Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

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

Virtual Sensor Middleware: Managing IoT Data for the Fog-Cloud Platform

This paper introduces the Virtual Sensor Middleware (VSM), which facilitates distributed sensor data processing on multiple fog nodes. VSM uses a Virtual Sensor as the core component of the middleware. The virtual sensor concept is redesigned to support functionality beyond sensor/device virtualization, such as deploying a set of virtual sensors to represent an IoT application and distributed sensor data processing across multiple fog nodes. Furthermore, the virtual sensor deals with the heterogeneous nature of IoT devices and the various communication protocols using different adapters to communicate with the IoT devices and the underlying protocol. VSM uses the publish-subscribe design pattern to allow virtual sensors to receive data from other virtual sensors for seamless sensor data consumption without tight integration among virtual sensors, which reduces application development efforts. Furthermore, VSM enhances the design of virtual sensors with additional components that support sharing of data in dynamic environments where data receivers may change over time, data aggregation is required, and dealing with missing data is essential for the applications

A survey of communication protocols for internet of things and related challenges of fog and cloud computing integration

The fast increment in the number of IoT (Internet of Things) devices is accelerating the research on new solutions to make cloud services scalable. In this context, the novel concept of fog computing as well as the combined fog-to-cloud computing paradigm is becoming essential to decentralize the cloud, while bringing the services closer to the end-system. This article surveys e application layer communication protocols to fulfill the IoT communication requirements, and their potential for implementation in fog- and cloud-based IoT systems. To this end, the article first briefly presents potential protocol candidates, including request-reply and publish-subscribe protocols. After that, the article surveys these protocols based on their main characteristics, as well as the main performance issues, including latency, energy consumption, and network throughput. These findings are thereafter used to place the protocols in each segment of the system (IoT, fog, cloud), and thus opens up the discussion on their choice, interoperability, and wider system integration. The survey is expected to be useful to system architects and protocol designers when choosing the communication protocols in an integrated IoT-to-fog-to-cloud system architecture.Peer ReviewedPostprint (author's final draft

Enabling IoT in Manufacturing: from device to the cloud

Industrial automation platforms are experiencing a paradigm shift. With the new technol-ogies and strategies that are being applied to enable a synchronization of the digital and real world, including real-time access to sensorial information and advanced networking capabilities to actively cooperate and form a nervous system within the enterprise, the amount of data that can be collected from real world and processed at digital level is growing at an exponential rate. Indeed, in modern industry, a huge amount of data is coming through sensorial networks em-bedded in the production line, allowing to manage the production in real-time. This dissertation proposes a data collection framework for continuously collecting data from the device to the cloud, enabling resources at manufacturing industries shop floors to be handled seamlessly. The framework envisions to provide a robust solution that besides collecting, transforming and man-aging data through an IoT model, facilitates the detection of patterns using collected historical sensor data. Industrial usage of this framework, accomplished in the frame of the EU C2NET project, supports and automates collaborative business opportunities and real-time monitoring of the production lines

IoT DEVICE MANAGEMENT AND CONFIGURATION

As the number of IoT devices grows, the management and configuration of IoT devices becomes crucial in resource constraint networks. It is hard to manage and configure a large amount of heterogeneous resource constraint IoT devices because people need to know how they connect to each other, what internet-enabled services are available to provide, and how people interact with things through the internet. The thing-centric approach focuses on user experience when engaging things, but the cloud- centric approach switch the focus to IoT services that can process data streams collected from things and applications that help get people joined in the IoT world. To manage IoT populations effectively in a centralized manner, not only does it mean that moving computational power closer to the edge is a way to reduce bandwidth and latency, but it also implies that it is necessary to build an architecture which can scale and manage tons of connected devices by a uniform interface. In particular, RESTful Web services can provide a uniform interface that operates resources by HTTP methods. For example, users can read and write data by a uniform interface, and a flowerpot can write data and be triggered to water plants by a uniform interface. Thus, in the scope of IoT, embedded middleware can implement uniform interface by REST model. Virtualizing physical things has emerged as a design pattern to build IoT systems. Resource less constraint devices are capable of being virtualized with enough CPU power, memory, networking, but they are more expensive and power consuming. However, resource highly constraint devices take advantage of low energy consumption and cheaper price, but they cannot be virtualized because they do not have ability to even run a single multi-threaded program. Therefore, it is very important to select the right platforms for the right roles. In our case, we use Raspberry Pi 3 as a middleware and Nordic nRF52832 as a BLE endpoint. In this thesis, a REST-based IoT management system based on Service-Oriented Architecture is built, and the performance of the system has been tested, including the response time of HTTP GET and POST requests of the centralized server in a Fog domain and a script engine onto a BLE-enabled endpoint

IoT for Efficient Data Collection from Real World Resources

The Internet of Things is providing new ways of experiencing and reacting to the physical world through the ability of advanced electronic devices that collect data. At the same time, as new application scenarios are envisioned, with the assistance of information generated by sensors, new problems and obstacles will arise. This requires new development to meet business and technical requirements, such as interoperability between heterogeneous devices and confidence (such as validity, security and trust) over smart devices. With the increase of these complex requirements it becomes crucial to develop an infrastructure aimed at tackling such requirements mentioned. IoT middleware – a software layer that bridges the gap between devices and information systems. Thus, this work aims to study the mechanisms and methodology for data collection, devices interoperability and data filtering, closer to the data sources, in order to optimize the collection and pre-analysis of data that can then be used by various applications such as the ones in manufacturing industry