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A Two-Stage Service Migration Algorithm in Parked Vehicle Edge Computing for Internet of Things.
Shuxin Ge1, Meng Cheng2, Xin He3
1Tianjin Key Laboratory of Advanced Networking (TANK), College of Intelligence and Computing, Tianjin University, Tianjin 300350, China.
Sensors (Basel, Switzerland)
|May 20, 2020
Summary
This study introduces a two-stage algorithm for optimal service migration in parked vehicle edge computing (PVEC) networks. The method minimizes average latency by efficiently managing vehicle resources and roadside units for vehicular IoT.
Area of Science:
- Vehicular Edge Computing
- Internet of Things (IoT)
- Network Optimization
Background:
- Parked Vehicle Edge Computing (PVEC) leverages parked vehicles (PVs) and roadside units (RSUs) as service providers (SPs) to enhance vehicular IoT performance.
- Optimal service migration in PVEC is challenging due to unpredictable PV parking durations and resource variability.
Purpose of the Study:
- To develop an effective algorithm for service migration in PVEC networks.
- To minimize average latency in vehicular edge computing environments.
Main Methods:
- Formulated service migration as an optimization problem targeting minimum average latency.
- Proposed a two-stage algorithm: service migration between SPs and PV selection.
- Utilized Lyapunov optimization for online service migration and a modified Hungarian algorithm for PV selection.
Main Results:
- The proposed two-stage service migration algorithm (SEA) demonstrated superior performance.
- Simulations based on real-world vehicle traces validated the algorithm's effectiveness.
- Achieved significant improvements compared to existing state-of-the-art solutions.
Conclusions:
- The developed two-stage algorithm effectively addresses service migration challenges in PVEC.
- The approach optimizes resource utilization and reduces latency in vehicular IoT.
- SEA offers a robust solution for enhancing PVEC network efficiency.
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