The Internet of Things (IoTs) enables coupling of digital and physical objects using worthy communication technologies and introduces a future vision where computing systems, users and objects cooperate for convenience and economic benefits. Such a vision requires seamless security, data privacy, authentication and robustness against attacks. These attributes can be introduced by blockchain, a distributed ledger that maintains an immutable log of network transactions. In this paper, we present a comprehensive review on how to remodel blockchain to the specific IoT needs in order to develop Blockchain based IoT (BIoT) applications and aim to shape a coherent picture of the current state-of-the-art efforts in this direction. After describing the basic characteristics and requirements of IoT, evolution of blockchain is presented. In this regard, we start with the fundamental working principles of blockchain and how such systems achieve auditability, security and decentralization. Further, we describe the most relevant BIoT applications, its architecture design and security aspects. From there, we build our narrative on the centralized IoT challenges followed by recent advances towards solving them. Finally, some future directions are enumerated with the aim to guide future BIoT researchers on challenges that needs to be considered ahead of deploying the next generation of BIoT applications.

Unification of Blockchain and Internet of Things (BIoT): requirements, working model, challenges and future directions

Blockchain is a technology that can ensure data integrity in a distributed network, and it is actively applied in various fields. Recently, blockchain is gaining attention due to combining with the Internet of Things (IoT) technology in the industrial field. Moreover, many researchers have proposed the Industrial IoT (IIoT) architecture with blockchain for data integrity and efficient management. The IIoT network consists of many heterogeneous devices (e.g., sensors, actuators, and programmable logic controllers (PLC)) with resources-constrained, and the availability of the network must be preferentially considered. Therefore, applying the existed blockchain technology is still challenging. There are some results about the technique of constructing blockchain lightly to solve this challenge. However, in these results, the analysis in perspective of cryptographic performance (area, throughput, and power consumption) has not been considered sufficiently, or only focused on the architecture of the blockchain network. The blockchain technology is based on cryptographic techniques, and the main part is a cryptographic hash function. Therefore, if we construct the blockchain-based IIoT architecture, we have to consider the performance of the hash function. Many lightweight hash functions have been proposed recently for the resource-constrained environment, and it can also be used to the blockchain. Therefore, in this paper, we analyze the considerations of lightweight blockchain for IIoT. Also, we conduct an analysis of lightweight hash for blockchain, and propose a new lightweight hash-based blockchain architecture that can change the hash algorithm used for mining adjust to network traffic.

https://www.mdpi.com/2076-3417/9/18/3740/pdf

A Lightweight Hash-Based Blockchain Architecture for Industrial IoT

Artificial intelligence (AI) and machine learning (ML) techniques have huge potential to efficiently manage the automated operation of the internet of things (IoT) nodes deployed in smart cities. In smart cities, the major IoT applications are smart traffic monitoring, smart waste management, smart buildings and patient healthcare monitoring. The small size IoT nodes based on low power Bluetooth (IEEE 802.15.1) standard and wireless sensor networks (WSN) (IEEE 802.15.4) standard are generally used for transmission of data to a remote location using gateways. The WSN based IoT (WSN-IoT) design problems include network coverage and connectivity issues, energy consumption, bandwidth requirement, network lifetime maximization, communication protocols and state of the art infrastructure. In this paper, the authors propose machine learning methods as an optimization tool for regular WSN-IoT nodes deployed in smart city applications. As per the author’s knowledge, this is the first in-depth literature survey of all ML techniques in the field of low power consumption WSN-IoT for smart cities. The results of this unique survey article show that the supervised learning algorithms have been most widely used (61%) as compared to reinforcement learning (27%) and unsupervised learning (12%) for smart city applications.

