Trust Enforced Computational Offloading for Health Care Applications in Fog Computing

Area of Science:

• Computer Science
• Network Engineering
• Cybersecurity

Background:

• The Internet of Things (IoT) generates vast amounts of data, with increasing use in healthcare for remote patient monitoring.
• Cloud computing faces challenges in managing private healthcare data due to privacy and availability constraints.
• Fog computing offers a proximity-based solution for computation and storage, but requires trustable processing entities.

Purpose of the Study:

• To propose a novel technique for secure and efficient data processing in fog computing environments for IoT applications.
• To address the challenges of data privacy, availability, and trust in remote healthcare monitoring systems.
• To reduce response times for delay-sensitive applications while ensuring data integrity.

Main Methods:

• Introduction of the Trust Enforced computation ofFLoading technique for trust worthy applications using fOg computiNg (TEFLON).
• Development of two algorithms: optimal service offloader and trust assessment.
• Simulation of the TEFLON framework to evaluate its performance.

Main Results:

• The TEFLON framework significantly improves the success rate of fog collaboration.
• Reduced average latency is achieved for delay-sensitive applications.
• The system ensures trust for trustworthy applications, addressing security and privacy concerns.

Conclusions:

• TEFLON provides a viable solution for secure and efficient data processing in fog computing for IoT.
• The proposed technique enhances the reliability and trustworthiness of remote healthcare monitoring.
• TEFLON effectively balances performance gains with robust security measures.