A metaheuristic‐based data replica placement approach for data‐intensive IoT applications in the fog computing environment

2021 ◽  
Author(s):  
Jaber Taghizadeh ◽  
Mostafa Ghobaei‐Arani ◽  
Ali Shahidinejad
Keyword(s):  
Fog Computing ◽  
Replica Placement ◽  
Computing Environment ◽  
Data Intensive ◽  
Iot Applications

Quantumized approach of load scheduling in fog computing environment for IoT applications

Computing ◽  
2020 ◽  
Vol 102 (5) ◽  
pp. 1097-1115 ◽  
Author(s):  
Munish Bhatia ◽  
Sandeep K. Sood ◽  
Simranpreet Kaur
Keyword(s):  
Fog Computing ◽  
Computing Environment ◽  
Load Scheduling ◽  
Iot Applications

Resource Provisioning Framework for IoT Applications in Fog Computing Environment

2018 ◽  
Author(s):  
G Rakshith ◽  
M V Rahul ◽  
G S Sanjay ◽  
B V Natesha ◽  
G Ram Mohana Reddy
Keyword(s):  
Fog Computing ◽  
Resource Provisioning ◽  
Computing Environment ◽  
Iot Applications

A cost-efficient auto-scaling mechanism for IoT applications in fog computing environment: a deep learning-based approach

2021 ◽  
Author(s):  
Masoumeh Etemadi ◽  
Mostafa Ghobaei-Arani ◽  
Ali Shahidinejad
Keyword(s):  
Deep Learning ◽  
Fog Computing ◽  
Computing Environment ◽  
Iot Applications ◽  
Cost Efficient ◽  
Auto Scaling

A Volunteer Supported Fog Computing Environment for Delay-Sensitive IoT Applications

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Babar Ali ◽  
Muhammad Adeel Pasha ◽  
Saif ul Islam ◽  
Houbing Song ◽  
Rajkumar Buyya
Keyword(s):  
Fog Computing ◽  
Computing Environment ◽  
Iot Applications ◽  
Delay Sensitive

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

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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