New Ways to Promote Sustainability and Social Well-Being in a Complex, Strongly Interdependent World: The FuturICT Approach

FuturICT is one of six proposals currently being considered for support within the European Commission's Flagship Initiative (see Box 1). The vision of the FuturICT project is to develop new science and new information and communication systems that will promote social self-organization, self-regulation, well-being, sustainability, and resilience. One of the main aims of the approach is to increase individual opportunities for social, economic and political participation, combined with the creation of collective awareness of the impact that human actions have on our world. This requires us to mine large datasets ("Big Data") and to develop new methods and tools: a Planetary Nervous System (PNS) to answer "What is (the state of the world)..." questions, a Living Earth Simulator (LES) to study "What ... if ..." scenarios, and a Global Participatory Platform (GPP) for social exploration and interaction.Comment: For related work see http://www.soms.ethz.ch and http://www.futurict.e

Smart systems, the fourth industrial revolution and new challenges in distributed computing

Smart systems and the smart world concept are addressed in the framework of the fourth industrial revolution. New challenges in distributed autonomous robots and computing are considered. An illustration of a new kind of smart and reconfigurable distributed modular robot system is given. A prototype is also presented as well as the associated distributed algorithm

A Distributed Control Framework of Multiple Unmanned Aerial Vehicles for Dynamic Wildfire Tracking

Wild-land fire fighting is a hazardous job. A key task for firefighters is to observe the "fire front" to chart the progress of the fire and areas that will likely spread next. Lack of information of the fire front causes many accidents. Using Unmanned Aerial Vehicles (UAVs) to cover wildfire is promising because it can replace humans in hazardous fire tracking and significantly reduce operation costs. In this paper we propose a distributed control framework designed for a team of UAVs that can closely monitor a wildfire in open space, and precisely track its development. The UAV team, designed for flexible deployment, can effectively avoid in-flight collisions and cooperate well with neighbors. They can maintain a certain height level to the ground for safe flight above fire. Experimental results are conducted to demonstrate the capabilities of the UAV team in covering a spreading wildfire.Comment: arXiv admin note: substantial text overlap with arXiv:1704.0263

A theoretical and computational basis for CATNETS

The main content of this report is the identification and definition of market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. These build the theoretical foundation for the work within the following two years of the CATNETS project. --Grid Computing

Decentralized Sensor Fusion With Distributed Particle Filters

This paper presents a scalable Bayesian technique for decentralized state estimation from multiple platforms in dynamic environments. As has long been recognized, centralized architectures impose severe scaling limitations for distributed systems due to the enormous communication overheads. We propose a strictly decentralized approach in which only nearby platforms exchange information. They do so through an interactive communication protocol aimed at maximizing information flow. Our approach is evaluated in the context of a distributed surveillance scenario that arises in a robotic system for playing the game of laser tag. Our results, both from simulation and using physical robots, illustrate an unprecedented scaling capability to large teams of vehicles.Comment: Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003

Evaluation and Challenges of IoT Simulators for Intelligent Transportation System Applications

The Internet-of-Things (IoT) constructs a vast, intricate, and perpetually evolving ecosystem exerting profound societal implications. This labyrinthine nature often culminates in errors that directly impact human lives. A significant domain where this complexity materializes is Intelligent Transportation Systems (ITS). Present tools and methodologies inadequately accommodate the complex task of testing and validation, underscoring the urgency for comprehensive review and enhancement. This study aims to present a broad analysis of existing simulators utilized for ITS simulations. It delves into the role and effectiveness of such simulation tools, highlighting their limitations and proposing research directions. This paper scrutinizes both commercial and research-oriented IoT simulators for ITS, evaluating their features and simulation environment tools. We have detailed various ITS scenarios simulated within these frameworks, intending to gauge their readiness for real-world ITS applications and to elaborate on the challenges involved in ITS infrastructure implementation. The findings suggest that despite numerous simulators aiding the evolution of solutions for IoT challenges in recent years, their utility in actual ITS implementations remain uncertain. Consequently, we explore public cloud platforms offering IoT simulation capabilities, focusing particularly on the capabilities provided by the Amazon Web Services (AWS) IoT simulation for this study. Our research outlines the pressing challenges in this field, while proposing potential solutions and flagging opportunities for further research. This study paves the way towards improving the reliability and accuracy of IoT simulators in the context of ITS, which has immense potential to enhance the quality of human life