https://www.mdpi.com/2079-9292/10/9/1012/pdf

Machine Learning in Wireless Sensor Networks for Smart Cities: A Survey

Internet of Things (IoT) deployments are on the rise globally with Low Power Wide Area Networks (LPWAN) providing the wireless networks needed for this expansion. One of these technologies namely Long Range Wide Area Network (LoRaWAN) has proven to be a very popular choice. The LoRaWAN protocol allows for confirmed traffic from the end device to the gateway (uplink) and the reverse (downlink), increasing the number of IoT use cases that it can support. However, this comes at a cost as downlink traffic severely impacts scalability due to in part a gateway's duty cycle restrictions. This paper highlights some of the use cases that require confirmed traffic, examines the recent works focused on LoRaWAN confirmed traffic and discusses the mechanism with which is implemented. It was found that confirmed traffic is viable in small networks, especially when data transfer is infrequent. Additionally, the following aspects negatively impact the viability of confirmed traffic in large networks: the duty cycle restrictions placed on gateways, the use of spreading factor 12 for receive window 2 transmissions, a high maximum number of transmissions (NbTrans) and the ACK_TIMEOUT transmission backoff interval. The paper also raises and suggests solutions to open research challenges that must be overcome to increase the viability of confirmed traffic.

/pdf/a-survey-on-the-viability-of-confirmed-traffic-in-a-lorawan-1awnvw18og.pdf

A Survey on the Viability of Confirmed Traffic in a LoRaWAN

Technical reports indicate that wireless and mobile devices will account for 71% of all IP traffic by 2022, an increase of 19% over four years. This increase is related to advances in wireless data communication technologies. Wireless networks have become one of the most important ways to connect devices to the Internet, therein improving productivity and encouraging information sharing. IEEE 802.11, known as Wi-Fi, has become the main standard for wireless local area networks. The most important metrics for measuring the quality of Wi-Fi are delay, jitter, and packet loss. Packet loss occurs when one or more packets fail to reach their destination and can occur for a variety of reasons. Packet loss influences the user's perceived quality of applications over Wi-Fi networks, mainly multimedia and real-time applications. The availability of accurate models for packet loss in Wi-Fi networks enables the development of more efficient methods for performance analysis and network design, as well as better computational simulations. Modeling packet loss in such networks presents a major challenge because packets may be lost for many different reasons, including signal attenuation, noise, multipathing, signal refraction, thermal noise, competition for media access and buffer issues. In this paper, we provide an overview of the causes of packet loss and a comprehensive survey of the available models for packet loss in Wi-Fi networks. The potential benefits of the survey are: (i) the systematic presentation of available packet loss models for Wi-Fi networks, their parameters, and respective packet loss rate evaluation, (ii) comparison of models considering validation scenarios and input parameters, and (iii) description of open issues and future research directions. We hope that our analysis will help researchers understand the most important characteristics of the packet loss process in Wi-Fi networks and the strengths and weaknesses of the main packet loss models.

/pdf/mac-layer-packet-loss-models-for-wi-fi-networks-a-survey-1i2y1uvxo7.pdf

MAC-Layer Packet Loss Models for Wi-Fi Networks: A Survey

The proliferation of embedded systems, wireless technologies, and Internet protocols have enabled the Internet of Things (IoT) to bridge the gap between the virtual and physical world through enabling the monitoring and actuation of the physical world controlled by data processing systems. Wireless technologies, despite their offered convenience, flexibility, low cost, and mobility pose unique challenges such as fading, interference, energy, and security, which must be carefully addressed when using resource-constrained IoT devices. To this end, the efforts of the research community have led to the standardization of several wireless technologies for various types of application domains depending on factors such as reliability, latency, scalability, and energy efficiency. In this paper, we first overview these standard wireless technologies, and we specifically study the MAC and physical layer technologies proposed to address the requirements and challenges of wireless communications. Furthermore, we explain the use of these standards in various application domains, such as smart homes, smart healthcare, industrial automation, and smart cities, and discuss their suitability in satisfying the requirements of these applications. In addition to proposing guidelines to weigh the pros and cons of each standard for an application at hand, we also examine what new strategies can be exploited to overcome existing challenges and support emerging IoT applications.

https://hal.archives-ouvertes.fr/hal-02161803/document

Angelina Poole

Papers

Low-Power Wireless for the Internet of Things: Standards and Applications