摘要
自动驾驶、增强现实等5G新兴的应用对网络时延和可靠性提出更高的挑战,针对边缘协同框架负载均衡问题,提出一种大规模边云协同分布式网络架构下的任务卸载模型。该模型以最低能耗为目标,根据任务特性与现有网络资源、计算资源和存储资源自适应优化任务卸载决策,通过整合边缘计算与云计算处理能力的优势,保证时延敏感型任务的质量,提高整个系统的负载均衡,降低能耗。
5G emerging applications such as autopilot and augmented reality pose higher challenges to network delay and reliability. Aiming at the load balancing problem of edge collaboration framework, this paper proposes a task offloading model under large-scale edge cloud collaborative distributed network architecture. The model takes the minimum energy consumption as the goal, and adaptively optimizes the task unloading decision according to the task characteristics and the existing network resources, computing resources and storage resources. By integrating the advantages of edge computing and cloud computing, the delay sensitive task quality is guaranteed, the load balance of the whole system is improved, and the energy consumption is reduced.
作者
陈慧敏
胡玉佩
CHEN Huimin;HU Yupei(Guangdong Vocational College of Post and Telecom,Guangzhou 510630,China)
出处
《移动通信》
2021年第4期144-148,共5页
Mobile Communications
关键词
边云协同
任务卸载
资源管理
负载均衡
edge cloud collaboration
task unloading
resource management
load balancing
