IntMA: Dynamic Interaction-aware resource allocation for containerized microservices in cloud environments
The Information Technology sector has undergone tremendous changes arising due to the emergence and prevalence of Cloud Computing. Microservice Architectures have also been attracting attention from several industries and researchers. Due to the suitability of microservices for the Cloud environment...
Saved in:
| Published in | Journal of systems architecture Vol. 111; p. 101785 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.12.2020
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 1383-7621 1873-6165 |
| DOI | 10.1016/j.sysarc.2020.101785 |
Cover
Loading…
| Abstract | The Information Technology sector has undergone tremendous changes arising due to the emergence and prevalence of Cloud Computing. Microservice Architectures have also been attracting attention from several industries and researchers. Due to the suitability of microservices for the Cloud environments, an increasing number of Cloud applications are now provided as microservices. However, this transition to microservices brings a wide range of infrastructural orchestration challenges. Though several research works have discussed the engineering of microservice-based applications, there is an inevitable need for research on handling the operational phases of the microservice components. Microservice application deployment in containerized datacenters must be optimized to enhance the overall system performance. In this research work, the deployment of microservice application modules on the Cloud infrastructure is first modelled as a Binary Quadratic Programming Problem. In order to reduce the adverse impact of communication latencies on the response time, the interaction pattern between the microservice components is modelled as an undirected doubly weighted complete Interaction Graph. A novel, robust heuristic approach IntMA is also proposed for deploying the microservices in an interaction-aware manner with the aid of the interaction information obtained from the Interaction Graph. The proposed allocation policies are implemented in Kubernetes. The effectiveness of the proposed approach is evaluated on the Google Cloud Platform, using different microservice reference applications. Experimental results indicate that the proposed approach improves the response time and throughput of the microservice-based systems. |
|---|---|
| AbstractList | The Information Technology sector has undergone tremendous changes arising due to the emergence and prevalence of Cloud Computing. Microservice Architectures have also been attracting attention from several industries and researchers. Due to the suitability of microservices for the Cloud environments, an increasing number of Cloud applications are now provided as microservices. However, this transition to microservices brings a wide range of infrastructural orchestration challenges. Though several research works have discussed the engineering of microservice-based applications, there is an inevitable need for research on handling the operational phases of the microservice components. Microservice application deployment in containerized datacenters must be optimized to enhance the overall system performance. In this research work, the deployment of microservice application modules on the Cloud infrastructure is first modelled as a Binary Quadratic Programming Problem. In order to reduce the adverse impact of communication latencies on the response time, the interaction pattern between the microservice components is modelled as an undirected doubly weighted complete Interaction Graph. A novel, robust heuristic approach IntMA is also proposed for deploying the microservices in an interaction-aware manner with the aid of the interaction information obtained from the Interaction Graph. The proposed allocation policies are implemented in Kubernetes. The effectiveness of the proposed approach is evaluated on the Google Cloud Platform, using different microservice reference applications. Experimental results indicate that the proposed approach improves the response time and throughput of the microservice-based systems. |
| ArticleNumber | 101785 |
| Author | Chandrasekaran, K. Joseph, Christina Terese |
