Placement of Microservices-based IoT Applications in Fog Computing: A Taxonomy and Future Directions

Author:

Pallewatta Samodha1ORCID,Kostakos Vassilis1ORCID,Buyya Rajkumar1ORCID

Affiliation:

1. The Cloud Computing and Distributed Systems (CLOUDS) Laboratory, School of Computing and Information Systems, University of Melbourne, Australia

Abstract

The Fog computing paradigm utilises distributed, heterogeneous and resource-constrained devices at the edge of the network for efficient deployment of latency-critical and bandwidth-hungry IoT application services. Moreover, MicroService Architecture (MSA) is increasingly adopted to keep up with the rapid development and deployment needs of fast-evolving IoT applications. Due to the fine-grained modularity of the microservices and their independently deployable and scalable nature, MSA exhibits great potential in harnessing Fog and Cloud resources, thus giving rise to novel paradigms like Osmotic computing. The loosely coupled nature of the microservices, aided by the container orchestrators and service mesh technologies, enables the dynamic composition of distributed and scalable microservices to achieve diverse performance requirements of the IoT applications using distributed Fog resources. To this end, efficient placement of microservice plays a vital role, and scalable placement algorithms are required to utilise the said characteristics of the MSA while overcoming novel challenges introduced by the architecture. Thus, we present a comprehensive taxonomy of recent literature on microservices-based IoT applications placement within Fog computing environments. Furthermore, we organise multiple taxonomies to capture the main aspects of the placement problem, analyse and classify related works, identify research gaps within each category, and discuss future research directions.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Reference116 articles.

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3. Eyhab Al-Masri. 2018. Enhancing the microservices architecture for the internet of things. In Proceedings of the IEEE International Conference on Big Data (Big Data’18). IEEE, 5119–5125.

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