EdgeCloudSim: An environment for performance evaluation of Edge Computing systems

Edge Computing is a fast growing field of research covering a spectrum of technologies such as Cloudlets, Fog Computing and Mobile Edge Computing (MEC). Edge Computing involves technically more sophisticated setup when compared with the pure Cloud Computing and pure Mobile Computing cases since both computational and network resources should be considered simultaneously. In that respect, it provides a larger design space with many parameters rendering a variety of novel approaches feasible. Given the complexity, Edge Computing designs deserve scientific scrutiny for sound assessment of their feasibility. However, despite increasing research activity, this field lacks a simulation tool compatible with the requirements. Starting from available simulators a significant programming effort is required to obtain a simulation tool meeting the actual needs. To decrease the barriers, a new simulator tool called EdgeCloudSim streamlined for Edge Computing scenarios is proposed in this work. EdgeCloudSim builds upon CloudSim to address the specific demands of Edge Computing research and support necessary functionality in terms of computation and networking abilities. To demonstrate the capabilities of EdgeCloudSim an experiment setup based on different edge architectures is simulated and the effect of the computational and networking system parameters on the results are depicted.

[1]  Myung J. Lee,et al.  Adaptive Multi-Resource Allocation for Cloudlet-Based Mobile Cloud Computing System , 2016, IEEE Transactions on Mobile Computing.

[2]  Rajkumar Buyya,et al.  CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms , 2011, Softw. Pract. Exp..

[3]  Daniel Camps-Mur,et al.  On the benefits of wireless SDN in networks of constrained edge devices , 2016, 2016 European Conference on Networks and Communications (EuCNC).

[4]  Mahmoud Al-Ayyoub,et al.  The future of mobile cloud computing: Integrating cloudlets and Mobile Edge Computing , 2016, 2016 23rd International Conference on Telecommunications (ICT).

[5]  Rute C. Sofia,et al.  A Survey on Mobility Models for Wireless Networks , 2011 .

[6]  Raja Lavanya,et al.  Fog Computing and Its Role in the Internet of Things , 2019, Advances in Computer and Electrical Engineering.

[7]  Paramvir Bahl,et al.  The Case for VM-Based Cloudlets in Mobile Computing , 2009, IEEE Pervasive Computing.

[8]  Yuelong Zhao,et al.  A Toolkit for Modeling and Simulating Cloud Data Storage: An Extension to CloudSim , 2012, 2012 International Conference on Control Engineering and Communication Technology.

[9]  Essaid Sabir,et al.  Modeling and evaluating a cloudlet-based architecture for Mobile Cloud Computing , 2014, 2014 9th International Conference on Intelligent Systems: Theories and Applications (SITA-14).

[10]  Weisong Shi,et al.  Edge Computing: Vision and Challenges , 2016, IEEE Internet of Things Journal.

[11]  Houbing Song,et al.  A Mobile Cloud Computing Model Using the Cloudlet Scheme for Big Data Applications , 2016, 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).

[12]  Min Dong,et al.  Joint offloading decision and resource allocation for mobile cloud with computing access point , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[13]  Rajkumar Buyya,et al.  iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments , 2016, Softw. Pract. Exp..

[14]  Hwangnam Kim,et al.  MR-CloudSim: Designing and implementing MapReduce computing model on CloudSim , 2012, 2012 International Conference on ICT Convergence (ICTC).

[15]  Chonho Lee,et al.  A survey of mobile cloud computing: architecture, applications, and approaches , 2013, Wirel. Commun. Mob. Comput..