| Author_xml | – sequence: 1 givenname: Christina Terese surname: Joseph fullname: Joseph, Christina Terese email: xtina1232@gmail.com organization: Distributed & Cloud Computing Lab, Department of Computer Science and Engineering, National Institute of Technology Karnataka, Surathkal, 575025, India – sequence: 2 givenname: K. surname: Chandrasekaran fullname: Chandrasekaran, K. organization: Distributed & Cloud Computing Lab, Department of Computer Science and Engineering, National Institute of Technology Karnataka, Surathkal, 575025, India |
| BookMark | eNqFkMtOwzAQRS1UJNrCH7DwD6TEDnHSLpCq8qpUxAbW1nQykRylNrLTovL1OA0rFrCa57mauRM2ss4SY9cinYlUqJtmFo4BPM5kKk-toszP2FiURZYoofJRzLMySwolxQWbhNCkaZrnQo5Zs7bdy3LB748WdgZ5LMkDdsbZBD7BE_cU3N4jcWhbh9BPeO08R2c7MJa8-aKKR9a7QP5gkAI3lmPr9hUnezDe2R3ZLlyy8xraQFc_ccreHx_eVs_J5vVpvVpuEsxS1SWiVHOFxRyqraxFLQmllNsacJ6DBMCtIqwwFwDxHYoLpaS4WOUykxUiZFO2GHT7i4KnWqPpTnd3HkyrRap713SjB9d075oeXIvw7S_4w5sd-ON_2N2AUXzsYMjrgIYsUmU8YacrZ_4W-AYm-I9d |
| CitedBy_id | crossref_primary_10_1002_spe_3211 crossref_primary_10_1109_TCC_2022_3161900 crossref_primary_10_1016_j_sysarc_2020_101957 crossref_primary_10_1002_cpe_8035 crossref_primary_10_1109_OJCOMS_2024_3399015 crossref_primary_10_2139_ssrn_4492378 crossref_primary_10_1109_ACCESS_2024_3502538 crossref_primary_10_1016_j_future_2024_03_010 crossref_primary_10_1016_j_sysarc_2020_101972 crossref_primary_10_1007_s10723_024_09760_8 crossref_primary_10_1016_j_sysarc_2021_102071 crossref_primary_10_1007_s10586_024_04615_z crossref_primary_10_1016_j_jss_2023_111857 crossref_primary_10_3233_WEB_210474 crossref_primary_10_1007_s10586_024_04824_6 crossref_primary_10_1109_TPDS_2023_3236447 crossref_primary_10_1049_iet_sen_2019_0338 crossref_primary_10_1007_s00607_021_01045_2 crossref_primary_10_1109_TNSM_2024_3483634 crossref_primary_10_32604_cmc_2023_032474 crossref_primary_10_1016_j_engappai_2024_109745 crossref_primary_10_1016_j_future_2024_107495 crossref_primary_10_1016_j_icte_2023_06_006 crossref_primary_10_1016_j_sysarc_2023_103009 crossref_primary_10_1016_j_cosrev_2023_100598 crossref_primary_10_1109_TII_2024_3424347 crossref_primary_10_1080_03772063_2023_2205864 crossref_primary_10_1109_TMC_2024_3396510 crossref_primary_10_1016_j_sysarc_2021_102064 crossref_primary_10_1109_TSC_2023_3292362 crossref_primary_10_1002_spe_3317 crossref_primary_10_1080_17517575_2022_2069478 crossref_primary_10_1109_TSUSC_2024_3371544 crossref_primary_10_1109_TPDS_2022_3150311 crossref_primary_10_1155_2022_7146716 crossref_primary_10_1109_JIOT_2023_3289228 crossref_primary_10_12720_jait_14_5_991_1002 crossref_primary_10_1109_ACCESS_2020_3033019 crossref_primary_10_1109_TSC_2022_3230699 |
| Cites_doi | 10.1016/j.jnca.2019.04.003 10.1109/ACCESS.2019.2924414 10.1007/s11280-018-0562-5 10.1109/MCC.2014.51 10.1016/j.sysarc.2019.08.004 10.1016/j.compchemeng.2014.04.013 10.1109/JIOT.2018.2889511 10.1016/j.jnca.2018.07.003 10.1016/j.sysarc.2018.03.002 10.1109/JIOT.2018.2792940 10.1016/j.sysarc.2016.12.007 10.1109/MCC.2017.4250939 10.1186/s13673-017-0124-3 10.1016/j.ejor.2006.09.028 10.1007/s10723-017-9419-x 10.1007/s10922-014-9307-7 10.1007/s10586-018-02890-1 10.1016/j.sysarc.2019.08.005 10.1109/MNET.2017.1700275 10.1007/978-1-4842-3012-1_2 10.1016/j.future.2019.04.008 10.1002/spe.2660 10.1109/MCC.2016.112 |
| ContentType | Journal Article |
| Copyright | 2020 Elsevier B.V. |
| Copyright_xml | – notice: 2020 Elsevier B.V. |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.sysarc.2020.101785 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1873-6165 |
| ExternalDocumentID | 10_1016_j_sysarc_2020_101785 S1383762120300758 |
| GroupedDBID | --K --M -~X .DC .~1 0R~ 1B1 1~. 1~5 29L 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXUO AAYFN ABBOA ABFNM ABFRF ABJNI ABMAC ABXDB ABYKQ ACDAQ ACGFO ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADJOM ADMUD ADTZH AEBSH AECPX AEFWE AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BKOMP BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HVGLF HZ~ IHE J1W JJJVA KOM M41 MO0 MS~ N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. PQQKQ Q38 R2- RIG ROL RPZ RXW SBC SDF SDG SDP SES SEW SPC SPCBC SST SSV SSZ T5K TAE TN5 U5U UHS ~G- AATTM AAXKI AAYWO AAYXX ABWVN ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AFXIZ AGCQF AGQPQ AGRNS AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP BNPGV CITATION SSH |
