Optimum resource allocation in optical wireless systems with energy-efficient fog and cloud architectures

Area of Science:

• Optical Wireless Communication (OWC)
• Networking and Distributed Systems

Background:

• Optical wireless communication (OWC) offers high data rates but lacks comprehensive multiple access and network integration strategies.
• Existing research on OWC primarily focuses on the physical layer, with limited attention to network connectivity and multi-user support.

Purpose of the Study:

• To propose and analyze a novel cloud/fog architecture for OWC systems to enhance multi-user support and processing capabilities.
• To investigate the integration of wavelength division multiple access (WDMA) within the OWC framework for efficient resource allocation.

Main Methods:

• Development of two mixed-integer linear programming (MILP) models to optimize resource allocation (APs, wavelengths) and processing task placement.
• Simulation of various scenarios, varying mobile node locations, processing demands, and data rate requirements.

Main Results:

• Identification of optimal APs and wavelengths for specific mobile node locations and OWC configurations.
• Determination of ideal processing task placement within the cloud/fog architecture.
• Analysis of the network architecture's impact on performance.

Conclusions:

• The proposed cloud/fog architecture effectively enhances OWC systems by integrating WDMA for multi-user access and distributed processing.
• MILP models provide a robust framework for optimizing resource allocation and task management in complex OWC networks.
• The study offers valuable insights for designing efficient and scalable indoor OWC systems.