MEC-EnergySaver:通过 D2D 和数据压缩提高效率

Anindita Ghosh, Poulomi Mukherjee, Tanmay De
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引用次数: 0

摘要

从基本手机到智能手机的转变带来了智能设备,同时移动应用程序的激增也重塑了日常生活。与此同时,数据分析、人工智能和物联网等技术也带来了智能家居和先进的交通系统,对移动设备的计算能力提出了更高的要求。为应对这一挑战,移动边缘计算(MEC)作为一种解决方案应运而生。与远程云计算不同,MEC 在网络边缘提供计算服务,允许移动用户将计算任务转移到附近的 MEC 服务器上。然而,MEC 系统在有效卸载计算和分配资源以减少能源消耗和处理时间方面面临挑战。移动设备的发展和数据密集型应用的兴起,促使人们需要像 MEC 这样的高效计算解决方案,并有可能整合数据压缩以节约能源。本文介绍了 MEC 系统中请求服务的两阶段方法。第一阶段根据设备邻近程度确定设备到设备(D2D)连接的优先级,有效配对设备进行数据交换。未配对的设备会被引导到最近的 MEC 节点。在第二阶段,未通过 D2D 连接满足的请求由战略定位的 MEC 节点处理,以确保全面覆盖并最大限度地减少网络能耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MEC-EnergySaver: Unleashing Efficiency Through D2D and Data Compression
The shift from basic cell phones to smartphones has ushered in intelligent devices, alongside a surge in mobile apps that reshape daily life. Simultaneously, technologies like data analytics, AI and IoT have enabled smart homes and advanced transport systems, demanding substantial computational power from mobile devices. To tackle this challenge, mobile-edge computing (MEC) has emerged as a solution. Unlike remote cloud computing, MEC offers computing services at the network's edge, allowing mobile users to transfer their computing tasks to MEC servers located nearby. However, MEC systems face challenges in efficient computation offloading and distributing resources in a way that reduces energy use and processing times. The evolution of mobile devices and the rise of data-intensive applications have led to the need for efficient computing solutions like MEC, with the potential to integrate data compression for energy savings. This paper introduced a two-phase approach for request servicing in MEC systems. The first phase prioritizes Device-to-Device (D2D) connections based on device proximity, efficiently pairing devices for data exchange. Unpaired devices are directed to the nearest MEC node. In the second phase, requests not fulfilled via D2D connections are handled by strategically positioned MEC nodes, ensuring comprehensive coverage and minimizing network energy consumption.
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