survey

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

Authors:

Samodha Pallewatta,

Vassilis Kostakos,

Rajkumar BuyyaAuthors Info & Claims

ACM Computing Surveys, Volume 55, Issue 14s

Article No.: 321, Pages 1 - 43

https://doi.org/10.1145/3592598

Published: 17 July 2023 Publication History

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.

References

[1]

Muhammad Abdullah, Waheed Iqbal, Arif Mahmood, Faisal Bukhari, and Abdelkarim Erradi. 2020. Predictive autoscaling of microservices hosted in fog microdata center. IEEE Syst. J. 15, 1 (2020), 1275–1286.

[2]

Madhura Adeppady, Carla Fabiana Chiasserini, Holger Karl, and Paolo Giaccone. 2022. iPlace: An interference-aware clustering algorithm for microservice placement. In Proceedings of the IEEE International Conference on Communications. IEEE, 5457–5462.

[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.

[4]

Derian Alencar, Cristiano Both, Rodolfo Antunes, Helder Oliveira, Eduardo Cerqueira, and Denis Rosário. 2021. Dynamic microservice allocation for virtual reality distribution with qoe support. IEEE Trans. Netw. Serv. Manag. 19, 1 (2021), 729–740.

[5]

Abdullah M. Alqahtani, Barzan Yosuf, Sanaa H. Mohamed, Taisir E. H. El-Gorashi, and Jaafar M. H. Elmirghani. 2021. Energy minimized federated fog computing over passive optical networks. In Proceedings of the International Symposium on Networks, Computers and Communications (ISNCC’21). IEEE, 1–6.

[6]

Darko Andročec. 2019. Systematic mapping study on osmotic computing. In Proceedings of the Central European Conference on Information and Intelligent Systems. Faculty of Organization and Informatics Varazdin, 79–84.

[7]

Valentino Armani, Francescomaria Faticanti, Silvio Cretti, Seungwoo Kum, and Domenico Siracusa. 2021. A cost-effective workload allocation strategy for cloud-native edge services. arXiv preprint arXiv:2110.12788 (2021).

[8]

D. Baburao, T. Pavankumar, and C. S. R. Prabhu. 2023. Load balancing in the fog nodes using particle swarm optimization- based enhanced dynamic resource allocation method. Applied Nanoscience 13, 2 (2023), 1045–1054.

[9]

Sanjeevani Bhardwaj and Alok Kole. 2016. Review and study of internet of things: It’s the future. In Proceedings of the International Conference on Intelligent Control Power and Instrumentation (ICICPI’16). IEEE, 47–50.

[10]

Flavio Bonomi, Rodolfo Milito, Jiang Zhu, and Sateesh Addepalli. 2012. Fog computing and its role in the Internet of Things. In Proceedings of the 1st Edition of the MCC Workshop on Mobile Cloud Computing. 13–16.

Digital Library

[11]

Wassim Boudieb, Abdelhamid Malki, and Mimoun Malki. 2022. Microservice instances provisioning for IoT applications in fog computing. In Proceedings of the 5th Conference on Computing Systems and Applications: Advances in Computing Systems and Applications. Springer, 107–117.

[12]

Antonio Brogi, Stefano Forti, Carlos Guerrero, and Isaac Lera. 2020. How to place your apps in the fog: State of the art and open challenges. Softw.: Pract. Exper. 50, 5 (2020), 719–740.

[13]

Neda Bugshan, Ibrahim Khalil, Nour Moustafa, and Mohammad Saidur Rahman. 2023. Privacy-Preserving Microservices in Industrial Internet of Things Driven Smart Applications. IEEE Internet of Things Journal 10, 4 (2023), 2821–2831.

[14]

Björn Butzin, Frank Golatowski, and Dirk Timmermann. 2016. Microservices approach for the internet of things. In Proceedings of the IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA’16). IEEE, 1–6.

Digital Library

[15]

Alina Buzachis, Antonino Galletta, Lorenzo Carnevale, Antonio Celesti, Maria Fazio, and Massimo Villari. 2018. Towards osmotic computing: Analyzing overlay network solutions to optimize the deployment of container-based microservices in fog, edge and IoT environments. In Proceedings of the IEEE 2nd International Conference on Fog and Edge Computing (ICFEC’18). IEEE, 1–10.

