Internet of things

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth

Interoperating networked embedded systems to compose the web of things

Improvements in science and technology have enhanced our quality of life with better healthcare services, comfortable living and transportation among others. Human beings are now able to travel faster, communicate across the globe in fraction of seconds, understand nature better than ever before and generate and consume huge amount of information. The Internet played a central role in this development by providing a vast network of networks. Leveraging this global infrastructure, the World Wide Web is providing a shared information space for such unprecedented amount of knowledge that is mostly contributed and used by human beings. It has played such a critical role in the adoption of the Internet, it is common to find people referring specific web sites as Internet. This adoption coupled with advances in manufacturing of computing elements that led to the reduction in size and price has introduced a new wave of technology, called the Internet of Things. A rudimentary description of the Internet of Things (IoT) is an Internet that connects, not only traditional computing devices (with higher capacity and provide user interface) but also everyday physical objects or ’Things’ around us. These objects are augmented by small networked embedded computing elements that interact with the host via sensors and actuators. It is estimated that there will be Billions of such devices and Trillions of dollars of market value distributed in multiple aspects of our lives; such as healthcare, smart home, smart industries and smart cities. However, there are many challenges that are hindering the wide adoption of IoT. One of these challenges is heterogeneity of network interfaces, platforms, data formats and many standards that led to vertical islands of systems that are not interoperable at various levels. To address the lack of interoperability, this thesis presents the author’s contributions in three categories. The first part is a lightweight middleware called LISA that address variations in protocols and platforms. It is designed to work within the constrained resources of the networked embedded devices. The overhead of the middleware is evaluated and compared with other related frameworks. The second set of contributions focus on higher level of system integration and related challenges. It includes a domain specific IoT language (DoS-IL) and a server implementation to support the proposed code on demand approach. The scripting language enables re-configuration of the behaviour of systems during integration or functional changes. The related server provides abstraction of the physical object and its embedded device to provide mobility services in addition to hosting the scripts. The last set of contributions are focused on either generalized architectural style design or a specific healthcare use case. In summary, the overall thesis presents a highlevel architectural style that provides ease of understanding and communication of IoT systems, serves as a means for system level integration and provides the desired quality attributes for IoT systems. The other contributions fit in the architectural style to facilitate the adoption of the style or showcase specific instances of the architecture’s use. The performance of the middleware, the scripting language and the server including their resource utilization and overhead have been analyzed and presented. In general, the combination of the contributions enable inter-operation of networked embedded systems that serve as building blocks for the Web of Things - a global system of IoT systems

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

Fog Computing: A Taxonomy, Survey and Future Directions

In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named "Fog computing" has been introduced. Generally, Fog computing resides closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities. In this chapter, we comprehensively analyse the challenges in Fogs acting as an intermediate layer between IoT devices/ sensors and Cloud datacentres and review the current developments in this field. We present a taxonomy of Fog computing according to the identified challenges and its key features.We also map the existing works to the taxonomy in order to identify current research gaps in the area of Fog computing. Moreover, based on the observations, we propose future directions for research

Orchestrating Service Migration for Low Power MEC-Enabled IoT Devices

Multi-Access Edge Computing (MEC) is a key enabling technology for Fifth Generation (5G) mobile networks. MEC facilitates distributed cloud computing capabilities and information technology service environment for applications and services at the edges of mobile networks. This architectural modification serves to reduce congestion, latency, and improve the performance of such edge colocated applications and devices. In this paper, we demonstrate how reactive service migration can be orchestrated for low-power MEC-enabled Internet of Things (IoT) devices. Here, we use open-source Kubernetes as container orchestration system. Our demo is based on traditional client-server system from user equipment (UE) over Long Term Evolution (LTE) to the MEC server. As the use case scenario, we post-process live video received over web real-time communication (WebRTC). Next, we integrate orchestration by Kubernetes with S1 handovers, demonstrating MEC-based software defined network (SDN). Now, edge applications may reactively follow the UE within the radio access network (RAN), expediting low-latency. The collected data is used to analyze the benefits of the low-power MEC-enabled IoT device scheme, in which end-to-end (E2E) latency and power requirements of the UE are improved. We further discuss the challenges of implementing such schemes and future research directions therein

Next Generation Cloud Computing: New Trends and Research Directions

The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.Comment: Accepted to Future Generation Computer Systems, 07 September 201