Theoretical and Computational Basis for Economical Ressource Allocation in Application Layer Networks - Annual Report Year 1

This paper identifies and defines suitable market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. --Grid Computing

The FuturIcT Knowledge Accelerator: Unleashing the Power of Information for a Sustainable Future

With our knowledge of the universe, we have sent men to the moon. We know microscopic details of objects around us and within us. And yet we know relatively little about how our society works and how it reacts to changes brought upon it. Humankind is now facing serious crises for which we must develop new ways to tackle the global challenges of humanity in the 21st century. With connectivity between people rapidly increasing, we are now able to exploit information and communication technologies to achieve major breakthroughs that go beyond the step-wise improvements in other areas. The need of a socio-economic knowledge collider was first pointed out in the OECD Global Science Forum on Applications of Complexity Science for Public Policy in Erice from October 5 to 7, 2008. Since then, many scientists have called for a large-scale ICT-based research initiative on techno-socialeconomic- environmental issues, sometimes phrased as a Manhattan-, Apollo-, or CERN-like project to study the way our living planet works in a social dimension. Due to the connotations, we use the term knowledge accelerator, here.Comment: For related information see http://www.futurict.eu (The spelling error in Sec. 2.5 was removed: "exclusion" was replaced by "inclusion"

Unconventional Arterial Intersection Designs under Connected and Automated Vehicle Environment: A Survey

Signalized intersections are major sources of traffic delay and collision within the modern transportation system. Conventional signal optimization has revealed its limitation in improving the mobility and safety of an intersection. Unconventional arterial intersection designs (UAIDs) are able to improve the performance of an intersection by reducing phases of a signal cycle. Furthermore, they can fundamentally alter the number and the nature of the conflicting points. However, the driver's confusion, as a result of the unconventional geometric designs, remains one of the major barriers for the widespread adoption of UAIDs. Connected and Automated Vehicle (CAV) technology has the potential to overcome this barrier by eliminating the driver's confusion of a UAID. Therefore, UAIDs can play a significant role in transportation networks in the near future. In this paper, we surveyed UAID studies and implementations. In addition, we present an overview of intersection control schemes with the emergence of CAV and highlight the opportunity rises for UAID with the CAV technology. It is believed that the benefits gained from deploying UAIDs in conjunction with CAV are significant during the initial rollout of CAV under low market penetration

Data-Driven Distributed Modeling, Operation, and Control of Electric Power Distribution Systems

The power distribution system is disorderly in design and implementation, chaotic in operation, large in scale, and complex in every way possible. Therefore, modeling, operating, and controlling the distribution system is incredibly challenging. It is required to find solutions to the multitude of challenges facing the distribution grid to transition towards a just and sustainable energy future for our society. The key to addressing distribution system challenges lies in unlocking the full potential of the distribution grid. The work in this dissertation is focused on finding methods to operate the distribution system in a reliable, cost-effective, and just manner. In this PhD dissertation, a new data-driven distributed ($D^3M$) framework using cellular computational networks has been developed to model power distribution systems. Its performance is validated on an IEEE test case. The results indicate a significant enhancement in accuracy and performance compared to the state-of-the-art centralized modeling approach. This dissertation also presents a new distributed and data-driven optimization method for volt-var control in power distribution systems. The framework is validated for voltage control on an IEEE test feeder. The results indicate that the system has improved performance compared to the state-of-the-art approach. The PhD dissertation also presents a design for a real-time power distribution system testbed. A new data-in-the-loop (DIL) simulation method has been developed and integrated into the testbed. The DIL method has been used to enhance the quality of the real-time simulations. The assets combined with the testbed include data, control, and hardware-in-the-loop infrastructure. The testbed is used to validate the performance of a distribution system with significant penetration of distributed energy resources