Automatic Failure Recovery for Container-Based IoT Edge Applications

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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Applications of IOT in Smart Cities and Smart Environment

International Research Journal of Multidisciplinary Technovation ◽

10.34256/irjmtcon2 ◽

2019 ◽

pp. 7-17 ◽

Cited By ~ 1

Author(s):

Keerthivasan G ◽

Aishwarya G ◽

Jawahar G ◽

Muthukumar C

Keyword(s):

Internet Of Things ◽

Smart Cities ◽

Smart Homes ◽

The Internet ◽

Large Network ◽

Smart Environment ◽

Transfer Data ◽

Ecological Resources ◽

The World ◽

Iot Devices

Internet of things is one of the emerging technologies in the world. Through which we can generate a large network among the tiny devices to communicate with each other to develop environmental and ecological resources. Most of the smart technology devices are designed by IoT network of devices. By connecting these devices that help to interact with each other and to collect and transfer data over the internet. The IoT devices working speed and their performance have improved by introducing a device called a sensor. The idea of IoT devices with sensors that sense the data and make smart decisions in the environment. This paper makes it clear about the benefits of IoT devices over technology in the modern environment. The sensors in IoT devices are connected to Wi-Fi, Bluetooth and RFID etc. to collect useful data. By connecting devices over the network, the world will become smart and thus it evolves the smart environment including smart homes, smart buildings and smart cities. It is believed that about 30 billion people in the world will use at least one IoT technology devices by the year 2020. To maintain our environment safe and secure the IoT devices play a major role in several enabling technologies. This paper is to present the applications of IoT in smart cities and the environment and a brief explanation about their uses.

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Internet of Things Research Challenges

The Internet of Things ◽

10.4018/978-1-5225-1832-7.ch012 ◽

2017 ◽

pp. 260-277

Author(s):

Mahmoud Elkhodr ◽

Seyed Shahrestani ◽

Hon Cheung

Keyword(s):

Internet Of Things ◽

Short Range ◽

Smart Cities ◽

Smart Homes ◽

The Internet ◽

Research Issues ◽

Iot Applications ◽

Research Challenges ◽

Business Opportunities ◽

The Internet Of Things

The Internet of Things (IoT) promises to revolute communications on the Internet. The IoT enables numerous business opportunities in fields as diverse as e-health, smart cities, smart homes, among many others. It incorporates multiple long-range, short-range, and personal area wireless networks and technologies into the designs of IoT applications. This will result in the IoT being pervasive in many areas which raise many challenges. This chapter reviews the major research issues challenging the IoT with regard to security, privacy, and management.

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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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ARTIFICIAL INTELLIGENCE AS A SERVICE IN DISTRIBUTED MULTI ACCESS EDGE COMPUTING ON 5G EXTRACTING DATA USING IOT AND INCLUDING AR/VR FOR REAL-TIME REPORTING

INFORMATION TECHNOLOGY IN INDUSTRY ◽

10.17762/itii.v9i1.220 ◽

2021 ◽

Vol 9 (1) ◽

pp. 912-931

Author(s):

Pavan Madduru

Keyword(s):

Cloud Computing ◽

Internet Of Things ◽

Virtual Machines ◽

Smart Cities ◽

Assistive Technologies ◽

Edge Computing ◽

Smart Devices ◽

The Internet ◽

Iot Applications ◽

The Internet Of Things

To meet the growing demand for mobile data traffic and the stringent requirements for Internet of Things (IoT) applications in emerging cities such as smart cities, healthcare, augmented / virtual reality (AR / VR), fifth-generation assistive technologies generation (5G) Suggest and use on the web. As a major emerging 5G technology and a major driver of the Internet of Things, Multiple Access Edge Computing (MEC), which integrates telecommunications and IT services, provides cloud computing capabilities at the edge of an access network. wireless (RAN). By providing maximum compute and storage resources, MEC can reduce end-user latency. Therefore, in this article we will take a closer look at 5G MEC and the Internet of Things. Analyze the main functions of MEC in 5G and IoT environments. It offers several core technologies that enable the use of MEC in 5G and IoT, such as cloud computing, SDN / NFV, information-oriented networks, virtual machines (VMs) and containers, smart devices, shared networks and computing offload. This article also provides an overview of MEC's role in 5G and IoT, a detailed introduction to MEC-enabled 5G and IoT applications, and future perspectives for MEC integration with 5G and IoT. Additionally, this article will take a closer look at the MEC research challenges and unresolved issues around 5G and the Internet of Things. Finally, we propose a use case that MEC uses to obtain advanced intelligence in IoT scenarios.

