There is a continuous growth in demand for time sensitive applications which has shifted the cloud paradigm from a centralized computing architecture towards distributed heterogeneous computing platforms where resources located at the edge of the network are used to provide cloud-like services. This paradigm is widely known as fog computing. Virtual machines (VMs) have been widely utilized in both paradigms to enhance the network scalability, improve resource utilization, and energy efficiency. Moreover, Passive Optical Networks (PONs) are a technology suited to handling the enormous volumes of data generated in the access network due to their energy efficiency and large bandwidth. In this paper, we utilize a PON to provide the connectivity between multiple distributed fog units to achieve federated (i.e. cooperative) computing units in the access network to serve intensive demands. We propose a mixed integer linear program (MILP) to optimize the VM placement in the federated fog computing units with the objective of minimizing the total power consumption while considering inter-VM traffic. The results show a significant power saving as a result of the proposed optimization model by up to 52%, in the VM-allocation compared to a baseline approach that allocates the VM requests while neglecting the power consumption and inter-VMs traffic in the optimization framework.

翻译：对时间敏感应用的需求持续增长,使云层范式从中央计算结构转向分布式混合计算平台,将位于网络边缘的资源用于提供云类服务。这种范式被广泛称为雾计算。虚拟机(VMs)在两种范式中被广泛使用,以提高网络的可扩缩性、改进资源利用和能源效率。此外,被动光学网络(PONs)是一种技术,适合处理接入网络中产生的大量数据,因为其能效和宽度很大。在本文中,我们使用一个PON,提供多个分布式烟雾单位之间的连接,以在接入网络中实现联邦化(即合作)计算单位,满足密集的需求。我们提议了一个混合整数线性程序(MILP),以优化在通电雾计算器中的 VM 配置,目的是在考虑 VM 内部交通流量时尽量减少总电耗量。结果显示,由于拟议的优化模式,在VM 定位中,与一个基线方法相比,将VM 配置为52%,在VM 通信节能框架中分配,同时忽略了VM 节能框架。