Optimizing Service Placement for Microservice Architecture in Clouds

被引:16
|
作者
Hu, Yang [1 ,2 ]
de Laat, Cees [1 ]
Zhao, Zhiming [1 ]
机构
[1] Univ Amsterdam, Fac Sci, Informat Inst, NL-1098 XH Amsterdam, Netherlands
[2] Natl Univ Def Technol, Sch Comp Sci, Changsha 410073, Hunan, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2019年 / 9卷 / 21期
基金
欧盟地平线“2020”;
关键词
service placement; cluster scheduling; network optimization; resource management; microservice architecture; cloud computing; DEPLOYMENT;
D O I
10.3390/app9214663
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
As microservice architecture is becoming more popular than ever, developers intend to transform traditional monolithic applications into service-based applications (composed by a number of services). To deploy a service-based application in clouds, besides the resource demands of each service, the traffic demands between collaborative services are crucial for the overall performance. Poor handling of the traffic demands can result in severe performance degradation, such as high response time and jitter. However, current cluster schedulers fail to place services at the best possible machine, since they only consider the resource constraints but ignore the traffic demands between services. To address this problem, we propose a new approach to optimize the placement of service-based applications in clouds. The approach first partitions the application into several parts while keeping overall traffic between different parts to a minimum and then carefully packs the different parts into machines with respect to their resource demands and traffic demands. We implement a prototype scheduler and evaluate it with extensive experiments on testbed clusters. The results show that our approach outperforms existing container cluster schedulers and representative heuristics, leading to much less overall inter-machine traffic.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Service Dependency Graph Analysis in Microservice Architecture
    Gaidels, Edgars
    Kirikova, Marite
    [J]. PERSPECTIVES IN BUSINESS INFORMATICS RESEARCH, BIR 2020, 2020, 398 : 128 - 139
  • [2] OPTIMIZING SERVICE REPLICATION IN CLOUDS
    Bjoerkqvist, Mathias
    Chen, Lydia Y.
    Binder, Walter
    [J]. PROCEEDINGS OF THE 2011 WINTER SIMULATION CONFERENCE (WSC), 2011, : 3307 - 3317
  • [3] Crossover Service Fusion Approach Based on Microservice Architecture
    Guo, Siying
    Xu, Chao
    Chen, Shizhan
    Xue, Xiao
    Feng, Zhiyong
    Chen, Shiping
    [J]. 2019 IEEE INTERNATIONAL CONFERENCE ON WEB SERVICES (IEEE ICWS 2019), 2019, : 237 - 241
  • [4] Infrastructure Smart Service System Based on Microservice Architecture
    Li, Xiaojun
    Xi, Yue
    Zhu, Hehua
    Ling, Jiaxin
    Zhang, Qi
    [J]. INFORMATION TECHNOLOGY IN GEO-ENGINEERING, 2020, : 131 - 143
  • [5] Design of WeChat Service System Based on Microservice Architecture
    Wu, Sikai
    Wang, Xiao
    Zhu, Quanyin
    [J]. 3RD ANNUAL INTERNATIONAL CONFERENCE ON INFORMATION SYSTEM AND ARTIFICIAL INTELLIGENCE (ISAI2018), 2018, 1069
  • [6] ICN-based Service Discovery Mechanism for Microservice Architecture
    Long, Kim Bao
    Yang, HyunSik
    Kim, YoungHan
    [J]. 2017 NINTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS (ICUFN 2017), 2017, : 773 - 775
  • [7] Joint optimization of service request routing and instance placement in the microservice system
    Yu, Yinbo
    Yang, Jianfeng
    Guo, Chengcheng
    Zheng, Hong
    He, Jiancheng
    [J]. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2019, 147
  • [8] Dynamic Service Placement in Geographically Distributed Clouds
    Zhang, Qi
    Zhu, Quanyan
    Zhani, Mohamed Faten
    Boutaba, Raouf
    Hellerstein, Joseph L.
    [J]. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2013, 31 (12) : 762 - 772
  • [9] Dynamic Service Placement in Geographically Distributed Clouds
    Zhang, Qi
    Zhu, Quanyan
    Zhani, Mohamed Faten
    Boutaba, Raouf
    [J]. 2012 IEEE 32ND INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS), 2012, : 526 - 535
  • [10] On Uncoordinated Service Placement in Edge-Clouds
    Ascigil, Onur
    Phan, Truong Khoa
    Tasiopoulos, Argyrios G.
    Sourlas, Vasilis
    Psaras, Ioannis
    Pavlou, George
    [J]. 2017 9TH IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM), 2017, : 41 - 48