Decentralized P2P Broker for M2M and IoT Applications

The recent increase in the number of connected IoT devices, as well as the heterogeneity of the environments where they are deployed, has derived into the growth of the complexity of Machine-to-Machine (M2M) communication protocols and technologies. In addition, the hardware used by IoT devices has become more powerful and efficient. Such enhancements have made it possible to implement novel decentralized computing architectures like the ones based on edge computing, which offload part of the central server processing by using multiple distributed low-power nodes. In order to ease the deployment and synchronization of decentralized edge computing nodes, this paper describes an M2M distributed protocol based on Peer-to-Peer (P2P) communications that can be executed on low-power ARM devices. In addition, this paper proposes to make use of brokerless communications by using a distributed publication/subscription protocol. Thanks to the fact that information is stored in a distributed way among the nodes of the swarm and since each node can implement a specific access control system, the proposed system is able to make use of write access mechanisms and encryption for the stored data so that the rest of the nodes cannot access sensitive information. In order to test the feasibility of the proposed approach, a comparison with an Message-Queuing Telemetry Transport (MQTT) based architecture is performed in terms of latency, network consumption and performance.

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Level Converters for Ultra Low Power IoT Applications

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.16.11409 ◽

2018 ◽

Vol 7 (2.16) ◽

pp. 19

Author(s):

T Yugendra Chary ◽

S Anitha ◽

M Alamillo ◽

Ameet Chavan

Keyword(s):

Energy Efficiency ◽

Low Power ◽

Slight Reduction ◽

Dramatic Improvement ◽

Modest Improvement ◽

Ultra Low Power ◽

Iot Applications ◽

Communication Devices ◽

And Performance ◽

Level Converter

For efficient ultra-low power IoT applications, working with various communication devices and sensors which operating voltages from subthreshold to superthreshold levels which requires wide variety of robust level converters for signal interfacing with low power dissipation. This paper proposes two topologies of level converter circuits that offer dramatic improvement in power and performance when compared to the existing level converters that shift signals from sub to super threshold levels for IoT applications. At 250 mV, the first proposed circuit - a modification of a tradition al current mirror level converter - offers the best energy efficiency with approximately seven times less energy consumption per operation than the existing design, but suffers from a slight reduction in performance. However, a second proposed circuit - based on a two-stage level converter - at the same voltage enhances performance by several orders of magnitude while still maintaining a modest improvement in energy efficiency. The Energy Delay Products (EDP) of the two proposed designs are equivalent and are approximately four times better than the best existing design. Consequently, the two circuit options either optimizes power or performance with improved overall EDP.

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An SDN-Based Connectivity Control System for Wi-Fi Devices

Wireless Communications and Mobile Computing ◽

10.1155/2018/9359878 ◽

2018 ◽

Vol 2018 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Duc-Thang Nguyen ◽

Taehong Kim

Keyword(s):

Control System ◽

Service Providers ◽

Connection Management ◽

Fine Grained ◽

Connectivity Information ◽

Wireless Environment ◽

Remote Services ◽

Iot Devices ◽

And Performance ◽

High Level

In recent years, the prevalence of Wi-Fi-enabled devices such as smartphones, smart appliances, and various sensors has increased. As most IoT devices lack a display or a keypad owing to their tiny size, it is difficult to set connectivity information such as service set identifier (SSID) and password without any help from external devices such as smartphones. Moreover, it is much more complex to apply advanced connectivity options such as SSID hiding, MAC ID filtering, and Wi-Fi Protected Access (WPA) to these devices. Thus, we need a new Wi-Fi network management system which not only facilitates client access operations but also provides a high-level authentication procedure. In this paper, we introduce a remote connectivity control system for Wi-Fi devices based on software-defined networking (SDN) in a wireless environment. The main contributions of the proposed system are twofold: (i) it enables network owner/administrator to manage and approve connection request from Wi-Fi devices through remote services, which is essential for easy connection management across diverse IoT devices; (ii) it also allows fine-grained access control at the device level through remote control. We describe the architecture of SDN-based remote connectivity control of Wi-Fi devices. While verifying the feasibility and performance of the proposed system, we discuss how the proposed system can benefit both service providers and users.

