Fog Computing Projects

Fog Computing Projects are trending now a days among scholars we have curated more than 5000+ fog projects tailored to scholars needs. There are several research project ideas that are progressing in the domain of fog computing.  Starting from conceptual studies to realistic deployments, we suggest 25 research project ideas that utilize fog computing efficiently:

  1. Dynamic Resource Allocation in Fog Computing
  • In order to enhance performance and decrease latency, aim to investigate methods for dynamically assigning sources in fog computing platforms.
  1. Energy-efficient Task Scheduling
  • Concentrating on decreasing energy absorption when sustaining effectiveness levels, it is appreciable to construct and examine task scheduling methods.
  1. Fog-based IoT Security Framework
  • By manipulating fog computing, formulate a safety model for IoT devices to improve data morality and confidentiality.
  1. Real-time Data Analytics for Smart Cities
  • To enhance city facilities such as pollution tracking and congestion management, aim to deploy a framework for actual-time data processing and analytics in smart cities by utilizing fog nodes.
  1. Fog Computing in Healthcare Monitoring Systems
  • Specifically, for actual-time data analysis and notifications for patient care, construct a healthcare monitoring framework that employs fog computing.
  1. Edge AI for Autonomous Vehicles
  • To assist automated driving frameworks with limited latency, it is approachable to develop an environment for processing AI methods at the edge of the network.
  1. Fog-assisted Robotics for Industry 4.0
  • A fog computing infrastructure has to be formulated in such a manner that has the capability to improve interaction and cooperation of robotics in the production platforms.
  1. Blockchain and Fog Computing for Supply Chain Management
  • To construct a safe, effective supply chain management model, focus on incorporating blockchain with fog computing that is good enough for actual-time monitoring and authentication.
  1. Disaster Response and Management Using Fog Computing
  • For rapid data processing and interaction in cases of urgency, it is appreciable to apply a disaster management model that utilizes fog computing.
  1. Fog-enhanced Augmented Reality (AR) Applications

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  1. QoS-aware Service Placement in Fog Networks

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  1. Load Balancing in Fog Computing Environments

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  1. Fog Computing for Video Streaming Services

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  1. Collaborative Edge and Fog Computing for IoT

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  1. Fog Computing in Agriculture for Precision Farming

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  1. Predictive Maintenance in Industrial IoT Using Fog Computing

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  1. Mobile Edge Computing (MEC) for 5G Networks

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  1. Privacy-preserving Data Analytics in Fog Computing

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  1. Fog Computing for Smart Grids

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  1. Content Delivery Networks (CDNs) Enhanced by Fog Computing

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  1. Fog Computing for Multi-access Edge Computing (MEC)

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  1. Distributed Data Storage Solutions in Fog Computing

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  1. Network Function Virtualization (NFV) with Fog Computing

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  1. Fog Computing for Environmental Monitoring

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  1. Serverless Computing Models in Fog Environments

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Based on certain necessities, these projects can be altered or prolonged to investigate multidisciplinary techniques, thereby creating in such a manner that is appropriate for thesis topics, educational study, or realistic deployments in business-specific applications.

Can I use iFogSim to simulate fog scenarios?

Yes, to simulate a fog setting, you can employ iFogSim. Generally, iFogSim is considered as a prominent simulator and is mainly formulated for designing and simulating fog computing platforms. In fog computing architecture, it allows developers and researchers to assess different policies for resource management, scheduling, and application employment. ClousSim is a prevalent cloud computing simulation toolkit, which is expanded by iFogSim in order to integrate the features and limitations certain to fog computing, like heterogeneity, integrity, and geo-distribution.

Usually, you should adhere to these procedures to simulate a fog setting with iFogSim:

  1. Define Fog Devices

It is advisable to begin by explaining the fog devices in your settings such as their hardware features like memory, software, CPU, power absorption, and network connectivity. Typically, in iFogSim, involving fog nodes and edge devices, the fog devices range from small IoT devices to cloud data centers.

  1. Create Applications

The applications that will execute on your fog architecture have to be described. iFogSim based application consists of modules. It is appreciable to mention the logic and necessities of these modules such as their processing power requirements and data exchange trends.

