research-article

A programming model and middleware for high throughput serverless computing applications

Authors:

Alfonso Pérez,

Germán Moltó,

Miguel Caballer,

Amanda CalatravaAuthors Info & Claims

SAC '19: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing

Pages 106 - 113

https://doi.org/10.1145/3297280.3297292

Published: 08 April 2019 Publication History

Abstract

Serverless computing has introduced unprecedented levels of scalability and parallelism for the execution of High Throughput Computing tasks. This represents a challenge and an opportunity for different scientific workloads to be adapted to upcoming programming models that simplify the usage of such platforms. In this paper we introduce a serverless model for highly-parallel file-processing applications. We also describe a middleware implementation that supports the execution of customized execution environments based on Docker images on AWS Lambda, the leading serverless computing platform. Moreover, this middleware offers tools to manage the input/output of the serverless infrastructure and the creation of HTTP endpoints in a transparent way to the user. To test the programming model proposed and the middleware, this paper describes two case studies. The first one analyzes medical images with a high degree of parallelism. The second one presents an architecture to process video keyframes. The results from both case studies are discussed and a cost analysis of the medical image architecture comparing different Cloud options is carried out. The results show that the combination of a high-level programming model with the scalable capabilities of AWS Lambda makes it easy for end users to efficiently exploit serverless computing for the optimized and cost-effective execution of loosely-coupled tasks.

References

[1]

Amazon. Amazon Lambda (AWS Lambda). https://aws.amazon.com/lambda/. {Online; accessed 24-September-2018}.

[2]

Amazon. Amazon Web Services (AWS). http://aws.amazon.com. {Online; accessed 24-September-2018}.

[3]

Amazon. AWS Serverless Application Model (AWS SAM). https://github.com/awslabs/serverless-application-model. {Online; accessed 24-September-2018}.

[4]

Apex. Up, deploy serverless apps in seconds. http://apex.run/. {Online; accessed 24-September-2018}.

[5]

AWS. Amazon EC2 Container Service (ECS). https://aws.amazon.com/es/ecs/. {Online; accessed 24-September-2018}.

[6]

I. Baldini, P. Castro, K. Chang, P. Cheng, S. Fink, V. Ishakian, N. Mitchell, V. Muthusamy, R. Rabbah, A. Slominski, and P. Suter. Serverless Computing: Current Trends and Open Problems. pages 1--20, jun 2017.

[7]

CoreOS. rkt. https://coreos.com/rkt/. {Online; accessed 24-September-2018}.

[8]

Databricks. Databricks Serverless. https://goo.gl/uagZ8E. {Online; accessed 24-September-2018}.

[9]

Docker. Docker. https://www.docker.com/. {Online; accessed 24-September-2018}.

[10]

Docker. Swarm Mode in Docker Engine. https://docs.docker.com/engine/swarm/. {Online; accessed 24-September-2018}.

[11]

S. Fouladi, R. S. Wahby, B. Shacklett, K. V. Balasubramaniam, W. Zeng, R. Bhalerao, A. Sivaraman, G. Porter, and K. Winstein. Encoding, fast and slow: Low-latency video processing using thousands of tiny threads. In 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 17), pages 363--376, Boston, MA, 2017. USENIX Association.

Digital Library

[12]

T. A. S. Foundation. Apache openwhisk. http://openwhisk.org/. {Online; accessed 24-September-2018}.

[13]

G. C. Fox, V. Ishakian, V. Muthusamy, and A. Slominski. Status of Serverless Computing and Function-as-a-Service(FaaS) in Industry and Research. aug 2017.

[14]

D. Gannon. Observations about Serverless Computing With a few examples from AWS Lambda, Azure Functions and Open Whisk. Technical report, 2017.

[15]

A. Glikson. TRANSIT: Flexible pipeline for IoT data with Bluemix and Open Whisk. https://goo.gl/ThN2TR. {Online; accessed 24-September-2018}.

[16]

Google. Container Engine. https://cloud.google.com/container-engine. {Online; accessed 24-September-2018}.

[17]

Google. Google Cloud Functions. https://cloud.google.com/functions/. {Online; accessed 24-September-2018}.

[18]

Google. Google Cloud Platform. https://cloud.google.com. {Online; accessed 24-September-2018}.

