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

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6441 ◽  
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.

Examining IoT's Applications Using Cloud Services

2018 ◽  
pp. 147-163 ◽  
Author(s):  
Saravanan K ◽  
P. Srinivasan
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Distributed Computing ◽  
Knowledge Sharing ◽  
Effective Communication ◽  
Cloud Services ◽  
On Demand ◽  
Computing Paradigm ◽  
Iot Devices ◽  
And Storage

Cloud IoT has evolved from the convergence of Cloud computing with Internet of Things (IoT). The networked devices in the IoT world grow exponentially in the distributed computing paradigm and thus require the power of the Cloud to access and share computing and storage for these devices. Cloud offers scalable on-demand services to the IoT devices for effective communication and knowledge sharing. It alleviates the computational load of IoT, which makes the devices smarter. This chapter explores the different IoT services offered by the Cloud as well as application domains that are benefited by the Cloud IoT. The challenges on offloading the IoT computation into the Cloud are also discussed.

Security Assertion of IoT Devices Using Cloud of Things Perception

2019 ◽  
Vol 11 (4) ◽  
pp. 17-31
Author(s):  
Mamata Rath ◽  
Bibudhendu Pati
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Communication Systems ◽  
Future Internet ◽  
Computing Systems ◽  
Iot Security ◽  
Security Assurance ◽  
Iot Applications ◽  
The Future ◽  
Iot Devices

Adoption of Internet of Things (IoT) and Cloud of Things (CoT) in the current developing technology era are expected to be more and more invasive, making them important mechanism of the future Internet-based communication systems. Cloud of Things and Internet of Things (IoT) are two emerging as well as diversified advanced domains that are diversified in current technological scenario. Paradigm where Cloud and IoT are merged together is foreseen as disruptive and as an enabler of a large number of application scenarios. Due to the adoption of the Cloud and IoT paradigm a number of applications are gaining important technical attention. In the future, it is going to be more complicated a setup to handle security in technology. Information till now will severely get changed and it will be very tough to keep up with varying technology. Organisations will have to repeatedly switch over to new skill-based technology with respect to higher expenditure. Latest tools, methods and enough expertise are highly essential to control threats and vulnerability to computing systems. Keeping in view the integration of Cloud computing and IoT in the new domain of Cloud of things, the said article provides an up-to-date eminence of Cloud-based IoT applications and Cloud of Things with a focus on their security and application-oriented challenges. These challenges are then synthesized in detail to present a technical survey on various issues related to IoT security, concerns, adopted mechanisms and their positive security assurance using Cloud of Things.

scholarly journals Automatic Failure Recovery for Container-Based IoT Edge Applications

Electronics ◽  
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.

Autonomic Trust Management in Cloud-Based and Highly Dynamic IOT Applications

2016 ◽  
Vol 1 (5) ◽  
pp. 26-32
Author(s):  
Suneth Namal ◽  
Hasindu Gamaarachchi ◽  
Gyu Myoung Lee ◽  
Tai-Won Um
Keyword(s):  
Cloud Computing ◽  
Feedback Control ◽  
Internet Of Things ◽  
Life Style ◽  
Trust Management ◽  
Control Loop ◽  
Management Framework ◽  
Iot Applications ◽  
Iot Devices ◽  
The Way

In this paper, we propose an autonomic trust management framework for cloud based and highly dynamic Internet of Things (IoT) applications and services. IoT is creating a world where physical objects are seamlessly integrated in order to provide advanced and intelligent services for humanbeings in their day-to-day life style. Therefore, trust on IoT devices plays an important role in IoT based services and applications. Cloud computing has been changing the way how provides are looking into these issues. Many studies have proposed different techniques to address trust management although non of them addresses autonomic trust management in cloud based highly dynamic IoT systems. To our understanding, IoT cloud ecosystems help to solve many of these issues while enhancing robustness and scalability. On this basis, we came up with an autonomic trust management framework based on MAPE-K feedback control loop to evaluate the level of trust. Finally, we presents the results that verify the effectiveness of this framework.

scholarly journals Hierarchical Multi-Blockchain Architecture for Scalable Internet of Things Environment

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1050 ◽  
Author(s):  
Yustus Eko Oktian ◽  
Sang-Gon Lee ◽  
Hoon Jae Lee
Keyword(s):  
Internet Of Things ◽  
High Throughput ◽  
Byzantine Fault Tolerance ◽  
The Core ◽  
Iot Applications ◽  
Internet Of Things Environment ◽  
Second Tier ◽  
Iot Devices ◽  
And Storage ◽  
Scalable Internet

Many researchers challenge the possibility of using blockchain and smart contracts to disrupt the Internet of Things (IoT) architecture because of their security and decentralization guarantees. However, the state-of-the-art blockchain architecture is not scalable enough to satisfy the requirements of massive data traffics in the IoT environment. The main reason for this issue is one needs to choose the consensus trade-off between either coping with a high throughput or a high number of nodes. Consequently, this issue prevents the applicability of blockchain for IoT use cases. In this paper, we propose a scalable two-tiered hierarchical blockchain architecture for IoT. The first tier is a Core Engine, which is based on a Practical Byzantine Fault Tolerance (PBFT) consensus to cope with a high throughput, that supervises the underlying subordinate engines (sub-engines) as its second tier. This second tier comprises of the Payment, Compute, and Storage Engine, respectively. We can deploy multiple instances of these sub-engines as many as we need and as local as possible near to the IoT domains, where IoT devices reside, to cope with a high number of nodes. Furthermore, to further extend the scalability of the proposed architecture, we also provide additional scalability features on the Core Engine such as request aggregation, request prioritization, as well as sub-engine parallelism. We implement all of our engines and expose them to IoT applications through the Engine APIs. With these APIs, developers can build and run IoT applications in our architecture. Our evaluation results show that our proposed features on the Core Engine can indeed enhance the overall performance of our architecture. Moreover, based on our proof-of-concept IoT car rental application, we also show that the interoperability between sub-engines through the Core Engine is possible, even when the particular sub-engine is under sub-engine parallelism.

