research-article

Model-based fleet deployment of edge computing applications

Authors:

Franck FleureyAuthors Info & Claims

MODELS '20: Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems

Pages 132 - 142

https://doi.org/10.1145/3365438.3410951

Published: 16 October 2020 Publication History

Abstract

Edge computing brings software in close proximity to end users and IoT devices. Given the increasing number of distributed Edge devices with various contexts, as well as the widely adopted continuous delivery practices, software developers need to maintain multiple application versions and frequently (re-)deploy them to a fleet of many devices with respect to their contexts. Doing this correctly and efficiently goes beyond manual capabilities and requires employing an intelligent and reliable automated approach. Accordingly this paper describes a joint research with a Smart Healthcare application provider on a model-based approach to automatically assigning multiple software deployments to hundreds of Edge gateways. From a Platform-Specific Model obtained from the existing Edge computing platform, we extract a Platform-Independent Model that describes a list of target devices and a pool of available deployments. Next, we use constraint solving to automatically assign deployments to devices at once, given their specific contexts. The resulting solution is transformed back to the PSM as to proceed with software deployment accordingly. We validate the approach with a Fleet Deployment prototype integrated into the DevOps toolchain currently used by the application provider. Initial experiments demonstrate the viability of the approach and its usefulness in supporting DevOps in Edge computing applications.

References

[1]

Amazon. 2020. AWS IoT Greengrass. https://aws.amazon.com/greengrass/. Accessed: 2020-05-20.

[2]

Carlos Ansótegui, Miquel Bofill, Miquel Palahí, Josep Suy, and Mateu Villaret. 2011. Satisfiability modulo theories: An efficient approach for the resource-constrained project scheduling problem. In Ninth Symposium of Abstraction, Reformulation, and Approximation.

[3]

Matej Artač, Tadej Borovšak, Elisabetta Di Nitto, Michele Guerriero, and Damian A Tamburri. 2016. Model-driven continuous deployment for quality devops. In Proceedings of the 2nd International Workshop on Quality-Aware DevOps. 40--41.

Digital Library

[4]

Clark Barrett and Cesare Tinelli. 2018. Satisfiability modulo theories. In Handbook of Model Checking. Springer, 305--343.

[5]

Miquel Bofill, Miquel Palahí, Josep Suy, and Mateu Villaret. 2012. Solving constraint satisfaction problems with SAT modulo theories. Constraints 17, 3 (2012), 273--303.

Digital Library

[6]

Maria Paola Bonacina, Stéphane Graham-Lengrand, and Natarajan Shankar. 2017. Satisfiability modulo theories and assignments. In International Conference on Automated Deduction. Springer, 42--59.

[7]

Randal E Bryant, Shuvendu K Lahiri, and Sanjit A Seshia. 2002. Modeling and verifying systems using a logic of counter arithmetic with lambda expressions and uninterpreted functions. In International Conference on Computer Aided Verification. Springer, 78--92.

[8]

Antonio Bucchiarone, Antonio Cicchetti, and Annapaola Marconi. 2019. Exploiting multi-level modelling for designing and deploying gameful systems. In 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems (MODELS). IEEE, 34--44.

[9]

CHEF. 2020. CHEF INFRA. https://www.chef.io/products/chef-infra/. Accessed: 2020-05-20.

[10]

Benoit Combemale and Manuel Wimmer. 2019. Towards a Model-Based DevOps for Cyber-Physical Systems. In Software Engineering Aspects of Continuous Development.

[11]

Rustem Dautov and Hui Song. 2019. Towards IoT Diversity via Automated Fleet Management. In MDE4IoT/ModComp@ MoDELS. 47--54.

[12]

Leonardo De Moura and Nikolaj Bjørner. 2008. Z3: An efficient SMT solver. In International conference on Tools and Algorithms for the Construction and Analysis of Systems. Springer, 337--340.

Digital Library

[13]

Johannes Eder, Andreas Bahya, Sebastian Voss, Alexandru Ipatiov, and Maged Khalil. 2018. From deployment to platform exploration: automatic synthesis of distributed automotive hardware architectures. In Proceedings of the 21th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems. 438--446.

Digital Library

[14]

Johannes Eder, Sergey Zverlov, Sebastian Voss, Maged Khalil, and Alexandru Ipatiov. 2017. Bringing DSE to life: exploring the design space of an industrial automotive use case. In 2017 ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems (MODELS). IEEE, 270--280.

Digital Library

[15]

Carlos RAguayo González, Carl B Dietrich, and Jeffrey H Reed. 2009. Understanding the software communications architecture. IEEE Communications Magazine 47, 9 (2009), 50--57.

Digital Library

[16]

Google. 2020. Coral Edge TPU. https://coral.ai/. Accessed:2020-05-20.

[17]

Daniel Hall. 2013. Ansible configuration management. Packt Publishing Ltd.

