Computational Viability of Fog Methodologies in IoT Enabled Smart City Architectures-A Smart Grid Case Study

Abstract

The gradual evolution in the Information Communication Technology (ICT) support of Smart City (SC) architecture leveraged with meshes of Internet of Things (IoT) creates and welcomes research and investment efforts from academia, R&Ds and policymakers. The IoT utilities are being deployed at every layers of a typical SG backbone namely Application layer, Energy layer and Communication layer. The geo-distributed clusters of IoT -objects‖ produce galactic volume of data that exacerbates the need to make a paradigm shift from centralized data center based processing to a hybrid model that supports both in situ as well as cloud based storage and computational resources. To combat such SC issues, Fog Computing (FC) emerges as a promising solution, which pushes the computation resources onto the network edge nodes. This work investigates the high performance of Fog Computing over generic cloud computing in terms of metrics viz. latencies, power consumption etc, through a Smart Grid (SG) use-case. Through an operational cost optimization framework, the work comprehends the suitability of fog methodologies to make a synergistic interplay with the core centered clouds thus empowering a wide breed of real-time and latency free services. Finally, an overview of the core orchestration issues, challenges, and future research directions are presented for FC enabled SCs.

Cloud-Edge Orchestration for Smart Cities: A Review of Kubernetes-based Orchestration Architectures

“…Especially the latter proposal aims to move workloads during runtime from edge nodes to other edge nodes. In regards to the already introduced edge technologies, there are architectures that either require or support cloud, edge, MEC, fog [75,76], or finally cloudlets [77] as fundamental edge technology. Distributing and shifting of workloads and tasks in SCs was covered in [78,79].…”