Fogify: A Fog Computing Emulation Framework

被引:39
作者
Symeonides, Moysis [1 ]
Georgiou, Zacharias [1 ]
Trihinas, Demetris [2 ]
Pallis, George [1 ]
Dikaiakos, Marios D. [1 ]
机构
[1] Univ Cyprus, Dept Comp Sci, Nicosia, Cyprus
[2] Univ Nicosia, Dept Comp Sci, Nicosia, Cyprus
来源
2020 IEEE/ACM SYMPOSIUM ON EDGE COMPUTING (SEC 2020) | 2020年
关键词
Fog Computing; Internet of Things; EDGE; CLOUD; SIMULATION; MANAGEMENT; PLATFORM; INTERNET; TOOLKIT; IOT;
D O I
10.1109/SEC50012.2020.00011
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Fog Computing is emerging as the dominating paradigm bridging the compute and connectivity gap between sensing devices and latency-sensitive services. However, experimenting and evaluating IoT services is a daunting task involving the manual configuration and deployment of a mixture of geo-distributed physical and virtual infrastructure with different resource and network requirements. This results in sub-optimal, costly and error-prone deployments due to numerous unexpected overheads not initially envisioned in the design phase and underwhelming testing conditions not resembling the end environment. In this paper, we introduce Fogify, an emulator easing the modeling, deployment and large-scale experimentation of fog and edge testbeds. Fogify provides a toolset to: (i) model complex fog topologies comprised of heterogeneous resources, network capabilities and QoS criteria; (ii) deploy the modelled configuration and services using popular containerized descriptions to a cloud or local environment; (iii) experiment, measure and evaluate the deployment by injecting faults and adapting the configuration at runtime to test different "what-if" scenarios that reveal the limitations of a service before introduced to the public. In the evaluation, proof-of-concept IoT services with real-world workloads are introduced to show the wide applicability and benefits of rapid prototyping via Fogify.
引用
收藏
页码:42 / 54
页数:13
相关论文
共 50 条
  • [21] Design, Resource Management, and Evaluation of Fog Computing Systems: A Survey
    Martinez, Ismael
    Hafid, Abdelhakim Senhaji
    Jarray, Abdallah
    IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (04) : 2494 - 2516
  • [22] Fog computing in internet of things: Practical applications and future directions
    Naeem, Rida Zojaj
    Bashir, Saman
    Amjad, Muhammad Faisal
    Abbas, Haider
    Afzal, Hammad
    PEER-TO-PEER NETWORKING AND APPLICATIONS, 2019, 12 (05) : 1236 - 1262
  • [23] Latency-Aware Placement Heuristic in Fog Computing Environment
    Amira, Rayane Benamer
    Hana, Teyeb
    Ben Hadj-Alouane, Nejib
    ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS (OTM 2018), PT II, 2018, 11230 : 241 - 257
  • [24] Secure framework for IoT applications using Deep Learning in fog Computing
    Chakraborty, Ananya
    Kumar, Mohit
    Chaurasia, Nisha
    JOURNAL OF INFORMATION SECURITY AND APPLICATIONS, 2023, 77
  • [25] Monitoring in fog computing: state-of-the-art and research challenges
    Abreha, Haftay Gebreslasie
    Bernardos, Carlos J.
    de la Oliva, Antonio
    Cominardi, Luca
    Azcorra, Arturo
    INTERNATIONAL JOURNAL OF AD HOC AND UBIQUITOUS COMPUTING, 2021, 36 (02) : 114 - 130
  • [26] Study of the Efficiency of Fog Computing in an Optimized LoRaWAN Cloud Architecture
    Jalowiczor, Jakub
    Rozhon, Jan
    Voznak, Miroslav
    SENSORS, 2021, 21 (09)
  • [27] Fog Computing for the Internet of Things: A Survey
    Puliafito, Carlo
    Mingozzi, Enzo
    Longo, Francesco
    Puliafito, Antonio
    Rana, Omer
    ACM TRANSACTIONS ON INTERNET TECHNOLOGY, 2019, 19 (02)
  • [28] Autonomic Resource Management for Fog Computing
    Tadakamalla, Uma
    Menasce, Daniel A.
    IEEE TRANSACTIONS ON CLOUD COMPUTING, 2022, 10 (04) : 2334 - 2350
  • [29] A queuing theory model for fog computing
    Mas, Lluis
    Vilaplana, Jordi
    Mateo, Jordi
    Solsona, Francesc
    JOURNAL OF SUPERCOMPUTING, 2022, 78 (08) : 11138 - 11155
  • [30] A Review on Fog Computing: Architecture, Fog with IoT, Algorithms and Research Challenges
    Sabireen, H. .
    Neelanarayanan, V. .
    ICT EXPRESS, 2021, 7 (02): : 162 - 176