Potentials, trends, and prospects in edge technologies: Fog, cloudlet, mobile edge, and micro data centers

Abstract

Advancements in smart devices, wearable gadgets, sensors, and communication paradigm have enabled the vision of smart cities, pervasive healthcare, augmented reality and interactive multimedia, Internet of Every Thing (IoE), and cognitive assistance, to name a few. All of these visions have one thing in common, i.e., delay sensitivity and instant response. Various new technologies designed to work at the edge of the network, such as fog computing, cloudlets, mobile edge computing, and micro data centers have emerged in the near past. We use the name "edge computing" for this set of emerging technologies. Edge computing is a promising paradigm to offer the required computation and storage resources with minimal delays because of "being near" to the users or terminal devices. Edge computing aims to bring cloud resources and services at the edge of the network, as a middle layer between end user and cloud data centers, to offer prompt service response with minimal delay. Two major aims of edge computing can be denoted as: (a) minimize response delay by servicing the users' request at the network edge instead of servicing it at far located cloud data centers, and (b) minimize downward and upward traffic volumes in the network core. Minimization of network core traffic inherently brings energy efficiency and data cost reductions. Downward network traffic can be minimized by servicing set of users at network edge instead of service provider's data centers (e.g., multimedia and shared data) Content Delivery Networks (CDNs), and upward traffic can be minimized by processing and filtering raw data (e.g., sensors monitored data) and uploading the processed information to cloud. This survey presents a detailed overview of potentials, trends, and challenges of edge computing. The survey illustrates a list of most significant applications and potentials in the area of edge computing. State of the art literature on edge computing domain is included in the survey to guide readers towards the current trends and future opportunities in the area of edge computing.

Quality of service‐aware approaches in fog computing

“…In FC, like in cloud computing, the following types of service models can be implemented: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). FC is distinguished from other computing approaches because of the following features 23,24 :…”

“…In FC, like in cloud computing, the following types of service models can be implemented: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). FC is distinguished from other computing approaches because of the following features: Because fog nodes are aware of their logical situation in the whole system and of the latency costs for communicating with other nodes, FC provides the least latency. As fog nodes border end devices, the analysis of and replying to the produced data by these devices are much faster than those of a cloud service. Compared to the centralized cloud, services and applications in a distributed geographic district are extensively the applicants of FC. FC provides the possibility of maintenance and processing different forms of data by applying different types of network communicative competence. Supporting defined services like real‐time streaming services needs providers' cooperation.…”

“…This architecture includes three layers: cloud, fog, and User device: Cloud layer : The cloud layer includes strong computing and storage servers to be able to the do storage of a huge amount of data and extensive computing analysis for various application services if necessary. Fog layer : This layer is situated on the network edge. Fog layer is a combination of a great number of fog nodes (physical or virtual) . These fog nodes are distributed extensively between cloud and end devices.…”

Location-Aware Energy-Efficient Workload Allocation in Geo Distributed Cloud Environment

“…This is beside the penalty ratio that paid by cloud provider for consumers' compensations if the given deadline is missed. Literature and researchers reveal that poor cloud experience and delay for each onesecond result in 16% degradation in customer satisfaction and more than 22% drop in cloud services sales (Bilal et al, 2018;Cheng et al, 2016).…”

Improving the Efficiency of Water Management System in Biomass Power Plant Using Cyber-Physical Cloud Computing

“…The edge computing device is a programmable logic controller integrated with industrial IoT gateway which provides functionalities of process operation control as well as enable cloud connection to physical devices [16].…”