How Fog Computing Can Support Latency/Reliability‐sensitive IoT Applications: An Overview and a Taxonomy of State‐of‐the‐art Solutions

2019 ◽

Vol 15 (2) ◽

pp. 80-96 ◽

Cited By ~ 2

Author(s):

Mohammad Irfan Bala ◽

Mohammad Ahsan Chishti

Keyword(s):

Design Methodology ◽

State Of The Art ◽

Fog Computing ◽

Full Potential ◽

Content Type ◽

Iot Applications ◽

Computing Model ◽

Current State ◽

Survey Papers ◽

Challenges And Opportunities

Purpose Fog computing is a new field of research and has emerged as a complement to the cloud which can mitigate the problems inherent to the cloud computing model such as unreliable latency, bandwidth constraints, security and mobility. This paper aims to provide detailed survey in the field of fog computing covering the current state-of-the-art in fog computing. Design/methodology/approach Cloud was developed for IT and not for Internet of Things (IoT); as a result, cloud is unable to meet the computing, storage, control and networking demands of the IoT applications. Fog is a companion for the cloud and aims to extend the cloud capabilities to the edge of the network. Findings Lack of survey papers in the area of fog computing was an important motivational factor for writing this paper. This paper highlights the capabilities of the fog computing and where it fits in between IoT and cloud. This paper has also presented architecture of the fog computing model and its characteristics. Finally, the challenges in the field of fog computing have been discussed in detail which need to be overcome to realize its full potential. Originality/value This paper presents the current state-of-the-art in fog computing. Lack of such papers increases the importance of this paper. It also includes challenges and opportunities in the fog computing and various possible solutions to overcome those challenges.

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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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Ambient Intelligence Based on IoT for Assisting People with Alzheimer’s Disease Through Context Histories

Electronics ◽

10.3390/electronics10111260 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1260

Author(s):

Savanna Denega Machado ◽

João Elison da Rosa Tavares ◽

Márcio Garcia Martins ◽

Jorge Luis Victória Barbosa ◽

Gabriel Villarrubia González ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

State Of The Art ◽

Physiological Data ◽

Data Sets ◽

Scientific Contribution ◽

Daily Lives ◽

Iot Applications ◽

Methodological Aspects ◽

Dangerous Behaviors

New Internet of Things (IoT) applications are enabling the development of projects that help with monitoring people with different diseases in their daily lives. Alzheimer’s is a disease that affects neurological functions and needs support to maintain maximum independence and security of patients during this stage of life, as the cure and reversal of symptoms have not yet been discovered. The IoT-based monitoring system provides the caregivers’ support in monitoring people with Alzheimer’s disease (AD). This paper presents an ontology-based computational model that receives physiological data from external IoT applications, allowing identification of potentially dangerous behaviors for patients with AD. The main scientific contribution of this work is the specification of a model focusing on Alzheimer’s disease using the analysis of context histories and context prediction, which, considering the state of the art, is the only one that uses analysis of context histories to perform predictions. In this research, we also propose a simulator to generate activities of the daily life of patients, allowing the creation of data sets. These data sets were used to evaluate the contributions of the model and were generated according to the standardization of the ontology. The simulator generated 1026 scenarios applied to guide the predictions, which achieved average accurary of 97.44%. The experiments also allowed the learning of 20 relevant lessons on technological, medical, and methodological aspects that are recorded in this article.

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A cloud-fog computing system for classification and scheduling the information-centric IoT applications

International Journal of Communication Networks and Distributed Systems ◽

10.1504/ijcnds.2021.119208 ◽

2021 ◽

Vol 27 (4) ◽

pp. 388

Author(s):

K. Jairam Naik

Keyword(s):

Fog Computing ◽

Computing System ◽

Iot Applications

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Analysis, Deployment and Integration of Platforms for Fog Computing

Journal of Computer Science and Technology ◽

10.24215/16666038.20.e12 ◽

2020 ◽

Vol 20 (2) ◽

pp. e12

Author(s):

Joaquín De Antueno ◽

Santiago Medina ◽

Laura De Giusti ◽

Armando De Giusti

Keyword(s):

Data Management ◽

Sensor Network ◽

Experimental Work ◽

Response Times ◽

Fog Computing ◽

Data Capture ◽

Local Data ◽

Iot Applications ◽

Flow Of Information ◽

Large Flow

In IoT applications, data capture in a sensor network can generate a large flow of information between the nodes and the cloud, affecting response times and device complexity but, above all, increasing costs. Fog computing refers to the use of pre-processing tools to improve local data management and communication with the cloud. This work presents an analysis of the features that platforms implementing fog computing solutions should have. Additionally, an experimental work integrating two specific platforms used for controlling devices in a sensor network, processing the generated data, and communicating with the cloud is presented.

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Towards the Protection and Security in Fog Computing for Industrial Internet of Things

Advances in Computer and Electrical Engineering - Innovations in the Industrial Internet of Things (IIoT) and Smart Factory ◽

10.4018/978-1-7998-3375-8.ch002 ◽

2021 ◽

pp. 17-32

Author(s):

G. Rama Subba Reddy ◽

K. Rangaswamy ◽

Malla Sudhakara ◽

Pole Anjaiah ◽

K. Reddy Madhavi

Keyword(s):

Internet Of Things ◽

Distributed Computing ◽

Fog Computing ◽

Security And Privacy ◽

Safety Measures ◽

Iot Applications ◽

Industrial Internet ◽

Sensor Devices ◽

Key Enabling Technologies ◽

Privacy Issues

Internet of things (IoT) has given a promising chance to construct amazing industrial frameworks and applications by utilizing wireless and sensor devices. To support IIoT benefits efficiently, fog computing is typically considered as one of the potential solutions. Be that as it may, IIoT services still experience issues such as high-latency and unreliable connections between cloud and terminals of IIoT. In addition to this, numerous security and privacy issues are raised and affect the users of the distributed computing environment. With an end goal to understand the improvement of IoT in industries, this chapter presents the current research of IoT along with the key enabling technologies. Further, the architecture and features of fog computing towards the fog-assisted IoT applications are presented. In addition to this, security and protection threats along with safety measures towards the IIoT applications are discussed.

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