Internet Of Things Software Research Articles

Elastic Smart Contracts in Blockchains

In this paper, we deal with questions related to blockchains in complex Internet of Things (IoT)-based ecosystems. Such ecosystems are typically composed of IoT devices, edge devices, cloud computing software services, as well as people, who are decision makers in scenarios such as smart cities. Many decisions related to analytics can be based on data coming from IoT sensors, software services, and people. However, they are typically based on different levels of abstraction and granularity. This poses a number of challenges when multiple blockchains are used together with smart contracts. This work proposes to apply our concept of elasticity to smart contracts and thereby enabling analytics in and between multiple blockchains in the context of IoT. We propose a reference architecture for Elastic Smart Contracts and evaluate the approach in a smart city scenario, discussing the benefits in terms of performance and self-adaptability of our solution.

A Comprehensive Survey on Interoperability for IIoT: Taxonomy, Standards, and Future Directions

In the era of Industry 4.0, the Internet-of-Things (IoT) performs the driving position analogous to the initial industrial metamorphosis. IoT affords the potential to couple machine-to-machine intercommunication and real-time information-gathering within the industry domain. Hence, the enactment of IoT in the industry magnifies effective optimization, authority, and data-driven judgment. However, this field undergoes several interoperable issues, including large numbers of heterogeneous IoT gadgets, tools, software, sensing, and processing components, joining through the Internet, despite the deficiency of communication protocols and standards. Recently, various interoperable protocols, platforms, standards, and technologies are enhanced and altered according to the specifications of the applicability in industrial applications. However, there are no recent survey papers that primarily examine various interoperability issues that Industrial IoT (IIoT) faces. In this review, we investigate the conventional and recent developments of relevant state-of-the-art IIoT technologies, frameworks, and solutions for facilitating interoperability between different IIoT components. We also discuss several interoperable IIoT standards, protocols, and models for digitizing the industrial revolution. Finally, we conclude this survey with an inherent discussion of open challenges and directions for future research.

Configurable IoT Open-Source Hardware and Software I-V Curve Tracer for Photovoltaic Generators.

Photovoltaic (PV) energy is a renewable energy resource which is being widely integrated in intelligent power grids, smart grids, and microgrids. To characterize and monitor the behavior of PV modules, current-voltage (I-V) curves are essential. In this regard, Internet of Things (IoT) technologies provide versatile and powerful tools, constituting a modern trend in the design of sensing and data acquisition systems for I-V curve tracing. This paper presents a novel I-V curve tracer based on IoT open-source hardware and software. Namely, a Raspberry Pi microcomputer composes the hardware level, whilst the applied software comprises mariaDB, Python, and Grafana. All the tasks required for curve tracing are automated: load sweep, data acquisition, data storage, communications, and real-time visualization. Modern and legacy communication protocols are handled for seamless data exchange with a programmable logic controller and a programmable load. The development of the system is expounded, and experimental results are reported to prove the suitability and validity of the proposal. In particular, I-V curve tracing of a monocrystalline PV generator under real operating conditions is successfully conducted.

Intelligent Systems for the Internet of Things: Essence, Perspectives and Problems

This article outlines the Internet of Things (IoT). The Internet of Things describes a network of physical objects, i.e., the “thing” including sensors, software, and other technologies for connection and data sharing with other devices and systems over the Internet. In other words, IoT is a relatively new technology enabling many “smart” devices to get connected, to analyze, process, and transfer data to each other and connect to a network. The article clarifies the essence of intelligent systems for the Internet of Things, and analyzes the most popular software for the IoT platform. It studies high-level systems for IoT and analyzes available literature in this field. It highlights most advanced IoT software of 2021. The article also identifies the prospects and challenges of intelligent systems for the Internet of Things. The creation of new intelligent systems for IoT and the development of technology will greatly contribute to the development of economy.

