In the Green Cloudlet Network (GCN) architecture, each User Equipment (UE) is associated with an Avatar (a private virtual machine for executing its UE's offloaded tasks) in a cloudlet located at the network edge. In order to reduce the operational expenditure for maintaining the distributed cloudlets, each cloudlet is powered by green energy and uses on-grid power as a backup. Owing to the spatial dynamics of energy demands and green energy generations, the energy gap (i.e., energy demand minus green energy generation) among different cloudlets in the network is unbalanced, i.e., some cloudlets’ energy demands can be fully provisioned by their green energy generations but others need to utilize on-grid power to meet their energy demands. The unbalanced energy gap increases the on-grid power consumption of the cloudlets. In this paper, we propose the Green-energy aware Avatar Placement (GAP) strategy to minimize the total on-grid power consumption of the cloudlets by migrating Avatars among the cloudlets according to the cloudlets’ residual green energy, while guaranteeing the service level agreement (the End-to-End (E2E) delay requirement between a UE and its Avatar). Simulation results show that GAP can save 57.1 and 57.6 percent of on-grid power consumption as compared to the two other Avatar placement strategies, i.e., Static Avatar Placement and Follow me AvataR, respectively.

中文翻译：

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Green Cloudlet Network：移动云计算的可持续平台

在绿色小云网络 (GCN) 架构中，每个用户设备 (UE) 都与位于网络边缘的小云中的 Avatar（用于执行其 UE 卸载任务的私有虚拟机）相关联。为了减少维护分布式小云的运营支出，每个小云都由绿色能源供电，并使用并网电源作为备份。由于能源需求和绿色能源发电的空间动态，网络中不同小云之间的能量缺口（即能源需求减去绿色能源发电）是不平衡的，即一些小云的能源需求可以完全由它们的绿色能源提供代，但其他人需要利用并网电力来满足他们的能源需求。不平衡的能隙增加了小云的并网功耗。在本文中，我们提出了绿色能源意识的化身放置（GAP）策略，通过根据小云的剩余绿色能量在小云之间迁移虚拟形象来最小化小云的总上网功耗，同时保证服务水平协议（终端- UE 与其虚拟形象之间的端到端 (E2E) 延迟要求）。仿真结果表明，与其他两种虚拟化身放置策略（即静态虚拟化放置和跟随我 AvataR）相比，GAP 可以分别节省 57.1% 和 57.6% 的并网功耗。同时保证服务水平协议（UE与其虚拟形象之间的端到端（E2E）延迟要求）。仿真结果表明，与其他两种头像放置策略（即静态头像放置和跟随我头像）相比，GAP 可以分别节省 57.1% 和 57.6% 的并网功耗。同时保证服务水平协议（UE与其虚拟形象之间的端到端（E2E）延迟要求）。仿真结果表明，与其他两种头像放置策略（即静态头像放置和跟随我头像）相比，GAP 可以分别节省 57.1% 和 57.6% 的并网功耗。