Joint Power Allocation and Task Replication for Reliability-Sensitive Services in NOMA-Enabled Vehicular Edge Computing

Abstract

To cope with the increasing demands of computing tasks in vehicles, task offloading to computing nodes (vehicles and edge servers) in a vehicular edge computing (VEC) scenario has gained significant attention. However, the high dynamic of task arrival and variant wireless network conditions could severely impact the quality of computation offloading for latency-aware and high-reliability services. Consequently, only offloading tasks to a single computing node may fail to satisfy the reliability requirements due to potential transmission errors or constraints on delay. To mitigate the limitations of task offloading to only one single computing node in VEC, task replication, in which a task can be sent to multiple computing nodes simultaneously is utilized. Nevertheless, unrestricted task replication may exacerbate the depletion of network and computing resources in VEC when a burst of computing tasks is generated. To address the above challenges, we first formulate the problem of power allocation with task replication in NOMA-enabled VEC. Our purpose is to maximize task transmission reliability based on the Finite Block Length (FBL) theory while following the delay constraint. To achieve this goal, we formulate the problem of task replication and power allocation into a constrained stochastic optimization problem and apply the Lyapunov optimization framework to adjust task replication decisions and power allocation for each vehicle. Simulation results demonstrate that the proposed algorithm can obtain better service reliability than other alternative algorithms.