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Automatic Failure Recovery for Container-Based IoT Edge Applications

Electronics ◽

10.3390/electronics10233047 ◽

2021 ◽

Vol 10 (23) ◽

pp. 3047

Author(s):

Kolade Olorunnife ◽

Kevin Lee ◽

Jonathan Kua

Keyword(s):

Internet Of Things ◽

Smart Cities ◽

Smart Homes ◽

Edge Computing ◽

Failure Recovery ◽

Software Failures ◽

Iot Applications ◽

Remote Management ◽

Management Ability ◽

Iot Devices

Recent years have seen the rapid adoption of Internet of Things (IoT) technologies, where billions of physical devices are interconnected to provide data sensing, computing and actuating capabilities. IoT-based systems have been extensively deployed across various sectors, such as smart homes, smart cities, smart transport, smart logistics and so forth. Newer paradigms such as edge computing are developed to facilitate computation and data intelligence to be performed closer to IoT devices, hence reducing latency for time-sensitive tasks. However, IoT applications are increasingly being deployed in remote and difficult to reach areas for edge computing scenarios. These deployment locations make upgrading application and dealing with software failures difficult. IoT applications are also increasingly being deployed as containers which offer increased remote management ability but are more complex to configure. This paper proposes an approach for effectively managing, updating and re-configuring container-based IoT software as efficiently, scalably and reliably as possible with minimal downtime upon the detection of software failures. The approach is evaluated using docker container-based IoT application deployments in an edge computing scenario.

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A lightweight cryptographic algorithm for the transmission of images from road environments in self-driving

Cybersecurity ◽

10.1186/s42400-020-00066-2 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Runchen Gao ◽

Shen Li ◽

Yuqi Gao ◽

Rui Guo

Keyword(s):

Large Scale ◽

Edge Computing ◽

Sensitive Information ◽

Security Strategy ◽

Privacy Leakage ◽

Computational Overhead ◽

Cryptographic Algorithm ◽

Comparable Encryption ◽

Iot Devices ◽

The Internet Of Things

AbstractWith the large-scale application of 5G in industrial production, the Internet of Things has become an important technology for various industries to achieve efficiency improvement and digital transformation with the help of the mobile edge computing. In the modern industry, the user often stores data collected by IoT devices in the cloud, but the data at the edge of the network involves a large of the sensitive information, which increases the risk of privacy leakage. In order to address these two challenges, we propose a security strategy in the edge computing. Our security strategy combines the Feistel architecture and short comparable encryption based on sliding window (SCESW). Compared to existing security strategies, our proposed security strategy guarantees its security while significantly reducing the computational overhead. And our GRC algorithm can be successfully deployed on a hardware platform.

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The Art of Designing Remote IoT Devices—Technologies and Strategies for a Long Battery Life

Sensors ◽

10.3390/s21030913 ◽

2021 ◽

Vol 21 (3) ◽

pp. 913

Author(s):

Gilles Callebaut ◽

Guus Leenders ◽

Jarne Van Mulders ◽

Geoffrey Ottoy ◽

Lieven De Strycker ◽

...

Keyword(s):

Low Power ◽

Long Range ◽

Battery Life ◽

Sensors And Actuators ◽

Iot Applications ◽

Rich Diversity ◽

Low Energy Consumption ◽

Networking Technologies ◽

Enhance Efficiency ◽

Iot Devices

Long-range wireless connectivity technologies for sensors and actuators open the door for a variety of new Internet of Things (IoT) applications. These technologies can be deployed to establish new monitoring capabilities and enhance efficiency of services in a rich diversity of domains. Low energy consumption is essential to enable battery-powered IoT nodes with a long autonomy. This paper explains the challenges posed by combining low-power and long-range connectivity. An energy breakdown demonstrates the dominance of transmit and sleep energy. The principles for achieving both low-power and wide-area are outlined, and the landscape of available networking technologies that are suited to connect remote IoT nodes is sketched. The typical anatomy of such a node is presented, and the subsystems are zoomed into. The art of designing remote IoT devices requires an application-oriented approach, where a meticulous design and smart operation are essential to grant a long battery life. In particular we demonstrate the importance of strategies such as “think before you talk” and “race to sleep”. As maintenance of IoT nodes is often cumbersome due to being deployed at hard to reach places, extending the battery life of these devices is critical. Moreover, the environmental impact of batteries further demonstrates the need for a longer battery life in order to reduce the number of batteries used.

