Placement of edge server based on task overhead in mobile edge computing environment,Transactions on Emerging Telecommunications Technologies

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Placement of edge server based on task overhead in mobile edge computing environment
Transactions on Emerging Telecommunications Technologies ( IF 2.5 ) Pub Date : 2020-12-20 , DOI: 10.1002/ett.4196
Bo Li ₁ , Peng Hou ₁ , Hao Wu ₁ , Rongrong Qian ₁ , Hongwei Ding ₁

Affiliation

Mobile edge computing (MEC) deployed cloud computing resources (such as storage and computing power) to the edge of wireless access networks to better meet the development of 5G communication and computing-intensive applications. As the first step of MEC architecture deployment, the placement of the edge server (ES) is the foundation and key, and its location affects the user experience and system performance. In this article, we study the placement of ESs in the heterogeneous networks and express it as an optimization problem. Weighing the response delay and energy consumption as the task overhead, and place the ESs on the optimal access point (AP). An adaptive clustering algorithm MTO based on AP suitability evaluation is proposed to solve the optimal solution, which minimizes the task overhead of computing tasks. Extensive experimental simulations evaluate the performance of the algorithm, and the results show that the MTO algorithm is superior to other representative methods.

中文翻译：

移动边缘计算环境下基于任务开销的边缘服务器放置

移动边缘计算（MEC）将云计算资源（如存储和计算能力）部署到无线接入网络的边缘，以更好地满足5G通信和计算密集型应用的发展。作为MEC架构部署的第一步，边缘服务器（ES）的放置是基础和关键，其位置影响用户体验和系统性能。在本文中，我们研究了异构网络中 ES 的放置，并将其表示为一个优化问题。权衡响应延迟和能耗作为任务开销，将ES放置在最佳接入点（AP）上。提出一种基于AP适用性评价的自适应聚类算法MTO求解最优解，最小化计算任务的任务开销。

更新日期：2020-12-20

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