EdgeCloudSim: An environment for performance evaluation of edge computing systems

Abstract

Edge computing is a fast growing field of research that covers a spectrum of technologies bringing the cloud computing services closer to the end user. Growing interest in this area yields many edge computing approaches that need to be evaluated and optimized. Experimenting on the real cloud environments is not always feasible due to the operational cost and the scalability. Despite increasing research activity, this field lacks a simulation tool that supports the modeling of both computational and networking resources to handle the edge computing scenarios. Existing network simulators can model the network behavior at different levels of granularity. The cloud computing simulators support the modeling and simulation of the computational infrastructures and services efficiently. Starting from the available simulators, a significant programming effort is required to obtain a simulation tool meeting the actual needs. On the other hand, designing a new edge computing tool has many challenges such as the scalability, extensibility, and modeling the mobility, network, and virtualized resources. To decrease the barriers, a new simulator tool called EdgeCloudSim streamlined for the edge computing scenarios is proposed in this work. EdgeCloudSim builds upon CloudSim to address the specific demands of edge computing research and support the necessary functionalities. To demonstrate the capabilities of EdgeCloudSim, an experiment setup based on different edge architectures is simulated. In addition, the effect of the edge server capacity and the mobility on the overall system performance are investigated.

All one needs to know about fog computing and related edge computing paradigms: A complete survey

“…Similarly, the authors in [388] propose another edge computing simulation environment, EdgeCloudSim 8 , that considers both network and computational resources and covers all aspects of edge computing simulation modeling, including network and computational modeling. Similar to iFogSim, EdgeCloudSim relies on CloudSim as well.…”

Robust Resource Allocation Using Edge Computing for Vehicle to Infrastructure (V2I) Networks

“…We have used EdgeCloudSim [16], a discrete edge simulator to evaluate the performance of our proposed model. Due to computational resource limitation, we implement Base Stations in a form of small data centers, with up to 4 cores having computational capacity of 1600 Million Instructions Per Second (MIPS) for each core.…”

“…Task allocation algorithm for load balancer. Input : Task t i ; ETC and ET T matrices; B (set of neighboring Base Stations) Output: Chosen Base Station j ∈ B to assign t i 1 p r (t i ) ← Probability on receiving Base Station r 2 Provisionally assign t i to receiving Base Station r 3 foreach Base Station j ∈ B do 4 p j (t i ) ← Probability on neighbor edge j 5 if p j (t i ) > p r (t i ) then 6 Assign t i to neighbor Base Station j Break if p j (t i ) = p r (t i ) then 10 if σ j < σ r then 11Assign t i to neighbor Base Station j probability of chosen destination is zero then16 Drop task t i…”

Modeling and Simulation of Fog and Edge Computing Environments Using iFogSim Toolkit

“…Simulation toolkits not only provide frameworks to design customized experiment environment but also assist in repeatable evaluation. There exists a certain number of simulators such as Edgecloudsim [6], SimpleIoTSimulator [7] and iFogSim [8] for modelling Fog computing environment and running experiments.…”