Examining the Performance of Fog-Aided, Cloud-Centered IoT in a Real-World Environment

The fog layer provides substantial benefits in cloud-based IoT applications because it can serve as an aggregation layer and it moves the computation resources nearer to the IoT devices; however, it is important to ensure adequate performance is achieved in such applications, as the devices usually communicate frequently and authenticate with the cloud. This can cause performance and availability issues, which can be dangerous in critical applications such as in the healthcare sector. In this paper, we analyze the efficacy of the fog layer in different architectures in a real-world environment by examining performance metrics for the cloud and fog layers using different numbers of IoT devices. We also implement the fog layer using two methods to determine whether different fog implementation frameworks can affect the performance. The results show that including a fog layer with semi-heavyweight computation capability results in higher capital costs, although the in the long run resources, time, and money are saved. This study can serve as a reference for fundamental fog computing concepts. It can also be used to walk practitioners through different implementation frameworks of fog-aided IoT and to show tradeoffs in order to inform when to use each implementation framework based on one’s objectives.

[1]  Frederick T. Sheldon,et al.  Access Control in Fog Computing: Challenges and Research Agenda , 2020, IEEE Access.

[2]  Manish Marwah,et al.  IoTAbench: an Internet of Things Analytics Benchmark , 2015, ICPE.

[3]  Nitin Naik,et al.  Choice of effective messaging protocols for IoT systems: MQTT, CoAP, AMQP and HTTP , 2017, 2017 IEEE International Systems Engineering Symposium (ISSE).

[4]  Victor C. M. Leung,et al.  End-edge-cloud collaborative computation offloading for multiple mobile users in heterogeneous edge-server environment , 2020, Wireless Networks.

[5]  Tilmann Rabl,et al.  Analysis of TPCx-IoT: The First Industry Standard Benchmark for IoT Gateway Systems , 2018, 2018 IEEE 34th International Conference on Data Engineering (ICDE).

[6]  Shajulin Benedict,et al.  Monitoring IaaS using various cloud monitors , 2018, Cluster Computing.

[7]  Frederick T. Sheldon,et al.  Performance Analysis of Two Cloud-Based IoT Implementations: Empirical Study , 2020, 2020 7th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2020 6th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom).

[8]  Silia Maksuti,et al.  Self-Adaptation Applied to MQTT via a Generic Autonomic Management Framework , 2019, 2019 IEEE International Conference on Industrial Technology (ICIT).

[9]  Heng Wang,et al.  A Lightweight XMPP Publish/Subscribe Scheme for Resource-Constrained IoT Devices , 2017, IEEE Access.

[10]  Khaled Salah,et al.  Performance Evaluation of IoT-Fag-Cloud Deployment for Healthcare servicies , 2018, 2018 4th International Conference on Cloud Computing Technologies and Applications (Cloudtech).

[11]  Vasaka Visoottiviseth,et al.  A scalable and low-cost MQTT broker clustering system , 2017, 2017 2nd International Conference on Information Technology (INCIT).

[12]  Sajjan G. Shiva,et al.  An Overview of Enabling Technologies for the Internet of Things , 2018, Internet of Things A to Z.

[13]  Mahantesh N. Birje,et al.  Commercial and Open Source Cloud Monitoring Tools: A Review , 2019 .

[14]  Ahmed A. Ismail,et al.  Performance Evaluation of Open Source IoT Platforms , 2018, 2018 IEEE Global Conference on Internet of Things (GCIoT).

[15]  Xuemin Shen,et al.  Securing Fog Computing for Internet of Things Applications: Challenges and Solutions , 2018, IEEE Communications Surveys & Tutorials.

[17]  Adel Nadjaran Toosi,et al.  Performance evaluation metrics for cloud, fog and edge computing: A review, taxonomy, benchmarks and standards for future research , 2020, Internet Things.

[18]  Sajjan G. Shiva,et al.  IoMT-SAF: Internet of Medical Things Security Assessment Framework , 2019, Internet Things.

[19]  Alexander Schill,et al.  A service infrastructure for the Internet of Things based on XMPP , 2013, 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).

[20]  Hyeonwoo Kim,et al.  Correlation analysis of MQTT loss and delay according to QoS level , 2013, The International Conference on Information Networking 2013 (ICOIN).

[21]  Blesson Varghese,et al.  DeFog: fog computing benchmarks , 2019, SEC.

[22]  Joel J. P. C. Rodrigues,et al.  Performance evaluation of a Fog-assisted IoT solution for e-Health applications , 2019, Future Gener. Comput. Syst..

[23]  Stacy Patterson,et al.  EdgeBench: Benchmarking Edge Computing Platforms , 2018, 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion).

[24]  Sherali Zeadally,et al.  Fog Computing Architecture, Evaluation, and Future Research Directions , 2018, IEEE Communications Magazine.