the generated samples, as demonstrated by the morphing of semantically meaningful parts of images. In this work, we explore the latent space and 3D GANs, examine several GAN variants and training methods to gain insights into improving 3D GAN training, and suggest potential future directions for further research

The dynamics of the RNA world : Insights and challenges

The problem of the origin of life is not only one of structure but also that of dynamics. Ever since the seminal result of Manfred Eigen in 1971 showing that early template replication suffers from an error threshold, research has tackled the issue of how early genomes could have been dynamically stable without highly evolved mechanisms such as accurate replication and chromosomes. We review the theory of the origin, maintenance and enhancement of the RNA world as an evolving population of dynamical systems. Investigation of sequence space has revealed how structures are allocated in sequence space and how this affects the nature of the error threshold that sets the selectively maintainable genome length. New applications of old dynamical theory are still possible: the application of Gause’s principle of competitive exclusion, based on resource utilisation, to RNA replication predicts that at most four pairs (plus and minus strands) can stably be maintained on four nucleotides. Other mechanisms of early template coexistence should be regarded as additional means to raise the number of coexisting species above the number set by the competitive exclusion principle. One such example is the hypercycle in which templates were postulated to help replication of the next member in a cycle superimposed on individual replication cycles. Although the hypercycle is ecologically unstable it is evolutionarily unstable because it cannot efficiently compete against emerging parasites. Population structure can modify this conclusion but not without further qualification. The simplest form of population structure is limited diffusion on a surface. This simple mechanism can ensure the coexistence of competing ribozymes contributing to surface metabolism as well as the spread of efficient replicases despite the parasite problem. Hypercycles can only be saved by active compartmentalization when replicators are enclosed in reproducing protocells. Once there are protocells there is no need for internal hypercyclic organization, however. Finally we review two crucial adaptations that enhanced the RNA world: chromosomes and enzymatic metabolism. Interestingly, it was shown that these two have been presumably coevolutionarily linked because protocells harbouring unlinked, competing ribozymes are better off if the ribozymes remain inefficient but generalists. The appearance of chromosomes alleviates intragenomic conflict and is enabling constraint for the emergence of specific and efficient enzymes

The dynamics of the RNA world : Insights and challenges

The problem of the origin of life is not only one of structure but also that of dynamics. Ever since the seminal result of Manfred Eigen in 1971 showing that early template replication suffers from an error threshold, research has tackled the issue of how early genomes could have been dynamically stable without highly evolved mechanisms such as accurate replication and chromosomes. We review the theory of the origin, maintenance and enhancement of the RNA world as an evolving population of dynamical systems. Investigation of sequence space has revealed how structures are allocated in sequence space and how this affects the nature of the error threshold that sets the selectively maintainable genome length. New applications of old dynamical theory are still possible: the application of Gause’s principle of competitive exclusion, based on resource utilisation, to RNA replication predicts that at most four pairs (plus and minus strands) can stably be maintained on four nucleotides. Other mechanisms of early template coexistence should be regarded as additional means to raise the number of coexisting species above the number set by the competitive exclusion principle. One such example is the hypercycle in which templates were postulated to help replication of the next member in a cycle superimposed on individual replication cycles. Although the hypercycle is ecologically unstable it is evolutionarily unstable because it cannot efficiently compete against emerging parasites. Population structure can modify this conclusion but not without further qualification. The simplest form of population structure is limited diffusion on a surface. This simple mechanism can ensure the coexistence of competing ribozymes contributing to surface metabolism as well as the spread of efficient replicases despite the parasite problem. Hypercycles can only be saved by active compartmentalization when replicators are enclosed in reproducing protocells. Once there are protocells there is no need for internal hypercyclic organization, however. Finally we review two crucial adaptations that enhanced the RNA world: chromosomes and enzymatic metabolism. Interestingly, it was shown that these two have been presumably coevolutionarily linked because protocells harbouring unlinked, competing ribozymes are better off if the ribozymes remain inefficient but generalists. The appearance of chromosomes alleviates intragenomic conflict and is enabling constraint for the emergence of specific and efficient enzymes

Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration

Future AI applications require performance, reliability and privacy that the existing, cloud-dependant system architectures cannot provide. In this article, we study orchestration in the device-edge-cloud continuum, and focus on AI for edge, that is, the AI methods used in resource orchestration. We claim that to support the constantly growing requirements of intelligent applications in the device-edge-cloud computing continuum, resource orchestration needs to embrace edge AI and emphasize local autonomy and intelligence. To justify the claim, we provide a general definition for continuum orchestration, and look at how current and emerging orchestration paradigms are suitable for the computing continuum. We describe certain major emerging research themes that may affect future orchestration, and provide an early vision of an orchestration paradigm that embraces those research themes. Finally, we survey current key edge AI methods and look at how they may contribute into fulfilling the vision of future continuum orchestration.Comment: 50 pages, 8 figures (Revised content in all sections, added figures and new section