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Resource Cluster-Based Resource Search and Allocation Scheme for Vehicular Clouds in Vehicular Ad Hoc Networks
Hyunseok Choi1, Yoonhyeong Lee2, Gayeong Kim3
1Research Institute for Computer and Information Communication, Chungbuk National University, Cheongju 28644, Republic of Korea.
Sensors (Basel, Switzerland)
|April 13, 2024
Summary
Vehicular clouds efficiently manage resources by clustering them by type, not location. This Resource Cluster-based Resource Search and Allocation (RCSA) scheme improves resource utilization and allocation in mobile vehicular networks.
Area of Science:
- Computer Science
- Networking
- Distributed Systems
Background:
- Vehicular clouds leverage vehicle resources for services.
- Efficient resource search and allocation are critical challenges.
- Existing cluster-based approaches struggle with vehicle mobility and diverse resources.
Purpose of the Study:
- To propose a novel scheme for efficient resource search and allocation in vehicular clouds.
- To address the limitations of proximity-based clustering in dynamic vehicular environments.
Main Methods:
- Introduced the Resource Cluster-based Resource Search and Allocation (RCSA) scheme.
- Clustered resources by type, enabling intra- and inter-resource cluster searches.
- Prioritized vehicles with longer connection times and larger capacities for allocation.
- Implemented mechanisms for dynamic cluster reconstruction (RCH/RCM replacement).
Main Results:
- RCSA demonstrates superior resource utilization compared to existing schemes.
- The proposed scheme shows enhanced resource allocation efficiency.
- Overall performance in vehicular cloud construction is significantly improved.
Conclusions:
- Resource clustering by type is more effective than proximity-based clustering for vehicular clouds.
- RCSA offers a robust solution for resource management in dynamic vehicular environments.
- The scheme effectively minimizes cloud breakdowns and communication traffic.
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