计算机科学
服务器
边缘计算
调度(生产过程)
分布式计算
移动边缘计算
计算机网络
边缘设备
GSM演进的增强数据速率
云计算
电信
操作系统
运营管理
经济
作者
Qinglan Peng,Chunrong Wu,Yunni Xia,Yong Ma,Xu Wang,Ning Jiang
出处
期刊:IEEE Internet of Things Journal
[Institute of Electrical and Electronics Engineers]
日期:2022-03-15
卷期号:9 (6): 4677-4692
被引量:19
标识
DOI:10.1109/jiot.2021.3107431
摘要
With the proliferation of novel Internet of Things (IoT) mobile applications and advanced communication technologies, nowadays we are surrounded by ubiquitous sensors and smart devices. These smart IoT devices generate a large volume of data day and night at the edge of the network, create a huge demand for edge computing resources, and thus, promote the emergence of the multiaccess edge computing (MEC) paradigm. In MEC environments, IoT devices or mobile users are allowed to offload their computational tasks to nearby edge servers to overcome the limitation of local computing resources. Though edge servers could provide low-latency service with high-responsible computing capabilities, they are still facing many challenges posed by the limited hardware resources and diverse offloading requests. However, traditional approaches are usually based on the centralized architecture and batch-processing scheduling mode, which might lead to low efficiency and high communication overhead. Besides, they also lack the consideration of task diversity and priorities, which are crucial in real-world application scenarios. Thus, smart task scheduling and resource provision strategies with a high real-time property are urgently needed for better user experience and higher resource utilization. In this article, we target the online edge IoT task scheduling and resource allocation problem and propose a decentralized approach (DoSRA). The experiments based on real-world edge environments have demonstrated that the proposed approach could achieve at most a 35.34% reduction on the average weighted offloading response time.
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