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Internet of Things Research Challenges

Security Solutions for Hyperconnectivity and the Internet of Things - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-5225-0741-3.ch002 ◽

2017 ◽

pp. 13-36 ◽

Cited By ~ 1

Author(s):

Mahmoud Elkhodr ◽

Seyed Shahrestani ◽

Hon Cheung

Keyword(s):

Internet Of Things ◽

Short Range ◽

Smart Cities ◽

Smart Homes ◽

The Internet ◽

Research Issues ◽

Iot Applications ◽

Research Challenges ◽

Business Opportunities ◽

The Internet Of Things

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Neighbor Aware Protocols for IoT Devices in Smart Cities—Overview, Challenges and Solutions

Electronics ◽

10.3390/electronics9060902 ◽

2020 ◽

Vol 9 (6) ◽

pp. 902

Author(s):

Sungwon Lee ◽

Muhammad Azfar Azfar Yaqub ◽

Dongkyun Kim

Keyword(s):

Internet Of Things ◽

Duty Cycle ◽

Smart City ◽

Mac Protocol ◽

Smart Cities ◽

Iot Applications ◽

Simulation Results ◽

Iot Devices ◽

The Impact

The principle of Smart Cities is the interconnection of services, based on a network of Internet of Things (IoT) devices. As the number of IoT devices continue to grow, the demand to organize and maintain the IoT applications is increased. Therefore, the solutions for smart city should have the ability to efficiently utilize the resources and their associated challenges. Neighbor aware solutions can enhance the capabilities of the smart city. In this article, we briefly overview the neighbor aware solutions and challenges in smart cities. We then categorize the neighbor aware solutions and discuss the possibilities using the collaboration among neighbors to extend the lifetime of IoT devices. We also propose a new duty cycle MAC protocol with assistance from the neighbors to extend the lifetime of the nodes. Simulation results further coagulate the impact of neighbor assistance on the performance of IoT devices in smart cities.

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Virtualizing AI at the Distributed Edge Towards Intelligent IoT Applications

Journal of Sensor and Actuator Networks ◽

10.3390/jsan10010013 ◽

2021 ◽

Vol 10 (1) ◽

pp. 13

Author(s):

Claudia Campolo ◽

Giacomo Genovese ◽

Antonio Iera ◽

Antonella Molinaro

Keyword(s):

Resource Constraints ◽

Smart Cities ◽

Traditional Approach ◽

Low Cost ◽

Iot Applications ◽

Software And Hardware ◽

Iot Devices ◽

Consumer Devices ◽

Hardware Platforms ◽

Smart Factories

Several Internet of Things (IoT) applications are booming which rely on advanced artificial intelligence (AI) and, in particular, machine learning (ML) algorithms to assist the users and make decisions on their behalf in a large variety of contexts, such as smart homes, smart cities, smart factories. Although the traditional approach is to deploy such compute-intensive algorithms into the centralized cloud, the recent proliferation of low-cost, AI-powered microcontrollers and consumer devices paves the way for having the intelligence pervasively spread along the cloud-to-things continuum. The take off of such a promising vision may be hurdled by the resource constraints of IoT devices and by the heterogeneity of (mostly proprietary) AI-embedded software and hardware platforms. In this paper, we propose a solution for the AI distributed deployment at the deep edge, which lays its foundation in the IoT virtualization concept. We design a virtualization layer hosted at the network edge that is in charge of the semantic description of AI-embedded IoT devices, and, hence, it can expose as well as augment their cognitive capabilities in order to feed intelligent IoT applications. The proposal has been mainly devised with the twofold aim of (i) relieving the pressure on constrained devices that are solicited by multiple parties interested in accessing their generated data and inference, and (ii) and targeting interoperability among AI-powered platforms. A Proof-of-Concept (PoC) is provided to showcase the viability and advantages of the proposed solution.