  1. Design the Network Topology

To depict the physical and logical correlations among your fog devices, aim to configure the network topology. In order to imitate actual-world implementation settings, like IoT devices linked to edge nodes, that in turn are linked to local fog nodes and cloud data centers, this step establishes parent-child relationships between devices.

  1. Implement Policies

The resource management and scheduling strategies should be deployed. Mainly, for task scheduling, resource allotment, and application positioning, iFogSim permits you to research various policies, thereby facilitating you to evaluate their influence on performance metrics like energy absorption, expense, and latency.

  1. Run the Simulation

You can execute the simulation after establishing your fog devices, applications, and strategies. Based on your configurations and strategies, iFogSim will simulate the execution of your applications on the specified fog architecture.

  1. Analyze Results

Finally, to interpret the activities of your applications and performance of your fog computing under various situations, aim to investigate the outcomes of simulation. For assessment, iFogSim offers different parameters like latency, network utilization, and energy absorption.

Example Code Snippet

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// Create fog devices

 FogDevice cloud = createFogDevice(“cloud”, 40000, 40000, 10000, 10000, 0, 0.01, 16 * 103, 16 * 83.25);

 FogDevice proxy = createFogDevice(“proxy-server”, 8000, 8000, 10000, 10000, 1, 0.0, 107.339, 83.4333);

// Add more devices…

// Create an application

 Application application = createApplication(appModel, appId);

// Define the network topology



// Define more connections…

// Run the simulation

CloudSim.init(1, Calendar.getInstance(), false);


// Process results…           

An extensive summary of the procedures that are included employing iFogSim are offered in this instance. Refer to the iFogSim documentation and accessible source code on its GitHub directory, for elaborated guidelines such as how to specify applications, devices, and certain configurations.

Fog Computing Project Topics

Fog Computing Project Topics & Ideas

Close to the realm of edge computing, the ethereal fog computing initiatives show a profound influence on the advancements of the cloud. With an unwavering dedication, their paramount goal is to elevate the performance of the system through expeditious accessibility to data. Moreover, they diligently prioritize the noble causes of compliance and safeguarding the sanctity of data. has precisely curated an extensive catalogue of nearly twenty ground-breaking ideas, each meticulously executed with the utmost precision. We do employ the finest simulations, tailored precisely to align with your visionary concept.

  1. Optimal deploying IoT services on the fog computing: A metaheuristic-based multi-objective approach
  2. A scalable simulator for cloud, fog and edge computing platforms with mobility support
  3. BSKM-FC: Blockchain-based secured key management in a fog computing environment
  4. A metric focused performance assessment of fog computing environments: A critical review
  5. LAMAS: Lightweight anonymous mutual authentication scheme for securing fog computing environments
  6. Multi-objective fuzzy approach to scheduling and offloading workflow tasks in Fog–Cloud computing
  7. PFogSim: A simulator for evaluation of mobile and hierarchical fog computing
  8. Extensibility-aware Fog Computing Platform configuration for mixed-criticality applications
  9. Industrial quality healthcare services using Internet of Things and fog computing approach
  10. Security in fog computing: A systematic review on issues, challenges and solutions
  11. Intrusion detection using optimized ensemble classification in fog computing paradigm
  12. Spectral graph theory-based virtual network embedding for vehicular fog computing: A deep reinforcement learning architecture
  13. An efficient reusable attribute-based signature scheme for mobile services with multi access policies in fog computing
  14. Genetic-based optimization in fog computing: Current trends and research opportunities
  15. Node cooperation for workload offloading in a fog computing network via multi-objective optimization
  16. An Efficient Trust Management using Feedback Credibility Evaluation Method in Fog Computing
  17. Analytical model for task offloading in a fog computing system with batch-size-dependent service
  18. Fuzzy-assisted machine learning framework for the fog-computing system in remote healthcare monitoring
  19. Optimization of IoT-Fog Network Path and fault Tolerance in Fog Computing based Environment
  20. Distributed application execution in fog computing: A taxonomy, challenges and future directions

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