| ID | FETCH-LOGICAL-c306t-18696c79adb2f1f2ec222bfac95a2aacb6ecdc51aa762e1f282e2f1d5232dcca3 |
| IEDL.DBID | .~1 |
| ISSN | 1383-7621 |
| IngestDate | Tue Jul 01 00:29:17 EDT 2025 Thu Apr 24 23:03:48 EDT 2025 Fri Feb 23 02:46:43 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Cloud computing Microservice placement Performance optimization Service oriented computing Container orchestration |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c306t-18696c79adb2f1f2ec222bfac95a2aacb6ecdc51aa762e1f282e2f1d5232dcca3 |
| ParticipantIDs | crossref_citationtrail_10_1016_j_sysarc_2020_101785 crossref_primary_10_1016_j_sysarc_2020_101785 elsevier_sciencedirect_doi_10_1016_j_sysarc_2020_101785 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | December 2020 2020-12-00 |
| PublicationDateYYYYMMDD | 2020-12-01 |
| PublicationDate_xml | – month: 12 year: 2020 text: December 2020 |
| PublicationDecade | 2020 |
| PublicationTitle | Journal of systems architecture |
| PublicationYear | 2020 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Soltesz, Pötzl, Fiuczynski, Bavier, Peterson (bib0006) 2007; vol. 41 Štefanič, Cigale, Jones, Knight, Taylor, Istrate, Suciu, Ulisses, Stankovski, Taherizadeh (bib0017) 2019; 99 Jaeger: Open Source, End-to-End Distributed Tracing, (https://www.jaegertracing.io/), Accessed: 29/8/2018. Martin, Kandasamy, Chandrasekaran (bib0007) 2018; 8 Goldschmidt, Hauck-Stattelmann, Malakuti, Grüner (bib0020) 2018; 84 Accessed: 29/8/2018. Lera, Guerrero, Juiz (bib0043) 2018; 6 Guerrero, Lera, Juiz (bib0013) 2018 Zheng, Zheng, Zhang, Deng, Dong, Zhang, Liu (bib0027) 2019; 22 Wan, Guan, Wang, Bai, Choi (bib0026) 2018; 119 Bogner, Zimmermann, Wagner (bib0002) 2018 Lin, Xi, Bai, Wu (bib0014) 2019; 7 Socks shop: Microservices demo Shojaiemehr, Rahmani, Qader (bib0001) 2019; 99 Pallewatta, Kostakos, Buyya (bib0011) 2019 Docker Kang, Choi, Kim, Hwang, Youn (bib0032) 2016 M.A. Rodriguez, R. Buyya, Container-based cluster orchestration systems: ataxonomy and future directions, arXiv GoogleCloudPlatform, Googlecloudplatform/microservices-demo, 2019, Accessed: 13/3/2019, https://github.com/GoogleCloudPlatform/microservices-demo. Tao, Wang, Xu, Chen (bib0030) 2017 Kitajima, Matsuoka (bib0049) 2017 Zhang, Xu, Wang, Li, Li, Cao (bib0033) 2018; 32 Fazio, Celesti, Ranjan, Liu, Chen, Villari (bib0010) 2016; 3 Bookinfo Application Guerrero, Lera, Juiz (bib0012) 2018; 16 Jennings, Stadler (bib0024) 2015; 23 An Open Source Load Testing Tool., Accessed: 29/8/2018, https://locust.io/. Pod Lifecycle, Accessed: 29/8/2018, https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/. R. Buyya, M.A. Rodriguez, A.N. Toosi, J. Park, Cost-efficient orchestration of containers in clouds: a vision, architectural elements, and future directions, arXiv Alshuqayran, Ali, Evans (bib0022) 2016 Kaewkasi, Chuenmuneewong (bib0031) 2017 Vural, Koyuncu, Guney (bib0023) 2017 Production-Grade Container Orchestration, (https://kubernetes.io/), Accessed: 29/8/2018. Netaji, Bhole (bib0015) 2019 Gannon, Barga, Sundaresan (bib0005) 2017; 4 Newman (bib0004) 2015 Microservices Zhou, Wang, Cong, Lu, Wei, Chen (bib0019) 2019; 100 Prometheus-Monitoring System & Time Series Database, (https://prometheus.io/), Accessed: 29/8/2018. Di Francesco, Malavolta, Lago (bib0021) 2017 Casalicchio (bib0009) 2019 Wen, Lin, Yang, Ji, Romanovsky, Lin, Xu (bib0016) 2019 Hedengren, Shishavan, Powell, Edgar (bib0035) 2014; 70 Google Cloud Platform Filip, Pop, Serbanescu, Choi (bib0025) 2018 Netto, Lung, Correia, Luiz, de Souza (bib0042) 2017; 73 (2018). Grafana-the Open Platform for Analytics and Monitoring, (https://grafana.com/), Accessed: 29/8/2018. Caprara (bib0034) 2008; 187 Bernstein (bib0008) 2014; 1 Adhikari, Srirama (bib0028) 2019; 137 Newman (10.1016/j.sysarc.2020.101785_bib0004) 2015 Netto (10.1016/j.sysarc.2020.101785_bib0042) 2017; 73 Jennings (10.1016/j.sysarc.2020.101785_bib0024) 2015; 23 Zheng (10.1016/j.sysarc.2020.101785_bib0027) 2019; 22 Caprara (10.1016/j.sysarc.2020.101785_bib0034) 2008; 187 Shojaiemehr (10.1016/j.sysarc.2020.101785_bib0001) 2019; 99 Zhou (10.1016/j.sysarc.2020.101785_bib0019) 2019; 100 Zhang (10.1016/j.sysarc.2020.101785_bib0033) 