[16]

Carmen Carrión. 2022. Kubernetes Scheduling: Taxonomy, Ongoing Issues and Challenges. ACM Computing Surveys (CSUR) 55, 7 (2022).

[17]

Ramaswamy Chandramouli, Zack Butcher, et al. 2020. Building secure microservices-based applications using service-mesh architecture. NIST Special Pub. 800 (2020), 204A.

[18]

Chen Chen, Junchao Li, Venki Balasubramaniam, Yongqiang Wu, Yuru Zhang, and Shaohua Wan. 2020. Contention resolution in Wi-Fi 6-Enabled Internet of Things based on deep learning. IEEE Internet Things J. 8, 7 (2020), 5309–5320.

[19]

Lalit Chettri and Rabindranath Bera. 2019. A comprehensive survey on Internet of Things (IoT) toward 5G wireless systems. IEEE Internet Things J. 7, 1 (2019), 16–32.

[20]

Breno Costa, Joao Bachiega Jr, Leonardo Rebouças de Carvalho, and Aleteia P. F. Araujo. 2022. Orchestration in fog computing: A comprehensive survey. ACM Comput. Surv. 55, 2 (2022), 1–34.

Digital Library

[21]

Hans Jakob Damsgaard, Aleksandr Ometov, and Jari Nurmi. 2023. Approximation Opportunities in Edge Computing Hardware: A Systematic Literature Review. ACM Computing Surveys (CSUR) 55, 12 (2023).

[22]

Antonio De Iasio, Angelo Futno, Lorenzo Goglia, and Eugenio Zimeo. 2019. A microservices platform for monitoring and analysis of IoT traffic data in smart cities. In Proceedings of the IEEE International Conference on Big Data (Big Data’19). IEEE, 5223–5232.

[23]

Davi L. de Oliveira, Artur F. da S. Veloso, José V. V. Sobral, Ricardo A. L. Rabêlo, Joel J. P. C. Rodrigues, and Petar Solic. 2019. Performance evaluation of MQTT brokers in the Internet of Things for smart cities. In Proceedings of the 4th International Conference on Smart and Sustainable Technologies (SpliTech’19). IEEE, 1–6.

[24]

Cleber Jorge Lira de Santana, Brenno de Mello Alencar, and Cássio V. Serafim Prazeres. 2019. Reactive microservices for the internet of things: A case study in fog computing. In Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing. 1243–1251.

Digital Library

[25]

Flavia C. Delicato, Paulo F. Pires, Thais Batista, Everton Cavalcante, Bruno Costa, and Thomaz Barros. 2013. Towards an IoT ecosystem. In Proceedings of the 1st International Workshop on Software Engineering for Systems-of-systems. 25–28.

Digital Library

[26]

Shuiguang Deng, Zhengzhe Xiang, Javid Taheri, Mohammad Ali Khoshkholghi, Jianwei Yin, Albert Y. Zomaya, and Schahram Dustdar. 2020. Optimal application deployment in resource constrained distributed edges. IEEE Trans. Mob. Comput. 20, 5 (2020), 1907–1923.

[27]

Koustabh Dolui and Soumya Kanti Datta. 2017. Comparison of edge computing implementations: Fog computing, cloudlet and mobile edge computing. In Proceedings of the Global Internet of Things Summit (GIoTS). IEEE, 1–6.

[28]

Juan Fang and Aonan Ma. 2020. IoT application modules placement and dynamic task processing in edge-cloud computing. IEEE Internet Things J. 8, 16 (2020), 12771–12781.

[29]

Francescomaria Faticanti, Francesco De Pellegrini, Domenico Siracusa, Daniele Santoro, and Silvio Cretti. 2019. Cutting throughput with the edge: App-aware placement in fog computing. In Proceedings of the 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom’19). IEEE, 196–203.

[30]

Francescomaria Faticanti, Francesco De Pellegrini, Domenico Siracusa, Daniele Santoro, and Silvio Cretti. 2020. Throughput-aware partitioning and placement of applications in fog computing. IEEE Trans. Netw. Serv. Manag. 17, 4 (2020), 2436–2450.