Requirements Engineering Technology for the IoT Software Systems

Contemporary software systems (CSS) – such as the internet of things (IoT) based software systems – incorporate new concerns and characteristics inherent to the network, software, hardware, context awareness, interoperability, and others, compared to conventional software systems. In this sense, requirements engineering (RE) plays a fundamental role in ensuring these software systems' correct development looking for the business and end-user needs. Several software technologies supporting RE are available in the literature, but many do not cover all CSS specificities, notably those based on IoT. This research article presents RETIoT (Requirements Engineering Technology for the Internet of Things based software systems), aiming to provide methodological, technical, and tooling support to produce IoT software system requirements document. It is composed of an IoT scenario description technique, a checklist to verify IoT scenarios, construction processes, and templates for IoT software systems. A feasibility study was carried out in IoT system projects to observe its templates and identify improvement opportunities. The results indicate the feasibility of RETIoT templates' when used to capture IoT characteristics. However, further experimental studies represent research opportunities, strengthen confidence in its elements (construction process, techniques, and templates), and capture end-user perception.

Internet of Things Software and Hardware Architectures and Their Impacts on Forensic Investigations: Current Approaches and Challenges

Internet of Things Software and Hardware Architectures and Their Impacts on Forensic Investigations: Current Approaches and Challenges

On the Design of IoT Security: Analysis of Software Vulnerabilities for Smart Grids

The 5G communication network will underpin a vast number of new and emerging services, paving the way for unprecedented performance and capabilities in mobile networks. In this setting, the Internet of Things (IoT) will proliferate, and IoT devices will be included in many 5G application contexts, including the Smart Grid. Even though 5G technology has been designed by taking security into account, design provisions may be undermined by software-rooted vulnerabilities in IoT devices that allow threat actors to compromise the devices, demote confidentiality, integrity and availability, and even pose risks for the operation of the power grid critical infrastructures. In this paper, we assess the current state of the vulnerabilities in IoT software utilized in smart grid applications from a source code point of view. To that end, we identified and analyzed open-source software that is used in the power grid and the IoT domain that varies in characteristics and functionality, ranging from operating systems to communication protocols, allowing us to obtain a more complete view of the vulnerability landscape. The results of this study can be used in the domain of software development, to enhance the security of produced software, as well as in the domain of automated software testing, targeting improvements to vulnerability detection mechanisms, especially with a focus on the reduction of false positives.

Dynamic neuromorphic architecture selection scheme for intelligent Internet of Things services

SummaryWith the development of Internet of Things (IoT)‐related technologies and artificial intelligence (AI) technologies, various IoT services are becoming more intelligent, and their use range is increasing and diversifying. IoT hardware and IoT software must support AI‐related functions to provide an intelligent IoT service. In general, IoT devices powered by batteries have limited computing performance when compared to general computing environments. Therefore, it is essential to provide AI‐related functions at low power in IoT devices to implement and offer various intelligent services. Neuromorphic computing devices or neuromorphic computing architectures can operate with low power energy consumption. If applied to IoT devices, AI‐related functions can be implemented in a resource‐constrained IoT device environment. The proposed neuromorphic architecture abstraction (NAA) model dynamically selects the proper neuromorphic architecture by comparing the parameter size of a given SNN model. It also considers the specifications and error probability of the available neuromorphic architecture. We also implement the proposed model in a real IoT computing environment and show that the proposed NAA model and dynamic selection scheme can reduce the execution time for training and inferencing. It reduces the training and inferencing time of a given model compared with the method of randomly specifying the neuromorphic architecture.

Simulation of Scalability in Cloud-Based IoT Reactive Systems Leveraged on a WSAN Simulator and Cloud Computing Technologies

Implementing a wireless sensor and actuator network (WSAN) in Internet of Things (IoT) applications is a complex task. The need to establish the number of nodes, sensors, and actuators, and their location and characteristics, requires a tool that allows the preliminary determination of this information. Additionally, in IoT scenarios where a large number of sensors and actuators are present, such as in a smart city, it is necessary to analyze the scalability of these systems. Modeling and simulation can help to conduct an early study and reduce development and deployment times in environments such as a smart city. The design-time verification of the system through a network simulation tool is useful for the most complex and expensive part of the system formed by a WSAN. However, the use of real components for other parts of the IoT system is feasible by using cloud computing infrastructure. Although there are cloud computing simulators, the cloud layer is poorly developed for the requirements of IoT applications. Technologies around cloud computing can be used for the rapid deployment of some parts of the IoT application and software services using containers. With this framework, it is possible to accelerate the development of the real system, facilitate the rapid deployment of a prototype, and provide more realistic simulations. This article proposes an approach for the modeling and simulation of IoT systems and services in a smart city leveraged in a WSAN simulator and technologies of cloud computing. Our approach was verified through experiments with two use cases. (1) A model of sensor and actuator networks as an integral part of an IoT application to monitor and control parks in a city. Through this use case, we analyze the scalability of a system whose sensors constantly emit data. (2) A model for cloud-based IoT reactive parking lot systems for a city. Through our approach, we have created an IoT parking system simulation model. The model contains an M/M/c/N queuing system to simulate service requests from users. In this use case, the model replication through hierarchical modeling and scalability of a distributed parking reservation service were evaluated. This last use case showed how the simulation model could provide information to size the system through probability distribution variables related to the queuing system. The experimental results show that the use of simulation techniques for this type of application makes it possible to analyze scalability in a more realistic way.

