Physics-Inspired Mobile Cloudlet Placement in Next-Generation Edge Networks
Physics-Inspired Mobile Cloudlet Placement in Next-Generation Edge Networks
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DOI：
10.1109/edge55608.2022.00031
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
Dixit Bhatta;Lena Mashayekhy
中科院分区：
文献类型：
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作者：
Dixit Bhatta;Lena Mashayekhy
IoT（物联网）设备需要可靠的超低延迟连接和对其附近计算资源的按需访问。边缘计算可以通过卸载到云来提供附近的计算资源。然而，在大城市、紧急情况和缺乏足够基础设施的地方提供稳定的服务面临挑战，因为物联网需求不断变化，移动性不确定，加上与附近计算资源的连接断断续续或有限。为了解决这些问题，越来越多地采用UAV安装的移动的微云，其中移动的微云可以无缝地集成到现有的网络基础设施中，用于卸载和增强连接。然而，自适应地放置移动的微云在不断发展的条件下仍然是一个悬而未决的问题。在本文中，我们研究了高度动态的下一代边缘网络中的移动的微云放置。我们的目标是通过在高度动态的场景中优化移动的云的放置，保持稳定的超低延迟服务并增强覆盖范围。我们提出了一种新的方法，这个问题的灵感来自物理概念，即重心和吸引力。我们的方法模拟物理机构如何保持平衡，并调整其位置时，由动态外力有效地放置移动的云响应动态和不确定的设备移动性。结果表明，我们提出的方法提供了高的设备覆盖率，出色的能源效率和稳定的边缘服务实时。
IoT (Internet-of-Things) devices require both reliable, ultra-low latency connection and on-demand access to computing resources in their vicinity. Edge computing can provide nearby computing resources through offloading to cloudlets. However, challenges lie in providing stable services in big cities, emergency situations, and places lacking sufficient infrastructure due to dynamic IoT demands and their uncertain mobility, coupled with intermittent or limited connectivity to nearby computing resources. There has been an increasing adoption of UAV-mounted mobile cloudlets to address these issues, where mobile cloudlets can be seamlessly integrated into the existing network infrastructure for offloading and enhanced connectivity. However, adaptively placing mobile cloudlets under continuously evolving conditions is still an open problem. In this paper, we study mobile cloudlet placement in highly dynamic, next-generation edge networks. Our objective is to maintain stable ultra-low-latency services and enhance coverage by optimizing the placement of mobile cloudlets in highly dynamic scenarios. We propose a novel approach for this problem using inspirations from concepts in physics, namely the center of gravity and force of attraction. Our approach emulates how physical bodies maintain balance and adjust their positions when acted upon by dynamic external forces for efficient placement of mobile cloudlets in response to dynamic and uncertain device mobility. The results show that our proposed approach provides high device coverage, excellent energy efficiency, and stable edge services in real-time.