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Fine-Grained Task Access Control System for Mobile Crowdsensing

Security and Communication Networks ◽

10.1155/2021/6682456 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Jingwei Wang ◽

Xinchun Yin ◽

Jianting Ning

Keyword(s):

Control System ◽

Access Control ◽

Privacy Preservation ◽

Security Analysis ◽

Task Assignment ◽

Sensitive Information ◽

Mobile Crowdsensing ◽

Fine Grained ◽

Access Control System ◽

Model Training

Mobile crowdsensing enables people to collect and process a massive amount of information by using social resources without any cost on sensor deployment or model training. Many schemes focusing on the problems of task assignment and privacy preservation have been proposed so far. However, the privacy-preserving of requesters and task access control, which are vital to mobile crowdsensing, is barely considered in the literature. To address the aforementioned issues, a fine-grained task access control system for mobile crowdsensing is proposed. In particular, the requester can decide the group of task performers who can access the task by utilizing attribute-based encryption technology. T he untrusted crowdsensing platform cannot obtain any sensitive information concerning the requester or the task, while the qualified task performers are capable of retrieving tasks within 0.85 ms. Security analysis and experimental results are presented to show the feasibility and efficiency of the proposed system.

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Automatic Key Update Mechanism for Lightweight M2M Communication and Enhancement of IoT Security: A Case Study of CoAP Using Libcoap Library

Sensors ◽

10.3390/s22010340 ◽

2022 ◽

Vol 22 (1) ◽

pp. 340

Author(s):

Wen-Chung Tsai ◽

Tzu-Hsuan Tsai ◽

Te-Jen Wang ◽

Mao-Lun Chiang

Keyword(s):

Information Exchange ◽

Iot Security ◽

M2m Communication ◽

Iot Applications ◽

Data Transfers ◽

Key Update ◽

Iot Devices ◽

One Time Password ◽

Cloud Servers

The ecosystem for an Internet of Things (IoT) generally comprises endpoint clients, network devices, and cloud servers. Thus, data transfers within the network present multiple security concerns. The recent boom in IoT applications has accelerated the need for a network infrastructure that provides timely and safe information exchange services. A shortcoming of many existing networks is the use of static key authentication. To enable the use of automatic key update mechanisms in IoT devices and enhance security in lightweight machine-to-machine (M2M) communications, we propose a key update mechanism, namely, double OTP (D-OTP), which combines both one-time password (OTP) and one-time pad to achieve an IoT ecosystem with theoretically unbreakable security. The proposed D-OTP was implemented into the Constrained Application Protocol (CoAP) through the commonly used libcoap library. The experimental results revealed that an additional 8.93% latency overhead was required to obtain an unbreakable guarantee of data transfers in 100 CoAP communication sessions.

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UAV-Enabled Mobile Edge-Computing for IoT Based on AI: A Comprehensive Review

Drones ◽

10.3390/drones5040148 ◽

2021 ◽

Vol 5 (4) ◽

pp. 148

Author(s):

Yassine Yazid ◽

Imad Ez-Zazi ◽

Antonio Guerrero-González ◽

Ahmed El Oualkadi ◽

Mounir Arioua

Keyword(s):