Modeling-framework for model-based software engineering of complex Internet of things systems.

Internet of things (IoT) systems are composed of variety of units from different domains. While developing a complete IoT system, different professionals from different domains may have to work in collaboration. In this paper we provide a framework which allows using discrete and continuous time modeling and simulation approaches in combination for IoT systems. The proposed framework demonstrates on how to model Ad-hoc and general IoT systems for software engineering purpose. We demonstrate that model-based software engineering on one hand can provide a common platform to overcome communication gaps among collaborating stakeholders whereas, on the other hand can model and integrate heterogeneous components of IoT systems. While modeling heterogeneous IoT systems, one of the major challenges is to apply continuous and discrete time modeling on intrinsically varying components of the system. Another difficulty may be how to compose these heterogeneous components into one whole system. The proposed framework provides a road-map to model discrete, continuous, Ad-hoc, general systems along with composition mechanism of heterogeneous subsystems. The framework uses a combination of Agent-based modeling, Aspect-oriented modeling, contract-based modeling and services-oriented modeling concepts. We used this framework to model a scenario example of a service-oriented IoT system as proof of concept. We analyzed our framework with existing systems and discussed it in details. Our framework provides a mechanism to model different viewpoints. The framework also enhances the completeness and consistency of the IoT software models.

Improving teachers’ competence on the use of internet of things for teachers in the city of Makassar

Internet of Things (IoT) is part of digital literacy that its function is undeniable when people are today obsessed more to social media and gadgets. IoT is greatly potential to support education field, especially in facilitating teachers. However, with all functions it has, IoT is not well mastered by many teachers in the city of Makassar. The issue is mainly because teachers are not well literate to IT. Therefore, it is significant to provide teachers with some trainings or workshops. Thus, this community service is projected to improve teachers’ competence in the use of IoT so that they will be life-long learners in the future. The ability to be life-long learner is one of the indicators to Sustainable Development Goals (SDGs). This community service has resulted in several outputs, they are: 1) teachers are equipped with the ability to use IoT and e-learning software, 2) the scoring results reveal that this community service has the average score of 4,67 (good criteria).

Evaluating the performance of the OSCORE security protocol in constrained IoT environments

The Constrained Application Protocol (CoAP) is a standard communication protocol for resource-constrained devices in the Internet of Things (IoT). Many IoT deployments require proxies to support asynchronous communication between edge devices and the back-end. This allows (non-trusted) proxies to access sensitive parts of CoAP messages. Object Security for Constrained RESTful Environments (OSCORE) is a recent standard protocol that provides end-to-end security for CoAP messages at the application layer. Unlike the commonly used standard Datagram Transport Layer Security (DTLS), OSCORE efficiently provides selective integrity protection and encryption on different parts of CoAP messages. Thus, OSCORE enables end-to-end security through intermediary (non-trusted) proxies, while still allowing them to perform their expected services, with considerable security and privacy improvements.To assess whether these security features consume too much of the limited resources available on a constrained device, we have implemented OSCORE (the implementation is available as open-source), and evaluated its efficiency. This paper provides a comprehensive, comparative and experimental performance evaluation of OSCORE on real resource-constrained IoT devices, using the operating system Contiki-NG as IoT software platform. In particular, we experimentally evaluated the efficiency of our OSCORE implementation on resource-constrained devices running Contiki-NG, in comparison with the DTLS implementation TinyDTLS maintained by the Eclipse Foundation. The evaluation results show that our OSCORE implementation displays moderately better performance than TinyDTLS, in terms of per-message network overhead, memory usage, message round-trip time and energy efficiency, thus providing the security improvements of OSCORE with no additional performance penalty.

