Ph.D Guidance in Fog Computing

In recent years, the rapid proliferation of performing the distributed computing demands the need of decentralized computing structure, especially for the latency-sensitive applications such as the Internet of Things (IoT) applications. As the rise of accessing the IoT applications, handling the real-time processing of a vast amount of data generated from heterogeneous wireless IoT devices is critical. To overcome this constraint, the Cloud computing technology has been applied over the past decades due to its on-demand access and high cost-efficiency. Although, with the rapid development of IoT applications, the centralized Cloud computing technology encounters high latency constraints. To deal with the delay-sensitive IoT applications in a Cloud environment, Fog computing extends the cloud computing to the edge of the network in which data and applications are located between the data source and the cloud. Fog computing is also termed as ‘fog networking,’ and ‘fogging.’

The dramatic growth of numerous internet-connected smart devices and frequent service requests generated by the users poses a heavy burden to the network bandwidth. The high network latency between the smart devices and the cloud makes it infeasible for delay-sensitive applications. A distributed computing system of the fog network is essential to reduce the power consumption and meet the latency requirements of the end devices, reduce the burden to the centralized data center, and provide real-time data processing with localized computing resources. With the necessity of improving the overall network performance and efficiency for latency-sensitive applications such as disaster management, smart healthcare, and smart transportation, fog computing becomes an emerging modern technology in our daily lives.

The emergence of Fog computing technology has been widely used in different fields including manufacturing, smart buildings, and healthcare. Fog computing provides the potential benefits for the IoT applications such as smart electrical grids, smart traffic light system, and smart transportation. It has the potential to support the different innovative applications involve smart cities, smart switching systems, and smart home appliances. For instance, to free-up, the congested road, traffic light sensors in the smart cities divert the traffic to another road. In the example of smart home appliances, if the sensors embedded in the home appliances detect anomalies, the home appliances send an automatic alert to the respective person.

  • Research Proposal in Fog Computing
  • Problem Identification in Fog Computing
  • Research Methodology
  • Mathematical Model / Formulation
  • Literature Survey in Fog Computing
  • System Design and Implementation
  • Performance Analysis and Results
  • Writing Services: Journal Papers, Synopsis and Thesis

Courses

  • Ph.D – Computer Science and Engineering, Computer Science, Computer Application, Information Technology and Computer Networks.
  • M.E/M.Tech/M.S – Computer Science and Engineering, Computer Science, Computer Application, Information Technology and Computer Networks.

Research Topics

  • Fog Computing architecture for Cloud of Things
  • Blockchain-based Fog computing
  • Autonomous transportation through Fog computing
  • Offloading and Load redistribution in Fog computing
  • Scalability and QoS management
  • Energy-aware Load balancing
  • Real-time analytics in Fog
  • Cognitive fog-based applications
  • Fog-to-Fog and Fog-to-Cloud communication
  • Fog Computing in 5G network
  • Trust and Security in Fog computing

Tools and Technologies

  • Java/CloudSim
  • Netbeans 7.0
  • Eclipse 4.3
  • Tomcat 7.0
  • Glass Fish 4.0
  • My-SQL 5.5
  • Apache Axis2
  • ArgoUML
  • Java Database Connectivity (JDBC)
  • Java Server Pages (JSP)
  • Servlets
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