[19]

Hashicorp. Nomad. https://www.nomadproject.io/. {Online; accessed 24-September-2018}.

[20]

S. Hendrickson, S. Sturdevant, T. Harter, V. Venkataramani, A. C. Arpaci-Dusseau, and R. H. Arpaci-Dusseau. Serverless computation with openlambda. In 8th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 16), Denver, CO, 2016. USENIX Association.

Digital Library

[21]

E. Jonas, Q. Pu, S. Venkataraman, I. Stoica, and B. Recht. Occupy the Cloud: Distributed Computing for the 99%. feb 2017.

Digital Library

[22]

Kubernetes. Kubernetes. https://kubernetes.io/. {Online; accessed 24-September-2018}.

[23]

LXC. LXC. https://linuxcontainers.org/. {Online; accessed 24-September-2018}.

[24]

G. McGrath, J. Short, S. Ennis, B. Judson, and P. Brenner. Cloud event programming paradigms: Applications and analysis. In 2016 IEEE 9th International Conference on Cloud Computing (CLOUD), pages 400--406, June 2016.

[25]

D. Merkel. Docker: lightweight Linux containers for consistent development and deployment. Linux Journal, 2014(239):2, mar 2014.

Digital Library

[26]

Microsoft. Azure Container Service. https://azure.microsoft.com/services/container-service/. {Online; accessed 24-September-2018}.

[27]

Microsoft. Microsoft Azure. https://azure.microsoft.com. {Online; accessed 24-September-2018}.

[28]

Microsoft. Microsoft Azure Functions. https://azure.microsoft.com/en-in/services/functions/. {Online; accessed 24-September-2018}.

[29]

OpenNebula. OpenNebula. https://opennebula.org. {Online; accessed 24-September-2018}.

[30]

OpenStack. OpenStack. http://openstack.org. {Online; accessed 24-September-2018}.

[31]

D. O. S. Platform. Ooso, serverless mapreduce. https://github.com/d2si-oss/ooso. {Online; accessed 24-September-2018}.

[32]

A. Pérez, G. Moltó, M. Caballer, and A. Calatrava. Serverless computing for container-based architectures. Future Generation Computer Systems, 83:50 -- 59, 2018.

[33]

J. Redmon and A. Farhadi. Yolov3: An incremental improvement. arXiv, 2018.

[34]

F. B. Torro, J. D. S. Quilis, I. B. Espert, A. A. Bayarri, and L. M. Bonmatí. Accelerating the diffusion-weighted imaging biomarker in the clinical practice: comparative study. Procedia Computer Science, 108(Supplement C):1185 -- 1194, 2017. International Conference on Computational Science, ICCS 2017, 12--14 June 2017, Zurich, Switzerland.

[35]

M. Villamizar, O. Garcés, L. Ochoa, H. Castro, L. Salamanca, M. Verano, R. Casallas, S. Gil, C. Valencia, A. Zambrano, and M. Lang. Cost comparison of running web applications in the cloud using monolithic, microservice, and aws lambda architectures. Service Oriented Computing and Applications, 11(2):233--247, 2017.

Digital Library

[36]

L. Wang, M. Li, Y. Zhang, T. Ristenpart, and M. Swift. Peeking Behind the Curtains of Serverless Platforms. 2018 USENIX Annual Technical Conference (USENIX ATC 18), pages 133--146, 2018.

Digital Library

Cited By

Deka RGhosh ANanda SBarik RSaikia M(2024)Smart Healthcare System in Server-Less Environment: Concepts, Architecture, Challenges, Future DirectionsComputers10.3390/computers1304010513:4(105)Online publication date: 19-Apr-2024
https://doi.org/10.3390/computers13040105
Verma ASatpathy ADas SAddya S(2024)LEASE: Leveraging Energy-Awareness in Serverless Edge for Latency-Sensitive IoT Services2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops59983.2024.10502788(302-307)Online publication date: 11-Mar-2024
https://doi.org/10.1109/PerComWorkshops59983.2024.10502788
Werner STai S(2024)A reference architecture for serverless big data processingFuture Generation Computer Systems10.1016/j.future.2024.01.029155:C(179-192)Online publication date: 18-Jul-2024
https://dl.acm.org/doi/10.1016/j.future.2024.01.029
Show More Cited By