Energy Demand ◽

Edge Computing ◽

Mobile Edge Computing ◽

Comprehensive Review ◽

Iot Applications ◽

Wide Range ◽

Technology Applications ◽

Iot Devices ◽

Insight Into

Unmanned aerial vehicles (UAVs) are becoming integrated into a wide range of modern IoT applications. The growing number of networked IoT devices generates a large amount of data. However, processing and memorizing this massive volume of data at local nodes have been deemed critical challenges, especially when using artificial intelligence (AI) systems to extract and exploit valuable information. In this context, mobile edge computing (MEC) has emerged as a way to bring cloud computing (CC) processes within reach of users, to address computation-intensive offloading and latency issues. This paper provides a comprehensive review of the most relevant research works related to UAV technology applications in terms of enabled or assisted MEC architectures. It details the utility of UAV-enabled MEC architecture regarding emerging IoT applications and the role of both deep learning (DL) and machine learning (ML) in meeting various limitations related to latency, task offloading, energy demand, and security. Furthermore, throughout this article, the reader gains an insight into the future of UAV-enabled MEC, the advantages and the critical challenges to be tackled when using AI.

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Queec: QoE-aware Edge Computing for IoT Devices under Dynamic Workloads

ACM Transactions on Sensor Networks ◽

10.1145/3442363 ◽

2021 ◽

Vol 17 (3) ◽

pp. 1-23

Author(s):

Borui Li ◽

Wei Dong ◽

Gaoyang Guan ◽

Jiadong Zhang ◽

Tao Gu ◽

...

Keyword(s):

Speech Recognition ◽

Optimization Problem ◽

State Of The Art ◽

Computing System ◽

Edge Computing ◽

Limited Resources ◽

Event Processing ◽

Iot Applications ◽

Iot Devices ◽

User Tasks

Many IoT applications have the requirements of conducting complex IoT events processing (e.g., speech recognition) that are hardly supported by low-end IoT devices due to limited resources. Most existing approaches enable complex IoT event processing on low-end IoT devices by statically allocating tasks to the edge or the cloud. In this article, we present Queec, a QoE-aware edge computing system for complex IoT event processing under dynamic workloads. With Queec, the complex IoT event processing tasks that are relatively computation-intensive for low-end IoT devices can be transparently offloaded to nearby edge nodes at runtime. We formulate the problem of scheduling multi-user tasks to multiple edge nodes as an optimization problem, which minimizes the overall offloading latency of all tasks while avoiding the overloading problem. We implement Queec on low-end IoT devices, edge nodes, and the cloud. We conduct extensive evaluations, and the results show that Queec reduces 56.98% of the offloading latency on average compared with the state-of-the-art under dynamic workloads, while incurring acceptable overhead.

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Edge-Computing Architectures for Internet of Things Applications: A Survey

Sensors ◽

10.3390/s20226441 ◽

2020 ◽

Vol 20 (22) ◽

pp. 6441 ◽

Cited By ~ 1

Author(s):

Salam Hamdan ◽

Moussa Ayyash ◽

Sufyan Almajali

Keyword(s):

Cloud Computing ◽

Internet Of Things ◽

Resource Limitation ◽

Edge Computing ◽

Iot Applications ◽

Life Tasks ◽

Iot Devices ◽

Processing And Storage ◽

Time Critical ◽

And Storage

The rapid growth of the Internet of Things (IoT) applications and their interference with our daily life tasks have led to a large number of IoT devices and enormous sizes of IoT-generated data. The resources of IoT devices are limited; therefore, the processing and storing IoT data in these devices are inefficient. Traditional cloud-computing resources are used to partially handle some of the IoT resource-limitation issues; however, using the resources in cloud centers leads to other issues, such as latency in time-critical IoT applications. Therefore, edge-cloud-computing technology has recently evolved. This technology allows for data processing and storage at the edge of the network. This paper studies, in-depth, edge-computing architectures for IoT (ECAs-IoT), and then classifies them according to different factors such as data placement, orchestration services, security, and big data. Besides, the paper studies each architecture in depth and compares them according to various features. Additionally, ECAs-IoT is mapped according to two existing IoT layered models, which helps in identifying the capabilities, features, and gaps of every architecture. Moreover, the paper presents the most important limitations of existing ECAs-IoT and recommends solutions to them. Furthermore, this survey details the IoT applications in the edge-computing domain. Lastly, the paper recommends four different scenarios for using ECAs-IoT by IoT applications.

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