Energy Efficient Resource Allocation in Federated Fog Computing Networks

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 (PON s) 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- Vmtraffic. 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

Energy Minimized Federated Fog Computing over Passive Optical Networks

The rapid growth of time-sensitive applications and services has driven enhancements to computing infrastructures. The main challenge that needs addressing for these applications is the optimal placement of the end-users’ demands to reduce the total power consumption and delay. One of the widely adopted paradigms to address such a challenge is fog computing. Placing fog units close to end-users at the edge of the network can help mitigate some of the latency and energy efficiency issues. Compared to the traditional hyperscale cloud data centres, fog computing units are constrained by computational power, hence, the capacity of fog units plays a critical role in meeting the stringent demands of the end-users due to intensive processing workloads. In this paper, we first propose a federated fog computing architecture where multiple distributed fog cells collaborate in serving users. These fog cells are connected through dedicated Passive Optical Network (PON) connections. We then aim to optimize the placement of virtual machines (VMs) demands originating from the end-users by formulating a Mixed Integer Linear Programming (MILP) model to minimize the total power consumption. The results show an increase in processing capacity and a reduction in the power consumption by up to 26% compared to a Non-Federated fogs computing architecture

モバイルクラウドコンピューティング環境における計算のオフローディング

筑波大学 (University of Tsukuba)201