Digital Library

[31]

Francescomaria Faticanti, Marco Savi, Francesco De Pellegrini, Petar Kochovski, Vlado Stankovski, and Domenico Siracusa. 2020. Deployment of application microservices in multi-domain federated fog environments. In Proceedings of the International Conference on Omni-layer Intelligent Systems (COINS’20). IEEE, 1–6.

[32]

Ion-Dorinel Filip, Florin Pop, Cristina Serbanescu, and Chang Choi. 2018. Microservices scheduling model over heterogeneous cloud-edge environments as support for IoT applications. IEEE Internet Things J. 5, 4 (2018), 2672–2681.

[33]

FogAtlas. Retrieved from https://fogatlas.fbk.eu/.

[34]

Martin Fowler and James Lewis. 2014. Microservices a Definition of This New Architectural Term. Retrieved from https://martinfowler.com/articles/microservices.html.

[35]

Kaihua Fu, Wei Zhang, Quan Chen, Deze Zeng, and Minyi Guo. 2021. Adaptive resource efficient microservice deployment in cloud-edge continuum. IEEE Trans. Parallel Distrib. Syst. 33, 8 (2021), 1825–1840.

Digital Library

[36]

Kaihua Fu, Wei Zhang, Quan Chen, Deze Zeng, Xin Peng, Wenli Zheng, and Minyi Guo. 2021. QoS-aware and resource efficient microservice deployment in cloud-edge continuum. In Proceedings of the IEEE International Parallel and Distributed Processing Symposium (IPDPS’21). IEEE, 932–941.

[37]

Damien Gallagher and Ruth G. Lennon. 2022. Architecting multi-cloud applications for high availability using DevOps. In Proceedings of the IEEE International Conference on e-Business Engineering (ICEBE’22). IEEE, 112–118.

[38]

Yu Gan, Yanqi Zhang, Dailun Cheng, Ankitha Shetty, Priyal Rathi, Nayan Katarki, Ariana Bruno, Justin Hu, Brian Ritchken, Brendon Jackson, et al. 2019. An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems. In Proceedings of the 24th International Conference on Architectural Support for Programming Languages and Operating Systems. 3–18.

Digital Library

[39]

Martin Garriga. 2017. Towards a taxonomy of microservices architectures. In Proceedings of the International Conference on Software Engineering and Formal Methods. Springer, 203–218.

[40]

Mostafa Ghobaei-Arani and Ali Shahidinejad. 2022. A cost-efficient IoT service placement approach using whale optimization algorithm in fog computing environment. Expert Syst. Applic. 200 (2022), 117012.

Digital Library

[41]

Mohammad Goudarzi, Marimuthu Palaniswami, and Rajkumar Buyya. 2022. Scheduling IoT applications in edge and fog computing environments: A taxonomy and future directions. Comput. Sur. 55, 7 (2022), 1–41.

[42]

Jayavardhana Gubbi, Rajkumar Buyya, Slaven Marusic, and Marimuthu Palaniswami. 2013. Internet of Things (IoT): A vision, architectural elements, and future directions. Fut. Gen. Comput. Syst. 29, 7 (2013), 1645–1660.

Digital Library

[43]

Carlos Guerrero, Isaac Lera, and Carlos Juiz. 2019. Evaluation and efficiency comparison of evolutionary algorithms for service placement optimization in fog architectures. Fut. Gen. Comput. Syst. 97 (2019), 131–144.

Digital Library

[44]

Carlos Guerrero, Isaac Lera, and Carlos Juiz. 2019. A lightweight decentralized service placement policy for performance optimization in fog computing. J. Amb. Intell. Humaniz. Comput. 10, 6 (2019), 2435–2452.

[45]

Feiyan Guo, Bing Tang, and Mingdong Tang. 2022. Joint optimization of delay and cost for microservice composition in mobile edge computing. World Wide Web 25, 5 (2022), 2019–2047.

[46]

Fengxian Guo, F. Richard Yu, Heli Zhang, Xi Li, Hong Ji, and Victor C. M. Leung. 2021. Enabling massive IoT toward 6G: A comprehensive survey. IEEE Internet Things J. 8, 15 (2021), 11891–11915.

[47]

Sara Hassan, Rami Bahsoon, and Rick Kazman. 2020. Microservice transition and its granularity problem: A systematic mapping study. Softw.: Pract. Exper. 50, 9 (2020), 1651–1681.

