Abstract
The Multi-Access Edge Computing (MEC) paradigm provides a promising solution to solve the resource-insufficiency problem in user mobile devices by offloading computation-intensive and delay-sensitive computing services to nearby edge nodes. However, there is a lack of research on the efficient task offloading and mobility support when mobile users frequently move in the MEC environment. In this paper, we propose the mobile personal MEC architecture that utilizes a user’s mobile device as an MEC server (MECS) so that mobile users can receive fast response and continuous service delivery. The results show that the proposed scheme reduces the average service delay and provides efficient task offloading compared to the existing MEC scheme. In addition, the proposed scheme outperforms the existing MEC scheme because the existing mobile user devices are used as MECS, enabling low-latency service and continuous service delivery, even as the mobile user requests and task sizes increase.
Highlights
The proliferation of high-performance user mobile devices and advances in network technology have led to the explosion of computational-intensive, delay-sensitive mobile application services such as real-time online games, virtual reality (VR) and augmented reality (AR) [1,2,3,4,5,6].For example, AR services provide mobile users with an experience of interacting with the real world by adding computer-generated perceptual information to objects that exist in the real world.Since these services should quickly process data collected from cameras and sensors on user mobile devices, AR services require high computing power
This paper makes the following points. It shows that the existing Multi-Access Edge Computing (MEC) architecture brings computing capacity to the edge of the mobile network, which enables the mobile user to run applications that require ultra-low delay service to meet strict service requirements
We propose a mobile personal MEC architecture that utilizes a user’s mobile device as an MEC server (MECS) in this paper
Summary
The proliferation of high-performance user mobile devices and advances in network technology have led to the explosion of computational-intensive, delay-sensitive mobile application services such as real-time online games, virtual reality (VR) and augmented reality (AR) [1,2,3,4,5,6]. AR services provide mobile users with an experience of interacting with the real world by adding computer-generated perceptual information to objects that exist in the real world Since these services should quickly process data collected from cameras and sensors on user mobile devices, AR services require high computing power. The enormous amount of data exchanged between the mobile device and central cloud data center causes the data tsunami that saturates the backhaul network These problems make it difficult to provide mobile users with the fifth-generation cellular network (5G) services that require high reliability and low latency such as ultra-reliable and low-latency communication (URLLC). There is a need for an efficient tasking offloading scheme in edge computing environments To solve these problems, this paper aims to study how to support efficient task offloading by using user mobile device as edge computing host in the MEC environment.
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