Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Addressing the Challenges in Federating Edge Resources

This book chapter considers how Edge deployments can be brought to bear in a global context by federating them across multiple geographic regions to create a global Edge-based fabric that decentralizes data center computation. This is currently impractical, not only because of technical challenges, but is also shrouded by social, legal and geopolitical issues. In this chapter, we discuss two key challenges - networking and management in federating Edge deployments. Additionally, we consider resource and modeling challenges that will need to be addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and Paradigms; Editors Buyya, Sriram

Customer-engineer relationship management for converged ICT service companies

Thanks to the advent of converged communications services (often referred to as ‘triple play’), the next generation Service Engineer will need radically different skills, processes and tools from today’s counterpart. Why? in order to meet the challenges of installing and maintaining services based on multi-vendor software and hardware components in an IP-based network environment. The converged services environment is likely to be ‘smart’ and support flexible and dynamic interoperability between appliances and computing devices. These radical changes in the working environment will inevitably force managers to rethink the role of Service Engineers in relation to customer relationship management. This paper aims to identify requirements for an information system to support converged communications service engineers with regard to customer-engineer relationship management. Furthermore, an architecture for such a system is proposed and how it meets these requirements is discussed

White Paper for Research Beyond 5G

The documents considers both research in the scope of evolutions of the 5G systems (for the period around 2025) and some alternative/longer term views (with later outcomes, or leading to substantial different design choices). This document reflects on four main system areas: fundamental theory and technology, radio and spectrum management; system design; and alternative concepts. The result of this exercise can be broken in two different strands: one focused in the evolution of technologies that are already ongoing development for 5G systems, but that will remain research areas in the future (with “more challenging” requirements and specifications); the other, highlighting technologies that are not really considered for deployment today, or that will be essential for addressing problems that are currently non-existing, but will become apparent when 5G systems begin their widespread deployment

A people-oriented paradigm for smart cities

Most works in the literature agree on considering the Internet of Things (IoT) as the base technology to collect information related to smart cities. This information is usually offered as open data for its analysis, and to elaborate statistics or provide services which improve the management of the city, making it more efficient and more comfortable to live in. However, it is not possible to actually improve the quality of life of smart cities’ inhabitants if there is no direct information about them and their experiences. To address this problem, we propose using a social and mobile computation model, called the Internet of People (IoP) which empowers smartphones to recollect information about their users, analyze it to obtain knowledge about their habits, and provide this knowledge as a service creating a collaborative information network. Combining IoT and IoP, we allow the smart city to dynamically adapt its services to the needs of its citizens, promoting their welfare as the main objective of the city.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft