IoT Resource Allocation and Optimization Based on Heuristic Algorithm

Area of Science:

• Computer Science
• Distributed Systems
• Optimization Algorithms

Background:

• The Internet of Things (IoT) involves complex distributed systems with numerous resources and gateways.
• Optimizing resource allocation and scheduling (IRAS) is critical for efficient IoT operation.
• Manual resource management in IoT is infeasible due to the scale of connected devices.

Purpose of the Study:

• To address the challenge of optimal resource allocation and scheduling in IoT environments.
• To minimize the total communication cost between resources and gateways within an IoT system.
• To evaluate the effectiveness of the proposed optimization algorithm against existing methods.

Main Methods:

• Implementation of the whale optimization algorithm (WOA) for resource allocation (RA) in IoT.
• Mapping resources to available gateways for optimal allocation.
• Comparative analysis of WOA against other established algorithms using various benchmarks.

Main Results:

• The proposed WOA demonstrates effective performance in solving the IoT RA problem.
• The algorithm successfully reduces the total communication cost between IoT resources and gateways.
• WOA-based resource allocation shows significant improvements over existing algorithms in terms of communication cost.

Conclusions:

• The whale optimization algorithm is a viable and effective solution for optimizing resource allocation and scheduling in IoT.
• The proposed method offers a significant reduction in total communication cost, enhancing IoT efficiency.
• WOA provides a superior approach for managing complex IoT infrastructures compared to traditional algorithms.