2018; 32 10.1016/j.sysarc.2020.101785_bib0029 Martin (10.1016/j.sysarc.2020.101785_bib0007) 2018; 8 Gannon (10.1016/j.sysarc.2020.101785_bib0005) 2017; 4 Adhikari (10.1016/j.sysarc.2020.101785_bib0028) 2019; 137 Guerrero (10.1016/j.sysarc.2020.101785_bib0013) 2018 Wan (10.1016/j.sysarc.2020.101785_bib0026) 2018; 119 Di Francesco (10.1016/j.sysarc.2020.101785_bib0021) 2017 Casalicchio (10.1016/j.sysarc.2020.101785_bib0009) 2019 Hedengren (10.1016/j.sysarc.2020.101785_bib0035) 2014; 70 10.1016/j.sysarc.2020.101785_bib0038 10.1016/j.sysarc.2020.101785_bib0039 Kang (10.1016/j.sysarc.2020.101785_bib0032) 2016 10.1016/j.sysarc.2020.101785_bib0036 10.1016/j.sysarc.2020.101785_bib0037 Bernstein (10.1016/j.sysarc.2020.101785_bib0008) 2014; 1 Soltesz (10.1016/j.sysarc.2020.101785_bib0006) 2007; vol. 41 Pallewatta (10.1016/j.sysarc.2020.101785_bib0011) 2019 Kaewkasi (10.1016/j.sysarc.2020.101785_bib0031) 2017 Lera (10.1016/j.sysarc.2020.101785_bib0043) 2018; 6 Goldschmidt (10.1016/j.sysarc.2020.101785_bib0020) 2018; 84 Tao (10.1016/j.sysarc.2020.101785_bib0030) 2017 10.1016/j.sysarc.2020.101785_bib0045 10.1016/j.sysarc.2020.101785_bib0046 10.1016/j.sysarc.2020.101785_bib0003 Guerrero (10.1016/j.sysarc.2020.101785_bib0012) 2018; 16 Netaji (10.1016/j.sysarc.2020.101785_bib0015) 2019 10.1016/j.sysarc.2020.101785_bib0047 10.1016/j.sysarc.2020.101785_bib0048 10.1016/j.sysarc.2020.101785_bib0041 Lin (10.1016/j.sysarc.2020.101785_bib0014) 2019; 7 Fazio (10.1016/j.sysarc.2020.101785_bib0010) 2016; 3 10.1016/j.sysarc.2020.101785_bib0044 Štefanič (10.1016/j.sysarc.2020.101785_bib0017) 2019; 99 10.1016/j.sysarc.2020.101785_bib0040 Alshuqayran (10.1016/j.sysarc.2020.101785_bib0022) 2016 Vural (10.1016/j.sysarc.2020.101785_bib0023) 2017 10.1016/j.sysarc.2020.101785_bib0018 Bogner (10.1016/j.sysarc.2020.101785_bib0002) 2018 Wen (10.1016/j.sysarc.2020.101785_bib0016) 2019 Filip (10.1016/j.sysarc.2020.101785_bib0025) 2018 Kitajima (10.1016/j.sysarc.2020.101785_bib0049) 2017 |
| References_xml | – reference: Bookinfo Application, ( – start-page: 2428 year: 2016 end-page: 2431 ident: bib0032 article-title: Workload-aware resource management for energy efficient heterogeneous docker containers publication-title: Region 10 Conference (TENCON), 2016 IEEE – year: 2019 ident: bib0009 article-title: A study on performance measures for auto-scaling cpu-intensive containerized applications publication-title: Cluster Comput – volume: 22 start-page: 275 year: 2019 end-page: 293 ident: bib0027 article-title: Smartvm: a sla-aware microservice deployment framework publication-title: World Wide Web – start-page: 1 year: 2018 end-page: 28 ident: bib0013 article-title: Resource optimization of container orchestration: a case study in multi-cloud microservices-based applications publication-title: J. Supercomput. – reference: Docker, ( – reference: Jaeger: Open Source, End-to-End Distributed Tracing, (https://www.jaegertracing.io/), Accessed: 29/8/2018. – reference: R. Buyya, M.A. Rodriguez, A.N. Toosi, J. Park, Cost-efficient orchestration of containers in clouds: a vision, architectural elements, and future directions, arXiv: – volume: 119 start-page: 97 year: 2018 end-page: 109 ident: bib0026 article-title: Application deployment using microservice and docker containers: framework and optimization publication-title: J. Netw. Comput. Appl. – volume: 137 start-page: 35 year: 2019 end-page: 61 ident: bib0028 article-title: Multi-objective accelerated particle swarm optimization with a container-based scheduling for internet-of-things in cloud environment publication-title: J. Netw. Comput. Appl. – volume: 8 start-page: 1 year: 2018 ident: bib0007 article-title: Exploring the support for high performance applications in the container runtime environment publication-title: Hum.-Centric Comput. Inf. Sci. – volume: 100 start-page: 101631 year: 2019 ident: bib0019 article-title: Cost and makespan-aware workflow scheduling in hybrid clouds publication-title: J. Syst. Archit. – volume: vol. 41 start-page: 275 year: 2007 end-page: 287 ident: bib0006 article-title: Container-based operating system virtualization: a scalable, high-performance alternative to hypervisors publication-title: ACM SIGOPS Operating Systems Review – year: 2018 ident: bib0025 article-title: Microservices scheduling model over heterogeneous cloud-edge environments as support for IoT applications publication-title: IEEE Internet Things J. – volume: 7 start-page: 83088 year: 2019 end-page: 83100 ident: bib0014 article-title: Ant colony algorithm for multi-objective optimization of container-based microservice scheduling in cloud publication-title: IEEE Access – reference: Pod Lifecycle, Accessed: 29/8/2018, https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/. – year: 2019 ident: bib0011 article-title: Microservices-based IoT application placement within heterogeneous and resource constrained fog computing environments publication-title: 12th International Conference on Utility and Cloud Computing (UCC) – start-page: 203 year: 2017 end-page: 217 ident: bib0023 article-title: A systematic literature review on microservices publication-title: International Conference on Computational Science and Its Applications – reference: (2018). – volume: 70 start-page: 133 year: 2014 end-page: 148 ident: bib0035 article-title: Nonlinear modeling, estimation and predictive control in apmonitor publication-title: Comput. Chem. Eng. – start-page: 61 year: 2017 end-page: 67 ident: bib0030 article-title: Dynamic resource allocation algorithm for container-based service computing publication-title: 2017 IEEE 13th International Symposium on Autonomous Decentralized System (ISADS) – year: 2015 ident: bib0004 article-title: Building Microservices - Designing Fine-Grained Systems, 1st Edition – reference: Microservices, ( – volume: 3 start-page: 81 year: 2016 end-page: 88 ident: bib0010 article-title: Open issues in scheduling microservices in the cloud publication-title: IEEE Cloud Comput. – start-page: 21 year: 2017 end-page: 30 ident: bib0021 article-title: Research on architecting microservices: trends, focus, and potential for industrial adoption publication-title: Software Architecture (ICSA), 2017 IEEE International Conference on – reference: Socks shop: Microservices demo, ( – volume: 32 start-page: 138 year: 2018 end-page: 143 ident: bib0033 article-title: Going fast and fair: latency optimization for cloud-based service chains publication-title: IEEE Netw. – year: 2019 ident: bib0016 article-title: Ga-par: dependable microservice orchestration framework for geo-distributed clouds publication-title: IEEE Trans. Parallel Distrib. Syst. – reference: GoogleCloudPlatform, Googlecloudplatform/microservices-demo, 2019, Accessed: 13/3/2019, https://github.com/GoogleCloudPlatform/microservices-demo. – volume: 6 start-page: 3641 year: 2018 end-page: 3651 ident: bib0043 article-title: Availability-aware service placement policy in fog computing based on graph partitions publication-title: IEEE Internet Things J. – volume: 23 start-page: 567 year: 2015 end-page: 619 ident: bib0024 article-title: Resource management in clouds: survey and research challenges publication-title: J. Netw. Syst. Manag. – year: 2018 ident: bib0002 article-title: Analyzing the relevance of SOA patterns for microservice-based systems publication-title: Proceedings of the 10th Central European Workshop on Services and their Composition (ZEUS’18). CEUR-WS. org – year: 2019 ident: bib0015 article-title: Optimal container resource allocation in cloud architecture: a new hybrid model publication-title: J. King Saud Univ. – volume: 99 start-page: 197 year: 2019 end-page: 212 ident: bib0017 article-title: Switch workbench: a novel approach for the development and deployment of time-critical microservice-based cloud-native applications publication-title: Fut. Gener. Comput. Syst. – volume: 84 start-page: 28 year: 2018 end-page: 36 ident: bib0020 article-title: Container-based architecture for flexible industrial control applications publication-title: J. Syst. Archit. – reference: Google Cloud Platform, ( – reference: ), Accessed: 29/8/2018. – start-page: 229 year: 2017 end-page: 237 ident: bib0049 article-title: Inferring calling relationship based on external observation for microservice architecture publication-title: International Conference on Service-Oriented Computing – reference: , Accessed: 29/8/2018. – reference: Prometheus-Monitoring System & Time Series Database, (https://prometheus.io/), Accessed: 29/8/2018. – reference: M.A. Rodriguez, R. Buyya, Container-based cluster orchestration systems: ataxonomy and future directions, arXiv: – volume: 187 start-page: 1494 year: 2008 end-page: 1503 ident: bib0034 article-title: Constrained 0–1 quadratic programming: basic approaches and extensions publication-title: Eur. J. Oper. Res. – volume: 16 start-page: 113 year: 2018 end-page: 135 ident: bib0012 article-title: Genetic algorithm for multi-objective optimization of container allocation in cloud architecture publication-title: J. Grid Comput. – reference: An Open Source Load Testing Tool., Accessed: 29/8/2018, https://locust.io/. – reference: Production-Grade Container Orchestration, (https://kubernetes.io/), Accessed: 29/8/2018. – volume: 1 start-page: 81 year: 2014 end-page: 84 ident: bib0008 article-title: Containers and cloud: from lxc to docker to kubernetes publication-title: IEEE Cloud Comput. – volume: 73 start-page: 53 year: 2017 end-page: 59 ident: bib0042 article-title: State machine replication in containers managed by kubernetes publication-title: J. Syst. Archit. – volume: 99 start-page: 101632 year: 2019 ident: bib0001 article-title: Automated negotiation for ensuring composite service requirements in cloud computing publication-title: J. Syst. Archit. – start-page: 44 year: 2016 end-page: 51 ident: bib0022 article-title: A systematic mapping study in microservice architecture publication-title: Service-Oriented Computing and Applications (SOCA), 2016 IEEE 9th International Conference on – start-page: 254 year: 2017 end-page: 259 ident: bib0031 article-title: Improvement of container scheduling for docker using ant colony optimization publication-title: Knowledge and Smart Technology (KST), 2017 9th International Conference on – reference: Grafana-the Open Platform for Analytics and Monitoring, (https://grafana.com/), Accessed: 29/8/2018. – volume: 4 start-page: 16 year: 2017 end-page: 21 ident: bib0005 article-title: Cloud-native applications publication-title: IEEE Cloud Comput. – ident: 10.1016/j.sysarc.2020.101785_bib0003 – volume: 137 start-page: 35 year: 2019 ident: 10.1016/j.sysarc.2020.101785_bib0028 article-title: Multi-objective accelerated particle swarm optimization with a container-based scheduling for internet-of-things in cloud environment publication-title: J. Netw. Comput. Appl. doi: 10.1016/j.jnca.2019.04.003 – start-page: 61 year: 2017 ident: 10.1016/j.sysarc.2020.101785_bib0030 article-title: Dynamic resource allocation algorithm for container-based service computing – volume: 7 start-page: 83088 year: 2019 ident: 10.1016/j.sysarc.2020.101785_bib0014 article-title: Ant colony algorithm for multi-objective optimization of container-based microservice scheduling in cloud publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2924414 – volume: 22 start-page: 275 issue: 1 year: 2019 ident: 10.1016/j.sysarc.2020.101785_bib0027 article-title: Smartvm: a sla-aware microservice deployment framework publication-title: World Wide Web doi: 10.1007/s11280-018-0562-5 – year: 2019 ident: 10.1016/j.sysarc.2020.101785_bib0016 article-title: Ga-par: dependable microservice orchestration framework for geo-distributed clouds publication-title: IEEE Trans. Parallel Distrib. Syst. – ident: 10.1016/j.sysarc.2020.101785_bib0036 – volume: 1 start-page: 81 issue: 3 year: 2014 ident: 10.1016/j.sysarc.2020.101785_bib0008 article-title: Containers and cloud: from lxc to docker to kubernetes publication-title: IEEE Cloud Comput. doi: 10.1109/MCC.2014.51 – volume: 100 start-page: 101631 year: 2019 ident: 10.1016/j.sysarc.2020.101785_bib0019 article-title: Cost and makespan-aware workflow scheduling in hybrid clouds publication-title: J. Syst. Archit. doi: 10.1016/j.sysarc.2019.08.004 – volume: 70 start-page: 133 year: 2014 ident: 10.1016/j.sysarc.2020.101785_bib0035 article-title: Nonlinear modeling, estimation and predictive control in apmonitor publication-title: Comput. Chem. Eng. doi: 10.1016/j.compchemeng.2014.04.013 – ident: 10.1016/j.sysarc.2020.101785_bib0046 – start-page: 229 year: 2017 ident: 10.1016/j.sysarc.2020.101785_bib0049 article-title: Inferring calling relationship based on external observation for microservice architecture – volume: 6 start-page: 3641 issue: 2 year: 2018 ident: 10.1016/j.sysarc.2020.101785_bib0043 