Index Terms

A programming model and middleware for high throughput serverless computing applications
1. Applied computing
  1. Enterprise computing
    1. Event-driven architectures
2. Computer systems organization
  1. Architectures
    1. Distributed architectures
      1. Cloud computing

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Published In

cover image ACM Conferences

SAC '19: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing

April 2019

2682 pages

ISBN:9781450359337

DOI:10.1145/3297280

Conference Chairs:
Chih-Cheng Hung
Kennesaw State University, Marietta, Georgia
,
George A. Papadopoulos
University of Cyprus, Nicosia, Cyprus

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGAPP: ACM Special Interest Group on Applied Computing

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 April 2019

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Ministerio de Economía, Industria y Competitividad, Gobierno de España

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SAC '19

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SIGAPP

SAC '19: The 34th ACM/SIGAPP Symposium on Applied Computing

April 8 - 12, 2019

Limassol, Cyprus

Acceptance Rates

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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SAC '25

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sigapp

The 40th ACM/SIGAPP Symposium on Applied Computing

March 31 - April 4, 2025

Catania , Italy

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Citations

Cited By

Deka RGhosh ANanda SBarik RSaikia M(2024)Smart Healthcare System in Server-Less Environment: Concepts, Architecture, Challenges, Future DirectionsComputers10.3390/computers1304010513:4(105)Online publication date: 19-Apr-2024
https://doi.org/10.3390/computers13040105
Verma ASatpathy ADas SAddya S(2024)LEASE: Leveraging Energy-Awareness in Serverless Edge for Latency-Sensitive IoT Services2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops59983.2024.10502788(302-307)Online publication date: 11-Mar-2024
https://doi.org/10.1109/PerComWorkshops59983.2024.10502788
Werner STai S(2024)A reference architecture for serverless big data processingFuture Generation Computer Systems10.1016/j.future.2024.01.029155:C(179-192)Online publication date: 18-Jul-2024
https://dl.acm.org/doi/10.1016/j.future.2024.01.029
Ghorbian MGhobaei-Arani M(2024)A Blockchain-Enabled Serverless Security Mechanism for IoT-Based DronesBuilding Cybersecurity Applications with Blockchain and Smart Contracts10.1007/978-3-031-50733-5_3(55-82)Online publication date: 22-Feb-2024
https://doi.org/10.1007/978-3-031-50733-5_3
Cuadra JHurtado EPérez FCasquero OArmentia A(2023)OpenFog-Compliant Application-Aware Platform: A Kubernetes ExtensionApplied Sciences10.3390/app1314836313:14(8363)Online publication date: 19-Jul-2023
https://doi.org/10.3390/app13148363
Wen JChen ZJin XLiu X(2023)Rise of the Planet of Serverless Computing: A Systematic ReviewACM Transactions on Software Engineering and Methodology10.1145/357964332:5(1-61)Online publication date: 21-Jul-2023
https://dl.acm.org/doi/10.1145/3579643
Moyer DNikolopoulos D(2023)Punching Holes in the Cloud: Direct Communication Between Serverless FunctionsServerless Computing: Principles and Paradigms10.1007/978-3-031-26633-1_2(15-41)Online publication date: 12-May-2023
https://doi.org/10.1007/978-3-031-26633-1_2
Krishnamurthi RKumar AGill SBuyya R(2023)Serverless Computing: New Trends and Research DirectionsServerless Computing: Principles and Paradigms10.1007/978-3-031-26633-1_1(1-13)Online publication date: 12-May-2023
https://doi.org/10.1007/978-3-031-26633-1_1
Augustyn DWyciślik ŁSojka M(2022)The FaaS-Based Cloud Agnostic Architecture of Medical Services—Polish Case StudyApplied Sciences10.3390/app1215795412:15(7954)Online publication date: 8-Aug-2022
https://doi.org/10.3390/app12157954
Shafiei HKhonsari AMousavi P(2022)Serverless Computing: A Survey of Opportunities, Challenges, and ApplicationsACM Computing Surveys10.1145/351061154:11s(1-32)Online publication date: 10-Nov-2022
https://dl.acm.org/doi/10.1145/3510611
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