ROMA: Resource Orchestration for Microservices-based 5G Applications

被引:4
|
作者
Gholami, Anousheh [1 ,4 ]
Rao, Kunal [2 ]
Hsiung, Wang-Pin [3 ]
Po, Oliver [3 ]
Sankaradas, Murugan [2 ]
Chakradhar, Srimat [2 ]
机构
[1] Univ Maryland, College Pk, MD 20742 USA
[2] NEC Labs Amer, Princeton, NJ USA
[3] NEC Labs Amer, San Jose, CA USA
[4] NEC Labs Amer Inc, Princeton, NJ USA
来源
PROCEEDINGS OF THE IEEE/IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM 2022 | 2022年
关键词
resource orchestration; IoT; 5G; edge computing; microservices; system modelling and optimization;
D O I
10.1109/NOMS54207.2022.9789821
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
With the growth of 5G, Internet of Things (IoT), edge computing and cloud computing technologies, the infrastructure (compute and network) available to emerging applications (AR/VR, autonomous driving, industry 4.0, etc.) has become quite complex. There are multiple tiers of computing (IoT devices, near edge, far edge, cloud, etc.) that are connected with different types of networking technologies (LAN, LTE, 5G, MAN, WAN, etc.). Deployment and management of applications in such an environment is quite challenging. In this paper, we propose ROMA, which performs resource orchestration for microservices-based 5G applications in a dynamic, heterogeneous, multi-tiered compute and network fabric. We assume that only application-level requirements are known, and the detailed requirements of the individual microservices in the application are not specified. As part of our solution, ROMA identifies and leverages the coupling relationship between compute and network usage for various microservices and solves an optimization problem in order to appropriately identify how each microservice should be deployed in the complex, multi-tiered compute and network fabric, so that the end-to-end application requirements are optimally met. We implemented two real-world 5G applications in video surveillance and intelligent transportation system (ITS) domains. Through extensive experiments, we show that ROMA is able to save up to 90%, 55% and 44% compute and up to 80%, 95% and 75% network bandwidth for the surveillance (watchlist) and transportation application (person and car detection), respectively. This improvement is achieved while honoring the application performance requirements, and it is over an alternative scheme that employs a static and overprovisioned resource allocation strategy by ignoring the resource coupling relationships.
引用
收藏
页数:9
相关论文
共 50 条
  • [31] Virtual Resource Consolidation in the Edge for 5G Networks
    Kokkinos, P.
    Kretsis, A.
    Varvarigos, E.
    2018 IEEE 29TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC), 2018,
  • [32] Deployment of IoT applications on 5G Edge
    Kiss, Peter
    Reale, Anna
    Ferrari, Charles Jose
    Istenes, Zoltan
    2018 IEEE INTERNATIONAL CONFERENCE ON FUTURE IOT TECHNOLOGIES (FUTURE IOT), 2018,
  • [33] Collaborative Cloud - Edge: A Declarative API orchestration model for the NextGen 5G Core
    Ungureanu, Oana-Mihaela
    Vladeanu, Calin
    Kooij, Robert
    2021 15TH IEEE INTERNATIONAL CONFERENCE ON SERVICE-ORIENTED SYSTEM ENGINEERING (SOSE 2021), 2021, : 124 - 133
  • [34] Service Orchestration for Integrating Edge Computing and 5G Network: State of the Art and Challenges
    Guo, Yan
    Duan, Qiang
    Wang, Shangguang
    2020 IEEE WORLD CONGRESS ON SERVICES (SERVICES), 2020, : 55 - 60
  • [35] Opportunities for Applications Using 5G Networks: Requirements, Challenges, and Outlook
    Ding, Aaron Yi
    Janssen, Marijn
    PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND REMOTE SENSING (ICTRS 2018), 2018, : 27 - 34
  • [36] Evaluation of IoT and videosurveillance applications in a 5G Smart City: the Italian 5G experimentation in Prato
    Nizzi, Francesca
    Pecorella, Tommaso
    Bertini, Marco
    Fantacci, Romano
    Bastianini, Mattia
    Cerboni, Carlo
    Buzzigoli, Alessandra
    Gattoni, Massimiliano
    Fratini, Andrea
    2018 AEIT INTERNATIONAL ANNUAL CONFERENCE, 2018,
  • [37] Applications of Machine Learning in Resource Management for RAN-Slicing in 5G and Beyond Networks: A Survey
    Azimi, Yaser
    Yousefi, Saleh
    Kalbkhani, Hashem
    Kunz, Thomas
    IEEE ACCESS, 2022, 10 : 106581 - 106612
  • [38] Secure Chaos of 5G Wireless Communication System Based on IOT Applications
    ALRikabi, Haider TH. Salim
    Hazim, Hussein Tuama
    INTERNATIONAL JOURNAL OF ONLINE AND BIOMEDICAL ENGINEERING, 2022, 18 (12) : 89 - 105
  • [39] Algorithm for 5G Resource Management Optimization in Edge Computing
    Lieira, Douglas Dias
    Quessada, Matheus Sanches
    Cristiani, Andre Luis
    Meneguette, Rodolfo Ipolito
    IEEE LATIN AMERICA TRANSACTIONS, 2021, 19 (10) : 1772 - 1780
  • [40] Resource Allocation Schemes for 5G Network: A Systematic Review
    Kamal, Muhammad Ayoub
    Raza, Hafiz Wahab
    Alam, Muhammad Mansoor
    Su'ud, Mazliham Mohd
    Sajak, Aznida binti Abu Bakar
    SENSORS, 2021, 21 (19)