Simulating Fog and Edge Computing Scenarios: An Overview and Research Challenges

Abstract

The fourth industrial revolution heralds a paradigm shift in how people, processes, things, data and networks communicate and connect with each other. Conventional computing infrastructures are struggling to satisfy dramatic growth in demand from a deluge of connected heterogeneous end points located at the edge of networks while, at the same time, meeting quality of service levels. The complexity of computing at the edge makes it increasingly difficult for infrastructure providers to plan for and provision resources to meet this demand. While simulation frameworks are used extensively in the modelling of cloud computing environments in order to test and validate technical solutions, they are at a nascent stage of development and adoption for fog and edge computing. This paper provides an overview of challenges posed by fog and edge computing in relation to simulation.

A Comprehensive Survey on Opportunistic Routing Protocols for MANETs: Issues, Challenges and Future Directions

“…Each of the protocols were discussed in detail along with their issues and drawbacks. This study would help researchers in developing much more efficient and optimal routing protocols for dynamic ad hoc networks in future Further researchers could also explore the possibilities of implementing opportunistic routing in Underwater Sensor Networks [84][85], IoT Networks [86][87][88][89][90][91][92][93][94][95][96][97][98][99] and Vehicular Fog Networks [100][101][102][103][104].…”

Edge Computing Simulators for IoT System Design: An Analysis of Qualities and Metrics

“…Many edge computing simulators are extensions of the comprehensive CloudSim simulator [21] which focuses on the simulation of cloud computing infrastructures. Svorobej et al [11] conducted a survey study to identify and analyze edge computing simulators in terms of implemented features such as mobility, scalability, as well as infrastructure and network level modeling, however, they did not study the support of QCs in the simulators. To investigate and compare the performance of different IoT architectures by means of simulation, and in terms of QCs relevant for the application at hand, quantitative metrics must be defined.…”

“…To investigate and compare the performance of different IoT architectures by means of simulation, and in terms of QCs relevant for the application at hand, quantitative metrics must be defined. As outputs, most frameworks focus on general network theoretical metrics, such as latency (end-to-end response time), network congestion, or energy consumption [11,17]. To investigate and assess edge-cloud architectures, as well as provide design decision support, the application of such standard metrics is not sufficient.…”

“…By this means, the network topology can be dynamically changed, which allows for the investigation of real-world fog infrastructures, where cloud services are provided closer to the edge of the network. Characteristics of the containers that are considered and can be changed are, for instance, available memory or CPU time, however, others that are of relevance to fog and edge computing such as security, fault tolerance, and scalability are not considered by Fogbed [11]. Although this emulator is mentioned by Sovobej et al [11], its primary purpose is not edge computing.…”

“…However, they only provide basic predefined attributes for the investigation of the IoT system's quality [10] and the integration and use of more sophisticated QCs is often not supported. In addition, simulation has been broadly used to analyze the quality of an IoT system in edge computing before its implementation [11]. Nevertheless, limitations in the extendibility of simulators apply and, as well, a fragmentation of the research regarding the relation between edge computing simulators and QCs can be observed.…”