Energy-Efficient Vehicular Edge Computing with One-by-one Access Scheme
With the advent of ever-growing vehicular applications, vehicular edge computing (VEC) has been a promising solution to augment the computing capacity of future smart vehicles. The ultimate challenge to fulfill the quality of service (QoS) is increasingly prominent with constrained computing and communication resources of vehicles. In this paper, we propose an energy-efficient task offloading strategy for VEC system with one-by-one scheduling mechanism, where only one vehicle wakes up at a time to offload with a road side unit (RSU). The goal of system is to minimize the total energy consumption of vehicles by jointly optimizing user scheduling, offloading ratio and bit allocation within a given mission time. To this end, the non-convex and mixed-integer optimization problem is formulated and solved by adopting Lagrange dual problem, whose superior performances are verified via numerical results, as compared to other benchmark schemes.
Code (0)
등록된 구현이 없습니다.
Tasks
Edge-computingSchedulingMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Energy-efficient Cooperative Offloading for Edge Computing-enabled Vehicular Networks
Edge computing technology has great potential to improve various computation-intensive applications in vehicular networks by providing sufficient computation resources for vehicles. However, it is still a challenge to fu…
Edge-computingSocial-Mobility-Aware Joint Communication and Computation Resource Management in NOMA-Enabled Vehicular Networks
The existing computation and communication (2C) optimization schemes for vehicular edge computing (VEC) networks mainly focus on the physical domain without considering the influence from the social domain. This may grea…
Edge-computingManagementHierarchical Task Offloading for UAV-Assisted Vehicular Edge Computing via Deep Reinforcement Learning
With the emergence of compute-intensive and delay-sensitive applications in vehicular networks, unmanned aerial vehicles (UAVs) have emerged as a promising complement for vehicular edge computing due to the high mobility…
Deep Reinforcement LearningEdge-computingSchedulingTrajectory PlanningBlockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks
The drastically increasing volume and the growing trend on the types of data have brought in the possibility of real- izing advanced applications such as enhanced driving safety, and have enriched existing vehicular s…
Edge-computingVehicular Multi-Tier Distributed Computing with Hybrid THz-RF Transmission in Satellite-Terrestrial Integrated Networks
In this paper, we propose a Satellite-Terrestrial Integrated Network (STIN) assisted vehicular multi-tier distributed computing (VMDC) system leveraging hybrid terahertz (THz) and radio frequency (RF) communication techn…
Distributed ComputingEdge-computing