Fog Computing Research Topics

Fog computing is a decentralized computing framework and has various research areas. Get your Survey paper writing on all areas of Fog Computing Research Topics are skilled experts as we have undertaken Fog Computing projects for past 18+ years. Relevant to this technology, we suggest several Fog Computing Research Topics that are interesting as well as effective for the investigation process:

  1. Resource Management and Scheduling
  • To enhance performance and effectiveness while reducing usage of energy, consider the better resource allotment and scheduling in the platforms of fog computing.
  1. Security and Privacy in Fog Environments
  • For fog computing frameworks, create powerful privacy-preserving approaches and safety protocols that must be effective as well as scalable.
  1. Data Analytics and Edge Intelligence
  • In order to promote rapid decision-making processes, apply and enhance machine learning methods and actual-time data analytics at the network edge.
  1. Fog and Cloud Integration
  • For the purpose of improving adaptability, accessibility of resources, and scalability, explore simple integration policies among cloud services and fog computing layers.
  1. Energy-efficient Fog Computing
  • With the aim of minimizing the energy footprint of fog computing nodes, outline policies along with energy harvesting techniques and eco-friendly computing mechanisms.
  1. Fog Computing for IoT Applications
  • By considering the possibilities and limitations in every field, investigate the fog computing application in different IoT settings like framing, industrial IoT (IIoT), healthcare, and smart cities.
  1. Network Function Virtualization (NFV) and Software-Defined Networking (SDN) in Fog
  • In the platforms of fog computing, enhance network handling, function placement, and adaptability through the use of NFV and SDN.
  1. Fog-based Autonomous Systems
  • By concentrating on actual-time data processing and operations, create protocols and frameworks with the intention of facilitating automatic systems through fog computing, and some instances of these systems are self-driving vehicles and drones.
  1. Service Placement and Orchestration
  • To assure more credibility, effective resource utilization, and less-latency, consider tactics, specifically for service deployment and arrangement in fog platforms.
  1. Fog Computing Architectures for 5G Networks

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  1. Cross-Layer Optimization Techniques

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  1. Quality of Service (QoS) and Quality of Experience (QoE) in Fog Computing

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  1. Fault Tolerance and Resilience in Fog Systems

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  1. Scalable and Flexible Fog Computing Frameworks

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  1. Interoperability and Standards in Fog Computing

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  1. Distributed Consensus and Blockchain in Fog Computing

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

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

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  1. Fog Computing for Environmental Monitoring

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  1. Serverless Computing in Fog Environments

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How to make topology using an iFogSim GUI without coding?

Specifically, iFogSim is a simulation toolkit that is proficient in modeling and assessing resource handling approaches in the platforms of fog computing. It was created at the University of Melbourne by the Cloud Computing and Distributed Systems (CLOUDS) Laboratory. It is particularly modeled to utilize in a programmatic manner with Java.

In iFogSim, the process of developing topologies includes the java code for describing the nodes such as actuators, fog devices, and sensors and their features like bandwidth, processing power, and latency, including their connections (for instance: parent-child relationships).

To create topologies with no or less coding, several techniques are there, and some of them are listed below to examine:

  1. Visual Programming Tools:

There are numerous tools that are capable of enabling the approach of visual programming or the development of flowcharts which can be converted into code. Tools such as Blockly or Node-RED can be employed for modeling a topology in a visual manner and then producing Java code which aligns with that model, even though these tools are not exactly incorporated with iFogSim. To connect the visual tool with iFogSim API, this will need a custom application.

  1. Custom GUI Development:

Creating a custom GUI application is another significant technique which produces iFogSim topology code through graphical interface on the basis of user inputs. Through this application, users are enabled to specify devices, their relationships, and features in a visual way, and then it will generate the relatable java code for iFogSim. For the users who are not familiar with programming, it can be a robust tool and also needs major proper development endeavors.

  1. Use of Third-party Tools with iFogSim Extensions:

Various tools or extensions might be developed by some developers and researchers and that could be combined with iFogSim, especially for particular assignments. There is a possibility to discover extensions or tools by exploring GitHub, academic publications, or group meetings relevant to iFogSim and fog computing, and that can offer a GUI for the development of topology.

  1. Educational Resources:

For the purpose of facilitating the coding procedure, seek instances, tutorials, and reports based on iFogSim.  Even though this approach does not remove the coding requirement, it can help to carry out the procedure in an easier way for the people who have no expertise in iFogSim or unskilled in programming.

  1. Collaboration:

Generally, it is approachable to associate with computer science experts, researchers, or students who can provide support in terms of the coding factors of your assignment and who have proficient skills in programming.

Going Forward

In the upcoming era, there is a potential to present GUI-related topology development by third-party extensions or the novel versions of iFogSim due to the emerging pattern of group contributions and software tools. It is easier to be aware of such creations while focusing on the group Meetings, Official Ifogsim Github Repository, And Related Academic Conferences.

Fog Computing Research Proposal Topics

Fog Computing Research Ideas

Presently, students are experiencing stress and self-doubt regarding their Fog Computing Research Ideas and projects. Our innovative approaches aim to alleviate these concerns by providing the expertise of skilled professionals to develop a flawless simulation for your concept. We are dedicated to ensuring your satisfaction and comfort throughout the project review process. If you are interested in fog computing, please do not hesitate to contact us via email for further guidance and detailed explanations.

  1. A Secure Mutual authentication approach to fog computing environment
  2. IoHT-enabled gliomas disease management using fog Computing computing for sustainable societies
  3. Effective load balancing strategy using fuzzy golden eagle optimization in fog computing environment
  4. Performance oriented task-resource mapping and scheduling in fog computing environment
  5. A revocable and outsourced multi-authority attribute-based encryption scheme in fog computing
  6. A scheduling-based dynamic fog computing framework for augmenting resource utilization
  7. Application placement in Fog computing with AI approach: Taxonomy and a state of the art survey
  8. A comprehensive study of simulation frameworks and research directions in fog computing
  9. Intrusion detection using multi-objective evolutionary convolutional neural network for Internet of Things in Fog computing
  10. Lightweight and secure authentication scheme for IoT network based on publish–subscribe fog computing model
  11. Optimized task scheduling for cost-latency trade-off in mobile fog computing using fuzzy analytical hierarchy process
  12. QoS-aware placement of microservices-based IoT applications in Fog computing environments
  13. Adopting elitism-based Genetic Algorithm for minimizing multi-objective problems of IoT service placement in fog computing environment
  14. Blockchain technology as a Fog computing security and privacy solution: An overview
  15. An efficient dynamic service provisioning mechanism in fog computing environment: A learning automata approach
  16. Fuzzy Reinforcement Learning for energy efficient task offloading in Vehicular Fog Computing
  17. Serverless data pipeline approaches for IoT data in fog and cloud computing
  18. Lightweight, Divide-and-Conquer privacy-preserving data aggregation in fog computing
  19. Building applications for smart and safe construction with the DECENTER Fog Computing and Brokerage Platform
  20. Energy- and performance-aware load-balancing in vehicular fog computing