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Implementation analysis of IoT-based offloading frameworks on cloud/edge computing for sensor generated big data

Complex & Intelligent Systems ◽

10.1007/s40747-021-00434-6 ◽

2021 ◽

Author(s):

Karan Bajaj ◽

Bhisham Sharma ◽

Raman Singh

Keyword(s):

High Speed ◽

Smart Cities ◽

Fog Computing ◽

Edge Computing ◽

Computation Offloading ◽

Performance Parameters ◽

Iot Applications ◽

Time Sensitivity ◽

Implementation Analysis ◽

Increasing Demand

AbstractThe Internet of Things (IoT) applications and services are increasingly becoming a part of daily life; from smart homes to smart cities, industry, agriculture, it is penetrating practically in every domain. Data collected over the IoT applications, mostly through the sensors connected over the devices, and with the increasing demand, it is not possible to process all the data on the devices itself. The data collected by the device sensors are in vast amount and require high-speed computation and processing, which demand advanced resources. Various applications and services that are crucial require meeting multiple performance parameters like time-sensitivity and energy efficiency, computation offloading framework comes into play to meet these performance parameters and extreme computation requirements. Computation or data offloading tasks to nearby devices or the fog or cloud structure can aid in achieving the resource requirements of IoT applications. In this paper, the role of context or situation to perform the offloading is studied and drawn to a conclusion, that to meet the performance requirements of IoT enabled services, context-based offloading can play a crucial role. Some of the existing frameworks EMCO, MobiCOP-IoT, Autonomic Management Framework, CSOS, Fog Computing Framework, based on their novelty and optimum performance are taken for implementation analysis and compared with the MAUI, AnyRun Computing (ARC), AutoScaler, Edge computing and Context-Sensitive Model for Offloading System (CoSMOS) frameworks. Based on the study of drawn results and limitations of the existing frameworks, future directions under offloading scenarios are discussed.

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State-of-the-Art Software-Based Remote Attestation: Opportunities and Open Issues for Internet of Things

Sensors ◽

10.3390/s21051598 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1598

Author(s):

Sigurd Frej Joel Jørgensen Ankergård ◽

Edlira Dushku ◽

Nicola Dragoni

Keyword(s):

Internet Of Things ◽

Smart Cities ◽

Cyber Attacks ◽

Resource Constrained ◽

Remote Attestation ◽

Comprehensive Overview ◽

Research Issues ◽

Advantages And Disadvantages ◽

Iot Devices ◽

Specialized Hardware

The Internet of Things (IoT) ecosystem comprises billions of heterogeneous Internet-connected devices which are revolutionizing many domains, such as healthcare, transportation, smart cities, to mention only a few. Along with the unprecedented new opportunities, the IoT revolution is creating an enormous attack surface for potential sophisticated cyber attacks. In this context, Remote Attestation (RA) has gained wide interest as an important security technique to remotely detect adversarial presence and assure the legitimate state of an IoT device. While many RA approaches proposed in the literature make different assumptions regarding the architecture of IoT devices and adversary capabilities, most typical RA schemes rely on minimal Root of Trust by leveraging hardware that guarantees code and memory isolation. However, the presence of a specialized hardware is not always a realistic assumption, for instance, in the context of legacy IoT devices and resource-constrained IoT devices. In this paper, we survey and analyze existing software-based RA schemes (i.e., RA schemes not relying on specialized hardware components) through the lens of IoT. In particular, we provide a comprehensive overview of their design characteristics and security capabilities, analyzing their advantages and disadvantages. Finally, we discuss the opportunities that these RA schemes bring in attesting legacy and resource-constrained IoT devices, along with open research issues.

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Recent Progress in the Energy Harvesting Technology—From Self-Powered Sensors to Self-Sustained IoT, and New Applications

Nanomaterials ◽

10.3390/nano11112975 ◽

2021 ◽

Vol 11 (11) ◽

pp. 2975

Author(s):

Long Liu ◽

Xinge Guo ◽

Weixin Liu ◽

Chengkuo Lee

Keyword(s):

Energy Harvesting ◽

Gas Sensing ◽

Smart Cities ◽

Scale Up ◽

Smart Homes ◽

Energy Harvesters ◽

Iot Applications ◽

Fast Development ◽

Self Powered ◽

New Applications

With the fast development of energy harvesting technology, micro-nano or scale-up energy harvesters have been proposed to allow sensors or internet of things (IoT) applications with self-powered or self-sustained capabilities. Facilitation within smart homes, manipulators in industries and monitoring systems in natural settings are all moving toward intellectually adaptable and energy-saving advances by converting distributed energies across diverse situations. The updated developments of major applications powered by improved energy harvesters are highlighted in this review. To begin, we study the evolution of energy harvesting technologies from fundamentals to various materials. Secondly, self-powered sensors and self-sustained IoT applications are discussed regarding current strategies for energy harvesting and sensing. Third, subdivided classifications investigate typical and new applications for smart homes, gas sensing, human monitoring, robotics, transportation, blue energy, aircraft, and aerospace. Lastly, the prospects of smart cities in the 5G era are discussed and summarized, along with research and application directions that have emerged.

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