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
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] End-to-end 5G network slice resource management and orchestration architecture
    Baba, Hiroki
    Hirai, Shiku
    Nakamura, Takayuki
    Kanemaru, Sho
    Takahashi, Kensuke
    Omoto, Taisuke
    Akiyama, Shinsaku
    Hirabaru, Senri
    PROCEEDINGS OF THE 2022 IEEE 8TH INTERNATIONAL CONFERENCE ON NETWORK SOFTWARIZATION (NETSOFT 2022): NETWORK SOFTWARIZATION COMING OF AGE: NEW CHALLENGES AND OPPORTUNITIES, 2022, : 269 - 271
  • [32] Poster: A Cross-Slice Resource Orchestration Framework for 5G Network Services
    Ramneek
    Hosein, Patrick
    Pack, Sangheon
    2023 IEEE 43RD INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS, ICDCS, 2023, : 1049 - 1050
  • [33] Multi-service Single Tenant 5G Fronthaul Resource Orchestration Framework based on Network Slicing
    Maule, Massimiliano
    Vardakas, John S.
    Kormentzas, Georgios
    Verikoukis, Christos
    2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), 2022, : 3417 - 3422
  • [34] Placement of Microservices-based IoT Applications in Fog Computing: A Taxonomy and Future Directions
    Pallewatta, Samodha
    Kostakos, Vassilis
    Buyya, Rajkumar
    ACM COMPUTING SURVEYS, 2023, 55 (14S)
  • [35] Agent composition for 5G management and orchestration
    Raisanen, Vilho
    2017 13TH INTERNATIONAL CONFERENCE ON NETWORK AND SERVICE MANAGEMENT (CNSM), 2017,
  • [36] 5G management and orchestration architecture framework
    Groenendijk J.
    Lan Z.
    Journal of ICT Standardization, 2019, 7 (02): : 81 - 91
  • [37] A Unifying Orchestration Operating Platform for 5G
    Manzalini, Antonio
    Di Girolamo, Marco
    Celozzi, Giuseppe
    Bruno, Fulvio
    Carullo, Giuliana
    Tambasco, Marco
    Carrozzo, Gino
    Risso, Fulvio
    Castellano, Gabriele
    GREEN, PERVASIVE, AND CLOUD COMPUTING (GPC 2017), 2017, 10232 : 252 - 266
  • [38] Provisioning big data applications as services on containerised cloud: a microservices-based approach
    Gao Jing
    Li Wubin
    Zhao Zhuofeng
    Han Yanbo
    INTERNATIONAL JOURNAL OF SERVICES TECHNOLOGY AND MANAGEMENT, 2020, 26 (2-3) : 167 - 181
  • [39] Microservice-based Management and Orchestration of 5G Core Network
    Zhu, Manhua
    Duan, Xuefei
    Tu, Haiyan
    Wang, Yunfeng
    Zhou, Guorong
    Jin, Xianmei
    Zhao, Liqiang
    2022 IEEE 33RD ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (IEEE PIMRC), 2022, : 609 - 615
  • [40] Cloud Native 5G: an Efficient Orchestration of Cloud Native 5G System
    Khichane, Abderaouf
    Fajjari, Ilhem
    Aitsaadi, Nadjib
    Gueroui, Mourad
    PROCEEDINGS OF THE IEEE/IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM 2022, 2022,