[48]

Xiang He, Zhiying Tu, Markus Wagner, Xiaofei Xu, and Zhongjie Wang. 2022. Online deployment algorithms for microservice systems with complex dependencies. IEEE Trans. Cloud Comput. (2022).

[49]

Robert Heinrich, André Van Hoorn, Holger Knoche, Fei Li, Lucy Ellen Lwakatare, Claus Pahl, Stefan Schulte, and Johannes Wettinger. 2017. Performance engineering for microservices: Research challenges and directions. In Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering. 223–226.

[50]

Juan Luis Herrera, Jaime Galán-Jiménez, Paolo Bellavista, Luca Foschini, Jose Garcia-Alonso, Juan M. Murillo, and Javier Berrocal. 2021. Optimal deployment of fog nodes, microservices and SDN controllers in time-sensitive IoT scenarios. In Proceedings of the IEEE Global Communications Conference (GLOBECOM’21). IEEE, 1–6.

Digital Library

[51]

Cheol-Ho Hong and Blesson Varghese. 2019. Resource management in fog/edge computing: A survey on architectures, infrastructure, and algorithms. ACM Comput. Surv. 52, 5 (2019), 1–37.

Digital Library

[52]

Tiansheng Huang, Weiwei Lin, Chennian Xiong, Rui Pan, and Jingxuan Huang. 2020. An ant colony optimization-based multiobjective service replicas placement strategy for fog computing. IEEE Trans. Cybern. 51, 11 (2020), 5595–5608.

[53]

Mohammad Mainul Islam, Fahimeh Ramezani, Hai Yan Lu, and Mohsen Naderpour. 2023. Optimal Placement of Applications in the Fog Environment: A Systematic Literature Review. J. Parallel and Distrib. Comput. 174 (2023), 46–69.

[54]

K. Iyeswariya and R. Muthubharathi. 2020. Investigation of edge-fog layer for accuracy and power consumption. In Proceedings of the 6th International Conference on Advanced Computing and Communication Systems (ICACCS’20). IEEE, 1252–1255.

[55]

Bushra Jamil, Humaira Ijaz, Mohammad Shojafar, Kashif Munir, and Rajkumar Buyya. 2022. Resource allocation and task scheduling in fog computing and internet of everything environments: A taxonomy, review, and future directions. ACM Comput. Surv. 54, 11s (2022), 1–38.

Digital Library

[56]

Muhammad Aslam Jarwar, Sajjad Ali, Muhammad Golam Kibria, Sunil Kumar, and Ilyoung Chong. 2017. Exploiting interoperable microservices in web objects enabled Internet of Things. In Proceedings of the 9th International Conference on Ubiquitous and Future Networks (ICUFN’17). IEEE, 49–54.

[57]

Christina Terese Joseph and K. Chandrasekaran. 2019. Straddling the crevasse: A review of microservice software architecture foundations and recent advancements. Softw.: Pract. Exper. 49, 10 (2019), 1448–1484.

[58]

Akashdeep Kaur, Rajesh Kumar, and Sharad Saxena. 2020. Osmotic computing and related challenges: A survey. In Proceedings of the 6th International Conference on Parallel, Distributed and Grid Computing (PDGC’20). IEEE, 378–383.

[59]

Kiranpreet Kaur, Fabrice Guillemin, Veronica Quintuna Rodriguez, and Francoise Sailhan. 2022. Latency and network aware placement for cloud-native 5G/6G services. In Proceedings of the IEEE 19th Annual Consumer Communications & Networking Conference (CCNC’22). IEEE, 114–119.

Digital Library

[60]

Kiranpreet Kaur, Fabrice Guillemin, and Francoise Sailhan. 2022. Container placement and migration strategies for cloud, fog, and edge data centers: A survey. Int. J. Netw. Manag. 32, 6 (2022), e2212.

[61]

Chao Lei and Hongjun Dai. 2020. A heuristic services binding algorithm to improve fault-tolerance in microservice based edge computing architecture. In Proceedings of the IEEE World Congress on Services (SERVICES’20). IEEE, 83–88.

[62]

Isaac Lera, Carlos Guerrero, and Carlos Juiz. 2018. Availability-aware service placement policy in fog computing based on graph partitions. IEEE Internet Things J. 6, 2 (2018), 3641–3651.

