Abstract
With the development of Internet of Things, massive computation-intensive tasks are generated by mobile devices whose limited computing and storage capacity lead to poor quality of services. Edge computing, as an effective computing paradigm, was proposed for efficient and real-time data processing by providing computing resources at the edge of the network. The deployment of 5G promises to speed up data transmission but also further increases the tasks to be offloaded. However, how to transfer the data or tasks to the edge servers in 5G for processing with high response efficiency remains a challenge. In this paper, a latency-aware computation offloading method in 5G networks is proposed. Firstly, the latency and energy consumption models of edge computation offloading in 5G are defined. Then the fine-grained computation offloading method is employed to reduce the overall completion time of the tasks. The approach is further extended to solve the multiuser computation offloading problem. To verify the effectiveness of the proposed method, extensive simulation experiments are conducted. The results show that the proposed offloading method can effectively reduce the execution latency of the tasks.
Highlights
With the development of wireless communication technology and the Internet of ings (IoT), a variety of emerging applications, such as intelligent access control based on facial recognition, path planning, and virtual reality, meet the needs of people and provide great convenience [1, 2]
In 5G, multiple heterogeneous edge servers can be deployed in the edge network to provide computing services to different users [16, 17]
When the computing task is more complex and the performance on the edge server is significantly better than the local execution, the computing task will be offloaded to the edge server
Summary
With the development of wireless communication technology and the Internet of ings (IoT), a variety of emerging applications, such as intelligent access control based on facial recognition, path planning, and virtual reality, meet the needs of people and provide great convenience [1, 2] These applications are usually resource-hungry and delay-sensitive while the physical limitations and the computing power of the mobile devices cannot undertake such applications [3, 4]. (i) Propose a latency-aware computation offloading method in 5G networks which effectively reduces the overall completion time of the tasks. (iii) rough extensive simulation experiments, our proposed offloading method can effectively reduce the execution latency of the tasks.
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