[18]

Lorin Hochstein and Rene Moser. 2017. Ansible: Up and Running: Automating Configuration Management and Deployment the Easy Way. O'Reilly Media, Inc.

[19]

Microsoft. 2020. Azure IoT Edge. https://azure.microsoft.com/en-us/services/iot-edge/. Accessed: 2020-05-20.

[20]

OMG. 2006. Deployment and Configuration of Component-based Distributed Applications Specification, v4.0. Technical Report. Object Management Group, Inc. https://www.omg.org/spec/DEPL/4.0/PDF

[21]

Temel Öncan. 2007. A survey of the generalized assignment problem and its applications. INFOR: Information Systems and Operational Research 45, 3 (2007), 123--141.

[22]

David W Pentico. 2007. Assignment problems: A golden anniversary survey. European Journal of Operational Research 176, 2 (2007), 774--793.

[23]

Subhav Pradhan, Abhishek Dubey, Shweta Khare, Saideep Nannapaneni, Aniruddha Gokhale, Sankaran Mahadevan, Douglas C Schmidt, and Martin Lehofer. 2018. Chariot: Goal-driven orchestration middleware for resilient IoT systems. ACM Transactions on Cyber-Physical Systems 2, 3 (2018), 1--37.

Digital Library

[24]

Michael Vögler, Johannes M Schleicher, Christian Inzinger, and Schahram Dustdar. 2016. A scalable framework for provisioning large-scale IoT deployments. ACM Transactions on Internet Technology (TOIT) 16, 2 (2016), 1--20.

Digital Library

[25]

Changsheng You, Kaibin Huang, Hyukjin Chae, and Byoung-Hoon Kim. 2016. Energy-efficient resource allocation for mobile-edge computation offloading. IEEE Transactions on Wireless Communications 16, 3 (2016), 1397--1411.

Digital Library

[26]

Lintao Zhang and Sharad Malik. 2002. The quest for efficient boolean satisfiability solvers. In International Conference on Computer Aided Verification. Springer, 17--36.

Cited By

Guan PDangwal ATaherkordi AWolski RKrintz C(2024)Energy-Aware IoT Deployment PlanningProceedings of the 21st ACM International Conference on Computing Frontiers10.1145/3649153.3649864(61-70)Online publication date: 7-May-2024
https://dl.acm.org/doi/10.1145/3649153.3649864
Li JMoeini BNejati SSabetzadeh MMcCallen M(2024)A Lean Simulation Framework for Stress Testing IoT Cloud SystemsIEEE Transactions on Software Engineering10.1109/TSE.2024.340215750:7(1827-1851)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1109/TSE.2024.3402157
Li JNejati SSabetzadeh MMcCallen MSyriani ESahraoui H(2022)A domain-specific language for simulation-based testing of IoT edge-to-cloud solutionsProceedings of the 25th International Conference on Model Driven Engineering Languages and Systems10.1145/3550355.3552405(367-378)Online publication date: 23-Oct-2022
https://dl.acm.org/doi/10.1145/3550355.3552405

Index Terms

Model-based fleet deployment of edge computing applications
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Sensor applications and deployments
2. Software and its engineering
  1. Software creation and management
    1. Software development process management
      1. Software development methods
        Agile software development
  2. Software notations and tools
    1. System description languages
      1. System modeling languages

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cover image ACM Conferences

MODELS '20: Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems

October 2020

406 pages

ISBN:9781450370196

DOI:10.1145/3365438

General Chairs:
Eugene Syriani
Université de Montréal, Canada
,
Houari Sahraoui
Université de Montréal, Canada

Copyright © 2020 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 the author(s) 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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Publication History

Published: 16 October 2020

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Norges Forskningsråd
H2020 LEIT Information and Communication Technologies

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MODELS '20

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MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems

October 16 - 23, 2020

Virtual Event, Canada

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MODELS '20 Paper Acceptance Rate 35 of 127 submissions, 28%;

Overall Acceptance Rate 118 of 382 submissions, 31%

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Cited By

Guan PDangwal ATaherkordi AWolski RKrintz C(2024)Energy-Aware IoT Deployment PlanningProceedings of the 21st ACM International Conference on Computing Frontiers10.1145/3649153.3649864(61-70)Online publication date: 7-May-2024
https://dl.acm.org/doi/10.1145/3649153.3649864
Li JMoeini BNejati SSabetzadeh MMcCallen M(2024)A Lean Simulation Framework for Stress Testing IoT Cloud SystemsIEEE Transactions on Software Engineering10.1109/TSE.2024.340215750:7(1827-1851)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1109/TSE.2024.3402157
Li JNejati SSabetzadeh MMcCallen MSyriani ESahraoui H(2022)A domain-specific language for simulation-based testing of IoT edge-to-cloud solutionsProceedings of the 25th International Conference on Model Driven Engineering Languages and Systems10.1145/3550355.3552405(367-378)Online publication date: 23-Oct-2022
https://dl.acm.org/doi/10.1145/3550355.3552405

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