[63]

Isaac Lera, Carlos Guerrero, and Carlos Juiz. 2019. YAFS: A simulator for IoT scenarios in fog computing. IEEE Access 7 (2019), 91745–91758.

[64]

Haiyan Li, Bing Tang, Wei Xu, Feiyan Guo, and Xiaoyuan Zhang. 2022. Application deployment in mobile edge computing environment based on microservice chain. In Proceedings of the IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD’22). IEEE, 531–536.

[65]

Jie Lin, Wei Yu, Nan Zhang, Xinyu Yang, Hanlin Zhang, and Wei Zhao. 2017. A survey on internet of things: Architecture, enabling technologies, security and privacy, and applications. IEEE Internet Things J. 4, 5 (2017), 1125–1142.

[66]

Marko Luksa. 2017. Kubernetes in Action. Simon and Schuster.

[67]

Wenkai Lv, Quan Wang, Pengfei Yang, Yunqing Ding, Bijie Yi, Zhenyi Wang, and Chengmin Lin. 2022. Microservice deployment in edge computing based on deep q learning. IEEE Trans. Parallel Distrib. Syst. 33, 11 (2022), 2968–2978.

[68]

Redowan Mahmud, Ramamohanarao Kotagiri, and Rajkumar Buyya. 2018. Fog computing: A taxonomy, survey and future directions. In Internet of Everything. Springer, 103–130.

[69]

Redowan Mahmud, Samodha Pallewatta, Mohammad Goudarzi, and Rajkumar Buyya. 2022. Ifogsim2: An extended ifogsim simulator for mobility, clustering, and microservice management in edge and fog computing environments. Journal of Systems and Software 190 (2022), 111351.

[70]

Redowan Mahmud, Kotagiri Ramamohanarao, and Rajkumar Buyya. 2020. Application management in fog computing environments: A taxonomy, review and future directions. ACM Comput. Surv. 53, 4 (2020), 1–43.

Digital Library

[71]

Hadi Tabatabaee Malazi, Saqib Rasool Chaudhry, Aqeel Kazmi, Andrei Palade, Christian Cabrera, Gary White, and Siobhán Clarke. 2022. Dynamic service placement in multi-access edge computing: A systematic literature review. IEEE Access 10 (2022), 32639–32688.

[72]

Mir Gholamreza Mortazavi, Mirsaeid Hosseini Shirvani, and Arash Dana. 2022. A discrete cuckoo search algorithm for reliability-aware energy-efficient IoT applications multi-service deployment in fog environment. In Proceedings of the International Conference on Electrical, Computer and Energy Technologies (ICECET’22). IEEE, 1–6.

[73]

Ranesh Kumar Naha, Saurabh Garg, Dimitrios Georgakopoulos, Prem Prakash Jayaraman, Longxiang Gao, Yong Xiang, and Rajiv Ranjan. 2018. Fog computing: Survey of trends, architectures, requirements, and research directions. IEEE Access 6 (2018), 47980–48009.

[74]

Zahra Makki Nayeri, Toktam Ghafarian, and Bahman Javadi. 2021. Application placement in Fog computing with AI approach: Taxonomy and a state of the art survey. J. Netw. Comput. Applic. 185 (2021), 103078.

[75]

Benazir Neha, Sanjaya Kumar Panda, Pradip Kumar Sahu, Kshira Sagar Sahoo, and Amir H. Gandomi. 2022. A systematic review on osmotic computing. ACM Trans. Internet Things 3, 2 (2022), 1–30.

Digital Library

[76]

Sam Newman. 2019. Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith. O’Reilly Media.

[77]

Yipei Niu, Fangming Liu, and Zongpeng Li. 2018. Load balancing across microservices. In Proceedings of the IEEE Conference on Computer Communications. IEEE, 198–206.

Digital Library

[78]

Roy Oberhauser. 2016. Microflows: Automated planning and enactment of dynamic workflows comprising semantically-annotated microservices. In Proceedings of the International Symposium on Business Modeling and Software Design. Springer, 183–199.

[79]

Samodha Pallewatta, Vassilis Kostakos, and Rajkumar Buyya. 2019. Microservices-based IoT application placement within heterogeneous and resource constrained fog computing environments. In Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing. 71–81.