Towards a Safer Internet of Things-A Survey of IoT Vulnerability Data Sources.

The security of the Internet of Things (IoT) is an important yet often overlooked subject. Specifically, the publicly available information sources about vulnerabilities affecting the connected devices are unsatisfactory. Our research shows that, while the information is available on the Internet, there is no single service offering data focused on the IoT in existence. The national vulnerability databases contain some IoT related entries, but they lack mechanisms to distinguish them from the remaining vulnerabilities. Moreover, information about many vulnerabilities affecting the IoT world never reaches these databases but can still be found scattered over the Internet. This review summarizes our effort at identifying and evaluating publicly available sources of information about vulnerabilities, focusing on their usefulness in the scope of IoT. The results of our search show that there is not yet a single satisfactory source covering vulnerabilities affecting IoT devices and software available.

Landscape of Architecture and Design Patterns for IoT Systems

Due to the widespread proliferation of today’s Internet of Things (IoT), a system designer needs the IoT system and software design patterns to assist in designing scalable and replicable solutions. Patterns are encapsulations of reusable common problems and solutions under specific contexts. Many IoT patterns have been published, such as IoT design patterns and IoT architecture patterns to document the successes (and failures) in IoT systems and software development. However, because these patterns are not well classified, their adoption does not live up to their potential. To understand the reasons, we conducted a systematic literature review. From the 32 identified papers, 143 IoT architecture and design patterns were extracted. We analyzed these patterns according to several characteristics and outlined directions for improvements when publishing and adopting IoT patterns. Of the extracted patterns, 57% are non-IoT patterns, suggesting that IoT systems and software are often designed via conventional architecture and design patterns that are not specific to IoT design. Although most IoT design patterns are applicable to any domain, IoT architecture patterns tend to be domain specific, implying that the unique nature of IoT adoption in specific domains appears at the architecture level. As more domains adopt IoT, the number of domain-specific IoT design patterns should increase. In terms of quality attributes, many IoT patterns address compatibility, security, and maintainability.

Design Guidelines for Machine Learning-based Cybersecurity in Internet of Things

Cybersecurity is one of the building blocks in need of increasing attention in Internet of things (IoT) applications. IoT has become a popular target for attackers seeking sensitive and personal user data, computing infrastructure for massive attacks, or aimed at compromising critical applications. Worryingly, the industrial race toward the forefront of IoT software and device development has led to increased market penetration of vulnerable IoT devices and applications. Nevertheless, traditional cybersecurity solutions designed for personal computers often rely on heavy computation and high communication overhead, and therefore are prohibitive for IoT, given the explosive number of IoT devices, their resource-con-strained nature, and their heterogeneity. Hence, innovative solutions must be designed for securing IoT applications, while considering the peculiar characteristics of IoT devices and networks. In this article, we discuss the motivations and challenges of using machine learning (ML) models for the design of cybersecurity solutions for IoT. More specifically, we tackle the challenge of designing ML-based solutions and provide guidelines for ML-based physical layer solutions aimed at securing IoT. We propose a device-oriented and network-oriented classification and investigate recent works that designed ML-based solutions, considering IoT physical layer features, to secure IoT applications. The proposed classification helps engineers and practitioners starting in this area to better identify and understand the challenges, requirements, and up-to-date common design principles for securing IoT devices and networks considering physical layer features. Finally, we shed light on some future research directions that need further investigation.

Software architecture of the internet of things (IoT) for smart city, healthcare and agriculture: analysis and improvement directions

Internet of things (IoT) enables organizations to automate the process and improves service delivery through Internet technology and transferring the data at the cloud level. IoT does not allow the use of a universal software architecture for different fields in which it is used, but needs to be adjusted according to the requirements of users. This paper presents an analysis of currently available types of software architectures of the IoT systems in the field of smart cities, healthcare, and agriculture. It provides a proposal for solutions and improvements of different software architecture types, interactions between identified software architecture elements that will provide better performance and simplicity. The novelty of the study is the analysis of different types of IoT software architecture such as: layered, service-oriented and cloud-based software architecture application in these areas of IoT. Based on the analysis, the study proposed the type of software architecture of the IoT system for the relevant area of application (smart city, healthcare, and agriculture). Specific points of research are: analysis of different types of software architecture applied in IoT systems, identification of functionalities available in IoT systems through different types of software architecture, the proposal for enhancement of the above functionalities, and proposal of software architecture that is most relevant to the IoT system of a particular area.

A wearable sensor vest for social humanoid robots with GPGPU, IoT, and modular software architecture

Currently, most social robots interact with their surroundings and humans through sensors that are integral parts of the robots, which limits the usability of the sensors, human–robot interaction, and interchangeability. A wearable sensor garment that fits many robots is needed in many applications. This article presents an affordable wearable sensor vest, and an open-source software architecture with the Internet of Things (IoT) for social humanoid robots. The vest consists of touch, temperature, gesture, distance, vision sensors, and a wireless communication module. The IoT feature allows the robot to interact with humans locally and over the Internet. The designed architecture works for any social robot that has a general-purpose graphics processing unit (GPGPU), I2C/SPI buses, Internet connection, and the Robotics Operating System (ROS). The modular design of this architecture enables developers to easily add/remove/update complex behaviors. The proposed software architecture provides IoT technology, GPGPU nodes, I2C and SPI bus mangers, audio-visual interaction nodes (speech to text, text to speech, and image understanding), and isolation between behavior nodes and other nodes. The proposed IoT solution consists of related nodes in the robot, a RESTful web service, and user interfaces. We used the HTTP protocol as a means of two-way communication with the social robot over the Internet. Developers can easily edit or add nodes in C, C++, and Python programming languages. Our architecture can be used for designing more sophisticated behaviors for social humanoid robots.

Interoperability Improvement in Internet of Things Using Fog Assisted Semantic Frame Work

Cloud computing is equipped with the numerous of advantageous features to support software and utilities on the Internet of Things (IoT). Cloud-based technology is widely used when offering support for heterogeneous applications integrating specific IoT that follows various semantics. Attaching additional information to raw data sensed with the help of ontology is accomplished in semantic model. The longer distance between the cloud and IoT applications, however, is a bottleneck for vital IoT software. So the paper puts forth a semantic frame work assisted by the fog to enhance the interoperability in the internet of things. The structure put forth moves some of the cloud's commonly used semantic resources sensor networks edge and also offers an effective off-loading technique between fog – fog and fog – cloud devices to diminish total computation time of the task and the energy consumed by the nodes in the fog. The proposed method further follows an efficient mapping technique to transform the data’s sensed into a RDF-format such that it is compatible for processing. The proposed model is evaluated on the basis of delay in the service provision, the energy consumed , and the total cost of the system and further the results obtained are compared with the relevant cloud based computing models , to reveal the proficiency of the proposed.

Machine Learning Framework to Analyze IoT Malware Using ELF and Opcode Features

Threats to devices that are part of the Internet of Things (IoT) are on the rise. Owing to the overwhelming diversity of IoT hardware and software, as well as its variants, conventional anti-virus techniques based on the Windows paradigm cannot be applied directly to counter threats to the IoT devices. In this article, we propose a framework that can efficiently analyze IoT malware in a wide range of environments. It consists of a universal feature representation obtained by static analysis of the malware and a machine learning scheme that first detects the malware and then classifies it into a known category. The framework was evaluated by applying it to a recently developed dataset consisting of more than 6,000 IoT malware samples collected from the HoneyPot project. The results show that the proposed method can obtain near-optimal accuracy in terms of the detection and classification of malware targeting IoT devices.

A Preliminary Component Model for IoT

The enthusiasm of IT entrepreneurs in producing Internet of Things (IoT) systems is undeniable as currently, the number of connected devices is enormously increasing. Many research has been done to efficiently develop IoT systems. IoT systems are usually engineered from scratch. IoT component models have been introduced but lack of generic development framework or model that supports high reusability and loose coupling in dealing with the heterogeneous devices that can hinder its development. Thus, an IoT component model is proposed. Meta-modelling has been used to define the component model where the specific interaction and composition standard in a component are abstracted. IoT component model is intended to develop a prototype for IoT development. With this IoT prototype, IoT system developers will not need to develop everything from scratch every time, as generic components can be reused even when it is applied in different domains or during system enhancement is required. Smart home IoT system has been selected as a case study to evaluate our prototype tool. In this study, we provide an alternative way to develop IoT software in component-based software engineering method. A prototype has also been developed to assist reusability and reduce coupling between modules.