Internet Of Things Operating Systems Research Articles

A survey on routing protocols supported by the Contiki Internet of things operating system

Standardization and technology advancements have helped the realization of the Internet of things (IoT). The availability of low-cost IoT devices has also played a key role in furthering IoT research, development, and deployment. IoT operating systems (OSs) provide integration of software and hardware components. The availability of standard protocols, heterogeneous hardware support, ease of development, and simulation or emulation support are desirable features of IoT OSs. Contiki OS is one of the contenders for future IoT OSs. It was proposed in 2003, and since then, it has been continually under development and upgraded by professionals, academia, and researchers. Contiki OS supports open source, Internet standards, power awareness, dynamic module loading, and many hardware platforms. The diverse applications of IoT, including smart homes, smart health, smart cities, require efficient network connectivity and demand intelligent routing protocols that can handle heterogeneous, mobile, and diverse networks. Subsequently, designing routing protocols for memory- and central processing unit (CPU)-constrained IoT devices is a very challenging task. Therefore, this paper surveys the state-of-the-art routing protocols of Contiki OS. To the best of the authors’ knowledge, this is the first study to classify the Contiki OS routing protocol literature and list the potential challenges and future work.

A Survey on Resource Management in IoT Operating Systems

Recently, the Internet of Things (IoT) concept has attracted a lot of attention due to its capability to translate our physical world into a digital cyber world with meaningful information. The IoT devices are smaller in size, sheer in number, contain less memory, use less energy, and have more computational capabilities. These scarce resources for IoT devices are powered by small operating systems (OSs) that are specially designed to support the IoT devices’ diverse applications and operational requirements. These IoT OSs are responsible for managing the constrained resources of IoT devices efficiently and in a timely manner. In this paper, discussions on IoT devices and OS resource management are provided. In detail, the resource management mechanisms of the state-of-the-art IoT OSs, such as Contiki, TinyOS, and FreeRTOS, are investigated. The different dimensions of their resource management approaches (including process management, memory management, energy management, communication management, and file management) are studied, and their advantages and limitations are highlighted.

Review on open source operating systems for internet of things

Internet of Things (IoT) is an environment in which everywhere and every device became smart in a smart world. Internet of Things is growing vastly; it is an integrated system of uniquely identifiable communicating devices which exchange information in a connected network to provide extensive services. IoT devices have very limited memory, computational power, and power supply. Traditional operating systems (OS) have no way to meet the needs of IoT systems. In this paper, we thus analyze the challenges of IoT OS and survey applicable open source OSs.

Recoverable Random Numbers in an Internet of Things Operating System

Over the past decade, several security issues with Linux Random Number Generator (LRNG) on PCs and Androids have emerged. The main problem involves the process of entropy harvesting, particularly at boot time. An entropy source in the input pool of LRNG is not transferred into the non-blocking output pool if the entropy counter of the input pool is less than 192 bits out of 4098 bits. Because the entropy estimation of LRNG is highly conservative, the process may require more than one minute for starting the transfer. Furthermore, the design principle of the estimation algorithm is not only heuristic but also unclear. Recently, Google released an Internet of Things (IoT) operating system called Brillo based on the Linux kernel. We analyze the behavior of the random number generator in Brillo, which inherits that of LRNG. In the results, we identify two features that enable recovery of random numbers. With these features, we demonstrate that random numbers of 700 bytes at boot time can be recovered with the success probability of 90% by using time complexity for 5.20 × 2 40 trials. Therefore, the entropy of random numbers of 700 bytes is merely about 43 bits. Since the initial random numbers are supposed to be used for sensitive security parameters, such as stack canary and key derivation, our observation can be applied to practical attacks against cryptosystem.