Edge Diagnostics Platform: Orchestration and Diagnosis Model for Edge Computing Infrastructure

被引:1
作者
Abdulmaksoud, Mohamed [1 ]
Dehadrai, Ninad [1 ]
Castrillon, Juan [1 ]
Sakr, Aly [1 ]
Schuster, Rolf [1 ]
机构
[1] Dortmund Univ Appl Sci & Arts, Dortmund, Germany
来源
2021 IEEE INTERNATIONAL CONFERENCE ON EDGE COMPUTING (EDGE 2021) | 2021年
关键词
Edge Computing; Cloud Computing; Network; Diagnostics; MEC; Match-making; Orchestration;
D O I
10.1109/EDGE53862.2021.00017
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The increasing demand for low-latency high-performance applications motivates the development of network and compute infrastructure. As an emerging paradigm, edge computing is becoming the chosen solution for many low-latency applications in many industries. However, the current orchestration and diagnostics methods do not fulfill the requirements of the new edge computing architectures. In contrast to cloud computing, edge applications are very sensitive to changes in the infrastructure. And thus, the orchestration and diagnosis of the infrastructure must be aware of the edge application's special needs. In this research work, we present a solution model: The Edge Diagnostics Platform. The platform has two main functions: Orchestration and Diagnosis. We show the design principles of the platform, how it can help with the orchestration and diagnosis of edge applications. Finally, we carry out practical experiments to show how the platform may be used to diagnose network and CPU problems. The results show practically accurate detection of network and CPU problems.
引用
收藏
页码:51 / 59
页数:9
相关论文
共 32 条
  • [1] Efficient Resource Allocation for Multi-tenant Monitoring of Edge Infrastructures
    Abderrahim, Mohamed
    Ouzzif, Meryem
    Guillouard, Karine
    Francois, Jerome
    Lebre, Adrien
    Prud'homme, Charles
    Lorca, Xavier
    [J]. 2019 27TH EUROMICRO INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND NETWORK-BASED PROCESSING (PDP), 2019, : 158 - 165
  • [2] A Holistic Monitoring Service for Fog/Edge Infrastructures: a Foresight Study
    Abderrahim, Mohamed
    Ouzzif, Meryem
    Guillouard, Karine
    Francois, Jerome
    Lebre, Adrien
    [J]. 2017 IEEE 5TH INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD (FICLOUD 2017), 2017, : 337 - 344
  • [3] [Anonymous], UBUNTU MANPAGE STRES
  • [4] Blakley J., 2020, SIMULATING EDGE COMP
  • [5] Castrillon J. P., 2021, DESIGN DEV EDGE INFR
  • [6] Castrillon J. P., 2021, IN PROGR
  • [7] Why Cloud Applications Are not Ready for the Edge (yet)
    Chanh Nguyen
    Mehta, Amardeep
    Klein, Cristian
    Elmroth, Erik
    [J]. SEC'19: PROCEEDINGS OF THE 4TH ACM/IEEE SYMPOSIUM ON EDGE COMPUTING, 2019, : 250 - 263
  • [8] Dahmen-Lhuissier S., MULTIACCESS EDGE COM
  • [9] EdgeBench: Benchmarking Edge Computing Platforms
    Das, Anirban
    Patterson, Stacy
    Wittie, Mike P.
    [J]. 2018 IEEE/ACM INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING COMPANION (UCC COMPANION), 2018, : 175 - 180
  • [10] An Application Placement Technique for Concurrent IoT Applications in Edge and Fog Computing Environments
    Goudarzi, Mohammad
    Wu, Huaming
    Palaniswami, Marimuthu
    Buyya, Rajkumar
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2021, 20 (04) : 1298 - 1311