A holistic architecture for the Internet of Things, sensing services and big data

Wireless Sensor Networks (WSNs) increasingly enable the interaction of the physical world with services, which may be located across the Internet from the sensing network. Cloud services and big data approaches may be used to store and analyse this data to improve scalability and availability, which will be required for the billions of devices envisaged in the Internet of Things (IoT). This potential of WSNs is limited by the relatively low number deployed and the difficulties imposed by their heterogeneous nature and limited (or proprietary) development environments and interfaces. This paper proposes a set of requirements for achieving a pervasive, integrated information system of WSNs and associated services. It also presents an architecture which provides a set of abstractions for the different types of sensors and services, enabling them to take advantage of Big Data and cloud technologies and which is termed holistic as it caters for the data flow from sensors through to services. The architecture has been designed for implementation on a resource constrained node and to be extensible to server environments, shown in this paper where we present a 'C' implementation of the core architecture, including services on Linux and Contiki (using the Constrained Application Protocol (CoAP)) and a Linux service to integrate with the Hadoop HBase data store

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

A holistic architecture using peer to peer (P2P) protocols for the internet of things and wireless sensor networks

Wireless Sensor Networks (WSNs) interact with the physical world using sensing and/or actuation. The wireless capability of WSN nodes allows them to be deployed close to the sensed phenomenon. Cheaper processing power and the use of micro IP stacks allow nodes to form an “Internet of Things” (IoT) integrating the physical world with the Internet in a distributed system of devices and applications. Applications using the sensor data may be located across the Internet from the sensor network, allowing Cloud services and Big Data approaches to store and analyse this data in a scalable manner, supported by new approaches in the area of fog and edge computing. Furthermore, the use of protocols such as the Constrained Application Protocol (CoAP) and data models such as IPSO Smart Objects have supported the adoption of IoT in a range of scenarios. IoT has the potential to become a realisation of Mark Weiser’s vision of ubiquitous computing where tiny networked computers become woven into everyday life. This presents the challenge of being able to scale the technology down to resource-constrained devices and to scale it up to billions of devices. This will require seamless interoperability and abstractions that can support applications on Cloud services and also on node devices with constrained computing and memory capabilities, limited development environments and requirements on energy consumption. This thesis proposes a holistic architecture using concepts from tuple-spaces and overlay Peer-to-Peer (P2P) networks. This architecture is termed as holistic, because it considers the flow of the data from sensors through to services. The key contributions of this work are: development of a set of architectural abstractions to provide application layer interoperability, a novel cache algorithm supporting leases, a tuple-space based data store for local and remote data and a Peer to Peer (P2P) protocol with an innovative use of a DHT in building an overlay network. All these elements are designed for implementation on a resource constrained node and to be extensible to server environments, which is shown in a prototype implementation. This provides the basis for a new P2P holistic approach that will allow Wireless Sensor Networks and IoT to operate in a self-organising ad hoc manner in order to deliver the promise of IoT

Enabling stream processing for people-centric IoT based on the fog computing paradigm

The world of machine-to-machine (M2M) communication is gradually moving from vertical single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organizations and people - A world of Internet of Things (IoT). The dominant approach for delivering IoT applications relies on the development of cloud-based IoT platforms that collect all the data generated by the sensing elements and centrally process the information to create real business value. In this paper, we present a system that follows the Fog Computing paradigm where the sensor resources, as well as the intermediate layers between embedded devices and cloud computing datacenters, participate by providing computational, storage, and control. We discuss the design aspects of our system and present a pilot deployment for the evaluating the performance in a real-world environment. Our findings indicate that Fog Computing can address the ever-increasing amount of data that is inherent in an IoT world by effective communication among all elements of the architecture

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea