IoT Operating System Research Articles

An Overview of Computer Operating Systems and Emerging Trends

This article presents an overview of computer operating systems (OS) and emerging trends. OS is simply defined as an interface between computer hardware and the user. The objective of the study is to investigate the emerging trends of OS and to find out the direction of OS for modern computing systems. To achieve this goal the paper looks at the concepts of OS, its underlying architectures and evolution. The papers also outline the components of the OS provide knowledge on security issues with OS architectures and provide best practices to secure OS. The paper found out that the current trends in OS include IoT OS, Cloud OS, AI-powered OS, Blockchain OS, Hybrid OS and Container OS. The paper compares the strengths and weaknesses of the major OS. The Paper proposes a double-layer security approach where the OS is hardened with security policies and embedding security protocols in the Hardware architecture of the OS. It was discovered that every technology comes with its unique architecture and OS. This makes it worrisome for engineers to crack their brains to develop such a system. The paper further proposes the development of a universal OS for all architectures leaving room for further expansion while mitigating power consumption issues by incorporating green computing technology in the design architecture.

Urban Farming Prototype Design and Development with IoT System using STEMSEL and Runlinc IDE

Urban farming technology is getting more acceptable with the increase in population. Running urban farming with IoT becomes more important as urban farming has many constraints. This project aimed to design and develop an automated urban farming system operated with an IoT system using Science Technology Engineering Maths Social Enterprise Learning Artificial Intelligence (STEMSEL AI), and Runlinc Integrated Development Environment (IDE) to ease urban farming. The prototype consists of three major components: the structural part, the water piping system, and the IoT operating system. Idea generation was applied to develop various conceptual designs in the structural component. Concept evaluation was performed to choose the final design. The IoT operation system was designed and developed using the STEMSEL module and Runlinc IDE. A few challenges were identified throughout the design process. Overall, STEMSEL is much simpler and easier to set up than other controllers.

Design of an IoT platform for data analytics based fault detection and classification in solar PV power plants using CFKC and ODENN

New policies are commenced all over the globe to diminish the use of fossil fuels, which gives rise to the augmented utilization of solar energy (SE). The photovoltaic (PV) system’s performance is extremely environmental variables reliant. Long-range transmission of SE is incompetent as well as complex to carry in the PV system. It can be affected by disparate sorts of faults, which cause severe energy loss all through the system operation. Thus, it is vital to incessantly monitor the solar PV (SPV) system to detect as well classify the faults by preventing energy losses. The IoT applications in SE production engage sensor devices that are fixed to the generation, and transmission, together with distribution equipment. These devices assist in monitoring the operation of the SPV power plant (SPVPP) system remotely in real-time. Presenting a new algorithm that can perform fault detection and classification in a PV system to a higher level of accuracy is the major contribution of this work. Thus, this work designs as well as develops an IoT platform for carrying out analytical tasks that can analyze data generated as of IoT operating systems to detect as well as classify faults in the SPVPP. Initially, the data collected from the dataset is pre-processed in which data duplication is performed using Hadoop distributed file system (HDFS) and then the fault is detected from the pre-processed data using the cosine function based k-means clustering (CFKC) technique in the SPV system. Finally, the obtained fault data is fed into the optimized deep learning centered ENN (ODENN) method which classifies the faults. The proposed techniques detect as well as classify the faults effectively that are experimentally proved by means of comparing them with the prevailing techniques, namely ENN, ANN and SVM, along with KNN in terms of some quality measures. The obtained results for ODENN showed an accuracy of 98.99%, specificity of 97.6%, and a sensitivity of 97.02%.

ML Based Authentication Scheme for Data Storage in Cloud Based IoT

Today, organizations are using IoT devices to accurately collect real data and make better business decisions to increase customer satisfaction. The data collected should be stored and stored in a well-designed storage system, which encourages companies to review their data storage infrastructure. The company needs to store data created by the Internet of Things, and that data grows exponentially, forcing IoT to think about cloud storage for data storage. Security issues are a major concern when handling and processing data in DI and cloud environments. Secure integration of IoT and cloud computing, and introduced a model to ensure this integration. The secure database of any IoT operating system was suffers from poorly protected read and write functions, which limits data storage on any IoT platform. In addition, clouds can provide space to store a wide variety of data that plays an important role in the world of cyber security. However, large centralized systems operating in the cloud are also very vulnerable due to their power, so they can be transformed into a kind of double-edged sword. In this paper, we propose a novel secure lightweight authentication scheme for data storage (SLA-DS) in IoT and cloud server. The SLA-DS integrates IoT and cloud technology combination which mainly focuses on security issues.

Code‐level model checking in the software development workflow at Amazon Web Services

AbstractThis article describes a style of applying symbolic model checking developed over the course of four years at Amazon Web Services (AWS). Lessons learned are drawn from proving properties of numerous C‐based systems, for example, custom hypervisors, encryption code, boot loaders, and an IoT operating system. Using our methodology, we find that we can prove the correctness of industrial low‐level C‐based systems with reasonable effort and predictability. Furthermore, AWS developers are increasingly writing their own formal specifications. As part of this effort, we have developed a CI system that allows integration of the proofs into standard development workflows and extended the proof tools to provide better feedback to users. All proofs discussed in this article are publicly available on GitHub.

A Review on IoT Operating Systems

A Review on IoT Operating Systems

Over-the-Air Software Updates in the Internet of Things: An Overview of Key Principles

Due to the fast pace at which IoT is evolving, there is an increasing need to support over-theair software updates for security updates, bug fixes, and software extensions. To this end, multiple over-the-air techniques have been proposed, each covering a specific aspect of the update process, such as (partial) code updates, data dissemination, and security. However, each technique introduces overhead, especially in terms of energy consumption, thereby impacting the operational lifetime of the battery constrained devices. Until now, a comprehensive overview describing the different update steps and quantifying the impact of each step is missing in the scientific literature, making it hard to assess the overall feasibility of an over-the-air update. To remedy this, our article analyzes which parts of an IoT operating system are most updated after device deployment, proposes a step-by-step approach to integrate software updates in IoT solutions, and quantifies the energy cost of each of the involved steps. The results show that besides the obvious dissemination cost, other phases such as security also introduce a significant overhead. For instance, a typical firmware update requires 135.026 mJ, of which the main portions are data dissemination (63.11 percent) and encryption (5.29 percent). However, when modular updates are used instead, the energy cost (e.g., for a MAC update) is reduced to 26.743 mJ (48.69 percent for data dissemination and 26.47 percent for encryption).

S The Security MicroVisor: A Formally-Verified Software-Based Security Architecture for the Internet of Things

The Internet of Things (IoT) is shaped by the increasing number of low-cost Internet-connected embedded devices that are becoming ubiquitous in every aspect of modern life. With their cost-sensitive design, integrating hardware-based security mechanisms into such devices is undesirable. Therefore, securing these devices is a particularly difficult challenge, especially, due to their growing popularity as attack targets, via remote malware infestations. The vast majority of such devices are bare-metal, where they execute programs in fully-accessible and unprotected memories without any operating system and even without including any form of security. This is beside the fact that IoToperating systems offer little or no protection. This paper addresses this problem through the concept of a Security MicroVisor (S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</sub> V), which provides embedded devices that lack hardware-based memory protection units with memory isolation using software virtualisation and assembly-level code verification. More specifically, our contribution is two-fold. First, we propose S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</sub> V as a software-based memory isolation technique. We then formally verify the software architecture, written in C, to prove that it is memory-safe and crash-free. Second, we propose a software-based remote attestation, as an example of a fundamental security service that can be implemented on top of S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</sub> V, to detect malware-infected devices. We first describe the design and implementation of S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</sub> V. Then, we highlight the formal verification of software architecture, and characterize the remote attestation protocol. We evaluate the S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</sub> V implementation using an 8-bit AVR microcontroller that is widely used in IoT devices. Evaluation results show that S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</sub> V provides strong security guarantees while maintaining extremely low overhead in terms of memory footprint, performance, and power consumption. Furthermore, we extend the performance evaluation also to the remote attestation scheme, illustrating its limited overhead.

Testing Real-Time Applications on Windows 10 IOT Using the Nyquist Theory

Raspberry Pi is a mini-computer that is provided to carry out activities quickly and precisely, but Raspberry Pi was created to not be able to do the real-time system with the support of Windows 10 IoT operating system, so the real-time system can be done on Raspberry Pi. The real-time applied in the application needs to be tested with the Nyquist theory. The purpose of this study was to get real-time system measurements available on Windows 10 IoT. This test is done using the Nyquist theory by calculating the results of measurements on mp3 streaming performed on Windows 10 IoT.

Functional Test Case Generator for Contiki Operating System and Cooja Simulator

Evolving multi-parameter, multi-configuration systems require regression test suite that can be customized. This is in terms of run time. Run time can be customized by generating the combinations using combinatorial techniques. For systems like Contiki operating system, the test cases need to be executed in its simulator Cooja. Executing test cases in a simulator requires functional test cases to be generated from the combinatorial parameter combinations obtained. In this work we present a methodology to generate the functional test cases. We present Functional Test Case Generator for Contiki and Cooja (FTCGCC), which is a tool developed using our methodology. We demonstrate use of our tool by generating customizable regression test suite for Contiki and Cooja using code coverage as criteria. FTCGCC is developed for the test case generation when target System Under Test is IoT operating system Contiki and its simulator Cooja.

IoT Operating System Based Fuzzy Inference System for Home Energy Management System in Smart Buildings.

Energy consumption in the residential sector is 25% of all the sectors. The advent of smart appliances and intelligent sensors have increased the realization of home energy management systems. Acquiring balance between energy consumption and user comfort is in the spotlight when the performance of the smart home is evaluated. Appliances of heating, ventilation and air conditioning constitute up to 64% of energy consumption in residential buildings. A number of research works have shown that fuzzy logic system integrated with other techniques is used with the main objective of energy consumption minimization. However, user comfort is often sacrificed in these techniques. In this paper, we have proposed a Fuzzy Inference System (FIS) that uses humidity as an additional input parameter in order to maintain the thermostat set-points according to user comfort. Additionally, we have used indoor room temperature variation as a feedback to proposed FIS in order to get the better energy consumption. As the number of rules increase, the task of defining them in FIS becomes time consuming and eventually increases the chance of manual errors. We have also proposed the automatic rule base generation using the combinatorial method. The proposed techniques are evaluated using Mamdani FIS and Sugeno FIS. The proposed method provides a flexible and energy efficient decision-making system that maintains the user thermal comfort with the help of intelligent sensors. The proposed FIS system requires less memory and low processing power along with the use of sensors, making it possible to be used in the IoT operating system e.g., RIOT. Simulation results validate that the proposed technique reduces energy consumption by 28%.

Performance Evaluation of Cryptographic Algorithms over IoT Platforms and Operating Systems

The deployment of security services over Wireless Sensor Networks (WSN) and IoT devices brings significant processing and energy consumption overheads. These overheads are mainly determined by algorithmic efficiency, quality of implementation, and operating system. Benchmarks of symmetric primitives exist in the literature for WSN platforms but they are mostly focused on single platforms or single operating systems. Moreover, they are not up to date with respect to implementations and/or operating systems versions which had significant progress. Herein, we provide time and energy benchmarks of reference implementations for different platforms and operating systems and analyze their impact. Moreover, we not only give the first benchmark results of symmetric cryptography for the Intel Edison IoT platform but also describe a methodology of how to measure energy consumption on that platform.

Comparison and Analysis of Functional Features of IoT Operating Systems

Comparison and Analysis of Functional Features of IoT Operating Systems