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Rule based auto-scalability of IoT services for efficient edge device resource utilization

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Abstract

Conveying the workload of IoT systems from the cloud to edge nodes have been widely adopted by industrial and academic sectors. This tendency is generally promoted to meet the requirements of some time-sensitive use cases such as IoT healthcare applications. However, IoT devices at the edge network are likely to be resource-limited, as well as, they perform under an extremely heterogeneous environment in terms of the connected devices and the deployed software modules. Thus, both of the aforementioned concerns have considerably led to hindering the deployment process of services on IoT edge devices. In this paper, we propose an approach to facilitate a scalable and lightweight solution for service deployment for efficient resource utilization on IoT edge nodes. Our solution is based on the container concept, and we adopt the cluster concept to define a group of IoT edge devices. Containers are lightweight virtualization technique that enables services to be packaged and deployed with their dependencies regardless of the hosts infrastructure, as well as, they facilitate the service communication and the update process. Furthermore, containers are supported by some means of orchestration such as swarm. These orchestration tools can be configured to enable services deployment and resources sharing among IoT edge devices falling within the same cluster. However, they lack elasticity in terms of auto-scaling up/down of services instances in corresponding to the resource utilization of all cluster elements, as well as, service performance metrics. Our approach overcomes these limitations by following an auto-scaling process based on MAPE-K loop, which is based on our proposed rule model to generate a scaling plan by analyzing collected performance metrics of a cluster. Our evaluation shows the efficiency of the proposed approach in adapting the system performance to meet service performance requirements and the availability of system resources.

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Notes

  1. https://docs.docker.com/v17.09/machine/get-started/

  2. https://docs.docker.com/engine/swarm/

  3. https://prometheus.io/

  4. https://grafana.com/

  5. https://jenkins.io/

  6. https://prometheus.io/docs/alerting/alertmanager/

  7. https://prometheus.io/docs/practices/instrumentation/

References

  • Ahmed B, Seghir B, Al-Osta M, Abdelouahed G (2019) Container based resource management for data processing on iot gateways. Procedia Comput Sci 155:234–241

    Article  Google Scholar 

  • Al-Osta M, Bali A, Gherbi A (2019) Event driven and semantic based approach for data processing on iot gateway devices. J Ambient Intell Hum Comput 10(12):4663–4678

    Article  Google Scholar 

  • Brogi A, Mencagli G, Neri D, Soldani J, Torquati M (2017) Container-based support for autonomic data stream processing through the fog. In: European conference on parallel processing, Springer, pp 17–28

  • Computing A et al (2006) An architectural blueprint for autonomic computing. IBM White Paper 31(2006):1–6

  • Devarajan M, Subramaniyaswamy V, Vijayakumar V, Ravi L (2019) Fog-assisted personalized healthcare-support system for remote patients with diabetes. J Ambient Intell Hum Comput:1–14

  • Evans D (2011) The internet of things: How the next evolution of the internet is changing everything. CISCO white paper 1(2011):1–11

    Google Scholar 

  • Ismail BI, Goortani EM, Ab Karim MB, Tat WM, Setapa S, Luke JY, Hoe OH (2015) Evaluation of docker as edge computing platform. In: 2015 IEEE conference on open systems (ICOS), IEEE, pp 130–135

  • Khazaei H, Bannazadeh H, Leon-Garcia A (2017) Savi-iot: A self-managing containerized iot platform. In: 2017 IEEE 5th international conference on future Internet of Things and Cloud (FiCloud), IEEE, pp 227–234

  • Morabito R (2017) Virtualization on internet of things edge devices with container technologies: a performance evaluation. IEEE Access 5:8835–8850

    Article  Google Scholar 

  • Morabito R, Beijar N (2016) Enabling data processing at the network edge through lightweight virtualization technologies. 2016 IEEE International Conference on Sensing. Communication and Networking (SECON Workshops), IEEE, pp 1–6

  • Renner T, Meldau M, Kliem A (2016) Towards container-based resource management for the internet of things. In: 2016 International conference on software networking (ICSN), IEEE, pp 1–5

  • Ruchika V (2016) Evaluation of docker for iot application. Int J Recent Innov Trends Comput Commun 4(6):624–628

    Google Scholar 

  • Venticinque S, Amato A (2019) A methodology for deployment of iot application in fog. J Ambient Intell Hum Comput 10(5):1955–1976

    Article  Google Scholar 

  • Wong W, Zavodovski A, Zhou P, Kangasharju J (2019) Container deployment strategy for edge networking. In: Proceedings of the 4th workshop on middleware for edge clouds & cloudlets, ACM, pp 1–6

Download references

Acknowledgements

This work is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC).

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Authors and Affiliations

  1. Department of Software and IT Engineering, École de technologie supérieure, Montreal, H3C 1K3, Canada

    Ahmed Bali, Mahmud Al-Osta, Soufiene Ben Dahsen & Abdelouahed Gherbi

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  1. Ahmed Bali
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  2. Mahmud Al-Osta
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  3. Soufiene Ben Dahsen
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  4. Abdelouahed Gherbi
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Correspondence to Ahmed Bali.

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Bali, A., Al-Osta, M., Ben Dahsen, S. et al. Rule based auto-scalability of IoT services for efficient edge device resource utilization. J Ambient Intell Human Comput 11, 5895–5912 (2020). https://doi.org/10.1007/s12652-020-02100-0

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  • DOI: https://doi.org/10.1007/s12652-020-02100-0

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