scholarly journals The embedded framework for securing the Internet of Things

2021 ◽  
Vol 9 (2) ◽  
Author(s):  
Feroz Khan A.B ◽  
◽  
Anandharaj G ◽  
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Security Protocols ◽  
Smart Devices ◽  
The Internet ◽  
Home Automation ◽  
Iot Applications ◽  
Iot Devices ◽  
The Internet Of Things ◽  
Entire Network

The smart devices connected on the internet turn to be the internet of things, which connect other objects or devices through unique identifiers with the capability of transferring and receiving the information over the internet. There are numerous applications in different areas such as healthcare, home automation, transportation, military, agriculture, and still so many sectors that incorporate cutting-edge technologies of communication, networking, cloud computing, sensing, and actuation. With this huge increase in the number of connected devices, a strong security mechanism is required to protect the IoT devices. Hence, it is required to focus on the challenges and issues of IoT enabled applications to safeguard the entire network from the outside invasion. This paper discusses some of the challenges in building IoT applications, a detailed study of the existing security protocols, and its issues, and the potential of the IoT.

scholarly journals 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

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.

scholarly journals Fog Computing and the Internet of Things: A Review

2018 ◽  
Vol 2 (2) ◽  
pp. 10 ◽  
Author(s):  
Hany Atlam ◽  
Robert Walters ◽  
Gary Wills
Keyword(s):  
Internet Of Things ◽  
Fog Computing ◽  
Future Research ◽  
Implementation Challenges ◽  
Network Failure ◽  
Iot Applications ◽  
Computing Paradigm ◽  
Future Research Directions ◽  
Iot Devices ◽  
Processing And Storage

With the rapid growth of Internet of Things (IoT) applications, the classic centralized cloud computing paradigm faces several challenges such as high latency, low capacity and network failure. To address these challenges, fog computing brings the cloud closer to IoT devices. The fog provides IoT data processing and storage locally at IoT devices instead of sending them to the cloud. In contrast to the cloud, the fog provides services with faster response and greater quality. Therefore, fog computing may be considered the best choice to enable the IoT to provide efficient and secure services for many IoT users. This paper presents the state-of-the-art of fog computing and its integration with the IoT by highlighting the benefits and implementation challenges. This review will also focus on the architecture of the fog and emerging IoT applications that will be improved by using the fog model. Finally, open issues and future research directions regarding fog computing and the IoT are discussed.

scholarly journals A novel approach for IoT tasks offloading in edge-cloud environments

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jaber Almutairi ◽  
Mohammad Aldossary
Keyword(s):  
Service Time ◽  
Edge Computing ◽  
Cloud System ◽  
Novel Approach ◽  
Delay Sensitivity ◽  
Cloud Environments ◽  
Application Characteristics ◽  
Iot Devices ◽  
Computational Resources ◽  
And Storage

AbstractRecently, the number of Internet of Things (IoT) devices connected to the Internet has increased dramatically as well as the data produced by these devices. This would require offloading IoT tasks to release heavy computation and storage to the resource-rich nodes such as Edge Computing and Cloud Computing. Although Edge Computing is a promising enabler for latency-sensitive related issues, its deployment produces new challenges. Besides, different service architectures and offloading strategies have a different impact on the service time performance of IoT applications. Therefore, this paper presents a novel approach for task offloading in an Edge-Cloud system in order to minimize the overall service time for latency-sensitive applications. This approach adopts fuzzy logic algorithms, considering application characteristics (e.g., CPU demand, network demand and delay sensitivity) as well as resource utilization and resource heterogeneity. A number of simulation experiments are conducted to evaluate the proposed approach with other related approaches, where it was found to improve the overall service time for latency-sensitive applications and utilize the edge-cloud resources effectively. Also, the results show that different offloading decisions within the Edge-Cloud system can lead to various service time due to the computational resources and communications types.

scholarly journals A Survey on Mobile Edge Computing: Focusing on Service Adoption and Provision

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Kai Peng ◽  
Victor C. M. Leung ◽  
Xiaolong Xu ◽  
Lixin Zheng ◽  
Jiabin Wang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Mobile Networks ◽  
Edge Computing ◽  
Computation Offloading ◽  
Battery Life ◽  
Mobile Edge Computing ◽  
Service Adoption ◽  
Comprehensive Survey ◽  
And Storage ◽  
Execution Delay

Mobile cloud computing (MCC) integrates cloud computing (CC) into mobile networks, prolonging the battery life of the mobile users (MUs). However, this mode may cause significant execution delay. To address the delay issue, a new mode known as mobile edge computing (MEC) has been proposed. MEC provides computing and storage service for the edge of network, which enables MUs to execute applications efficiently and meet the delay requirements. In this paper, we present a comprehensive survey of the MEC research from the perspective of service adoption and provision. We first describe the overview of MEC, including the definition, architecture, and service of MEC. After that we review the existing MUs-oriented service adoption of MEC, i.e., offloading. More specifically, the study on offloading is divided into two key taxonomies: computation offloading and data offloading. In addition, each of them is further divided into single MU offloading scheme and multi-MU offloading scheme. Then we survey edge server- (ES-) oriented service provision, including technical indicators, ES placement, and resource allocation. In addition, other issues like applications on MEC and open issues are investigated. Finally, we conclude the paper.

Sign in / Sign up

Export Citation Format

Share Document