article-title: Availability-aware service placement policy in fog computing based on graph partitions publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2018.2889511 – volume: 119 start-page: 97 year: 2018 ident: 10.1016/j.sysarc.2020.101785_bib0026 article-title: Application deployment using microservice and docker containers: framework and optimization publication-title: J. Netw. Comput. Appl. doi: 10.1016/j.jnca.2018.07.003 – ident: 10.1016/j.sysarc.2020.101785_bib0039 – ident: 10.1016/j.sysarc.2020.101785_bib0041 – volume: 84 start-page: 28 year: 2018 ident: 10.1016/j.sysarc.2020.101785_bib0020 article-title: Container-based architecture for flexible industrial control applications publication-title: J. Syst. Archit. doi: 10.1016/j.sysarc.2018.03.002 – ident: 10.1016/j.sysarc.2020.101785_bib0045 – year: 2019 ident: 10.1016/j.sysarc.2020.101785_bib0011 article-title: Microservices-based IoT application placement within heterogeneous and resource constrained fog computing environments – year: 2018 ident: 10.1016/j.sysarc.2020.101785_bib0025 article-title: Microservices scheduling model over heterogeneous cloud-edge environments as support for IoT applications publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2018.2792940 – year: 2019 ident: 10.1016/j.sysarc.2020.101785_bib0015 article-title: Optimal container resource allocation in cloud architecture: a new hybrid model publication-title: J. King Saud Univ. – volume: 73 start-page: 53 year: 2017 ident: 10.1016/j.sysarc.2020.101785_bib0042 article-title: State machine replication in containers managed by kubernetes publication-title: J. Syst. Archit. doi: 10.1016/j.sysarc.2016.12.007 – volume: 4 start-page: 16 issue: 5 year: 2017 ident: 10.1016/j.sysarc.2020.101785_bib0005 article-title: Cloud-native applications publication-title: IEEE Cloud Comput. doi: 10.1109/MCC.2017.4250939 – volume: 8 start-page: 1 issue: 1 year: 2018 ident: 10.1016/j.sysarc.2020.101785_bib0007 article-title: Exploring the support for high performance applications in the container runtime environment publication-title: Hum.-Centric Comput. Inf. Sci. doi: 10.1186/s13673-017-0124-3 – ident: 10.1016/j.sysarc.2020.101785_bib0018 – volume: 187 start-page: 1494 issue: 3 year: 2008 ident: 10.1016/j.sysarc.2020.101785_bib0034 article-title: Constrained 0–1 quadratic programming: basic approaches and extensions publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2006.09.028 – volume: 16 start-page: 113 issue: 1 year: 2018 ident: 10.1016/j.sysarc.2020.101785_bib0012 article-title: Genetic algorithm for multi-objective optimization of container allocation in cloud architecture publication-title: J. Grid Comput. doi: 10.1007/s10723-017-9419-x – ident: 10.1016/j.sysarc.2020.101785_bib0040 – volume: 23 start-page: 567 issue: 3 year: 2015 ident: 10.1016/j.sysarc.2020.101785_bib0024 article-title: Resource management in clouds: survey and research challenges publication-title: J. Netw. Syst. Manag. doi: 10.1007/s10922-014-9307-7 – start-page: 21 year: 2017 ident: 10.1016/j.sysarc.2020.101785_bib0021 article-title: Research on architecting microservices: trends, focus, and potential for industrial adoption – year: 2019 ident: 10.1016/j.sysarc.2020.101785_bib0009 article-title: A study on performance measures for auto-scaling cpu-intensive containerized applications publication-title: Cluster Comput doi: 10.1007/s10586-018-02890-1 – ident: 10.1016/j.sysarc.2020.101785_bib0044 – ident: 10.1016/j.sysarc.2020.101785_bib0048 – volume: vol. 41 start-page: 275 year: 2007 ident: 10.1016/j.sysarc.2020.101785_bib0006 article-title: Container-based operating system virtualization: a scalable, high-performance alternative to hypervisors – start-page: 203 year: 2017 ident: 10.1016/j.sysarc.2020.101785_bib0023 article-title: A systematic literature review on microservices – volume: 99 start-page: 101632 year: 2019 ident: 10.1016/j.sysarc.2020.101785_bib0001 article-title: Automated negotiation for ensuring composite service requirements in cloud computing publication-title: J. Syst. Archit. doi: 10.1016/j.sysarc.2019.08.005 – year: 2018 ident: 10.1016/j.sysarc.2020.101785_bib0002 article-title: Analyzing the relevance of SOA patterns for microservice-based systems – year: 2015 ident: 