计算卸载
计算机科学
云计算
边缘计算
延迟(音频)
计算
移动云计算
移动设备
GSM演进的增强数据速率
体验质量
边缘设备
计算机网络
移动边缘计算
分布式计算
低延迟(资本市场)
服务质量
操作系统
人工智能
算法
电信
作者
Divya Gupta,Aditi Moudgil,Shivani Wadhwa,Vikas Solanki
出处
期刊:2021 International Conference on Emerging Smart Computing and Informatics (ESCI)
日期:2022-03-09
卷期号:: 1-5
被引量:5
标识
DOI:10.1109/esci53509.2022.9758379
摘要
We live in a world where huge end devices execute computing on a daily basis. With the growing number of sophisticated apps (e.g., augmented reality and face recognition) that require considerably more computational capacity, they are shifting to mobile cloud computing (MCC), or offloading computation to the cloud. Unfortunately, because the cloud is typically located far away from end devices, latency and quality of experience (QoE) for delay-sensitive applications suffer. Mobile edge computing (MEC) is considered to be a viable solution for meeting the requirement for low latency. Prior works on edge computing mostly focused on computation offloading to support low latency. This paper Jointly considered data caching and computation offloading to support better QoE for end device users. With caching of completed tasks data and offloading of computations at edge cloud using an efficient approach termed as data caching and computation offloading at edge (DCCO-E), the simulation results proved outstanding performance of the DCCO-E against other schemes in terms of low energy consumption and reduced latency.
科研通智能强力驱动
Strongly Powered by AbleSci AI