10.1016/j.sysarc.2020.101785_bib0004 – volume: 32 start-page: 138 issue: 2 year: 2018 ident: 10.1016/j.sysarc.2020.101785_bib0033 article-title: Going fast and fair: latency optimization for cloud-based service chains publication-title: IEEE Netw. doi: 10.1109/MNET.2017.1700275 – ident: 10.1016/j.sysarc.2020.101785_bib0037 – ident: 10.1016/j.sysarc.2020.101785_bib0038 doi: 10.1007/978-1-4842-3012-1_2 – start-page: 2428 year: 2016 ident: 10.1016/j.sysarc.2020.101785_bib0032 article-title: Workload-aware resource management for energy efficient heterogeneous docker containers – volume: 99 start-page: 197 year: 2019 ident: 10.1016/j.sysarc.2020.101785_bib0017 article-title: Switch workbench: a novel approach for the development and deployment of time-critical microservice-based cloud-native applications publication-title: Fut. Gener. Comput. Syst. doi: 10.1016/j.future.2019.04.008 – ident: 10.1016/j.sysarc.2020.101785_bib0029 doi: 10.1002/spe.2660 – start-page: 254 year: 2017 ident: 10.1016/j.sysarc.2020.101785_bib0031 article-title: Improvement of container scheduling for docker using ant colony optimization – start-page: 44 year: 2016 ident: 10.1016/j.sysarc.2020.101785_bib0022 article-title: A systematic mapping study in microservice architecture – volume: 3 start-page: 81 issue: 5 year: 2016 ident: 10.1016/j.sysarc.2020.101785_bib0010 article-title: Open issues in scheduling microservices in the cloud publication-title: IEEE Cloud Comput. doi: 10.1109/MCC.2016.112 – ident: 10.1016/j.sysarc.2020.101785_bib0047 – start-page: 1 year: 2018 ident: 10.1016/j.sysarc.2020.101785_bib0013 article-title: Resource optimization of container orchestration: a case study in multi-cloud microservices-based applications publication-title: J. Supercomput. |
| SSID | ssj0005512 |
| Score | 2.4303026 |
| Snippet | The Information Technology sector has undergone tremendous changes arising due to the emergence and prevalence of Cloud Computing. Microservice Architectures... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 101785 |
| SubjectTerms | Cloud computing Container orchestration Microservice placement Performance optimization Service oriented computing |
| Title | IntMA: Dynamic Interaction-aware resource allocation for containerized microservices in cloud environments |
| URI | https://dx.doi.org/10.1016/j.sysarc.2020.101785 |
| Volume | 111 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LS8NAEF5KvXjxLdZH2YPXtWaTbFNvpVqq0l600FvYJ6TUtLQpogd_u7PZjVQQBY8JsxBmJ_PY_b4ZhC5DATlDYjoklGFIIskNEUYzwkKjOFM6kuXt-XDEBuPoYRJPaqhXcWEsrNL7fufTS2_t37S8NluLLGs9Bba4YuB6wU4h8FnCr-1eBzZ99bEB84jdjScIEytd0edKjNfqbQXmBFUidQ2H7ETln8LTRsjp76EdnyvirvucfVTT-QHareYwYP9bHqLpfV4Muzf41k2Xx-UpnyMsEP7Klxov_SE9ttfs7pAOQ7aKLVCdW_pf9q4VfrHgvJV3HjjLsZzN1wpvcuGO0Lh_99wbED9DgUgoBgpiJ04x2e5wJagJDNUSEgJhuOzEnHIuBdNSyTjgHJSjQSChGgQV1KdUwe6Gx6iez3N9gjC1bH4jRMgkj6hUyXUiIQQyFSdBIBPdQGGlulT6BuN2zsUsrZBk09QpPLUKT53CG4h8rVq4Bht_yLerXUm_GUoKMeDXlaf_XnmGtu2TQ7Gco3qxXOsLyEUK0SyNrYm2uvePg9Engz3iYw |
| linkProvider | Elsevier |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT8MwDLbGdoALb8R45sA1Gn1lHbdpMHXscWGTdqvSJJU6jW7aQwh-Pc6S8pAQSFxbW6oc1698tgFuvARjhjBtUE94HvUFT2mSKkaZl0rOpPLF5va8P2DRyH8cB-MStIpeGA2rtLbf2PSNtbZPalaatXmW1Z4cnVwxNL2op-j4wi2o6OlUfhkqzU43GnwiPQJz6Yn0VDMUHXQbmNfydYkahYmia2YO6aXKP3moL16nvQ-7NlwkTfNFB1BS-SHsFasYiP0zj2DSyVf95h25NwvmyabQZ3oWKH_hC0UWtk5P9E27qdMRDFiJxqpz3QGYvSlJnjU-b2ntB8lyIqaztSRf2-GOYdR-GLYiatcoUIH5wIrqpVNM1BtcJm7qpK4SGBMkKReNgLuci4QpIUXgcI7CUUgQugoJJaaorsQD9k6gnM9ydQrE1Q39aZJ4THDfFTK8DQV6QSaD0HFEqKrgFaKLhZ0xrlddTOMCTDaJjcBjLfDYCLwK9INrbmZs_EFfL04l_qYrMbqBXznP_s15DdvRsN-Le51B9xx29BsDarmA8mqxVpcYmqySK6t670YJ5RQ |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=IntMA%3A+Dynamic+Interaction-aware+resource+allocation+for+containerized+microservices+in+cloud+environments&rft.jtitle=Journal+of+systems+architecture&rft.au=Joseph%2C+Christina+Terese&rft.au=Chandrasekaran%2C+K.&rft.date=2020-12-01&rft.pub=Elsevier+B.V&rft.issn=1383-7621&rft.eissn=1873-6165&rft.volume=111&rft_id=info:doi/10.1016%2Fj.sysarc.2020.101785&rft.externalDocID=S1383762120300758 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1383-7621&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1383-7621&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1383-7621&client=summon |