Digital Library

[80]

Samodha Pallewatta, Vassilis Kostakos, and Rajkumar Buyya. 2022. QoS-aware placement of microservices-based IoT applications in Fog computing environments. Fut. Gen. Comput. Syst. 131 (2022), 121–136.

Digital Library

[81]

John Paul Martin, A. Kandasamy, and K. Chandrasekaran. 2020. CREW: Cost and reliability aware eagle-whale optimiser for service placement in Fog. Softw.: Pract. Exper. 50, 12 (2020), 2337–2360.

[82]

Mohammad Imranur Rahman, Sebastiano Panichella, and Davide Taibi. 2019. A curated dataset of microservices-based systems. In Joint Proceedings of the Inforte Summer School on Software Maintenance and Evolution (SSSME-2019). 1–9.

[83]

Nitin Rathore, Anand Rajavat, and Margi Patel. 2020. Investigations of microservices architecture in edge computing environment. In Social Networking and Computational Intelligence. Springer, 77–84.

[84]

Abdul Razzaq. 2020. A systematic review on software architectures for IoT systems and future direction to the adoption of microservices architecture. SN Comput. Sci. 1, 6 (2020), 1–30.

Digital Library

[85]

Ju Ren, Deyu Zhang, Shiwen He, Yaoxue Zhang, and Tao Li. 2019. A survey on end-edge-cloud orchestrated network computing paradigms: Transparent computing, mobile edge computing, fog computing, and cloudlet. ACM Comput. Surv. 52, 6 (2019), 1–36.

Digital Library

[86]

Chris Richardson. 2018. Microservices Patterns. Manning Publications Company.

[87]

Maria Alejandra Rodriguez and Rajkumar Buyya. 2017. A taxonomy and survey on scheduling algorithms for scientific workflows in IaaS cloud computing environments. Concurr. Computat.: Pract. Exper. 29, 8 (2017), e4041.

[88]

Oscar Ricardo Cuéllar Rodríguez, Claus Pahl, Nabil El Ioini, Hamid R. Barzegar, et al. 2021. Improvement of edge computing workload placement using multi objective particle swarm optimization. In Proceedings of the 8th International Conference on Internet of Things: Systems, Management and Security (IOTSMS’21). IEEE, 1–8.

[89]

Tasneem Salah, M. Jamal Zemerly, Chan Yeob Yeun, Mahmoud Al-Qutayri, and Yousof Al-Hammadi. 2016. The evolution of distributed systems towards microservices architecture. In Proceedings of the 11th International Conference for Internet Technology and Secured Transactions (ICITST’16). IEEE, 318–325.

[90]

Farah Ait Salaht, Frédéric Desprez, and Adrien Lebre. 2020. An overview of service placement problem in fog and edge computing. ACM Comput. Surv. 53, 3 (2020), 1–35.

Digital Library

[91]

Amit Samanta and Jianhua Tang. 2020. Dyme: Dynamic microservice scheduling in edge computing enabled IoT. IEEE Internet Things J. 7, 7 (2020), 6164–6174.

[92]

Cleber Santana, Brenno Alencar, and Cássio Prazeres. 2018. Microservices: A mapping study for internet of things solutions. In Proceedings of the IEEE 17th International Symposium on Network Computing and Applications (NCA’18). IEEE, 1–4.

[93]

Dharmendra Shadija, Mo Rezai, and Richard Hill. 2017. Microservices: Granularity vs. performance. In Proceedings of the 10th International Conference on Utility and Cloud Computing. 215–220.

Digital Library

[94]

Olena Skarlat, Matteo Nardelli, Stefan Schulte, and Schahram Dustdar. 2017. Towards QoS-aware fog service placement. In Proceedings of the IEEE 1st International Conference on Fog and Edge Computing (ICFEC’17). IEEE, 89–96.

[95]

Sven Smolka and Zoltán Ádám Mann. 2022. Evaluation of fog application placement algorithms: A survey. Computing 104, 6 (2022), 1397–1423.

Digital Library

[96]

Bing Tang, Feiyan Guo, Buqing Cao, Mingdong Tang, and Kuanching Li. 2022. Cost-aware deployment of microservices for IoT applications in mobile edge computing environment. IEEE Trans. Netw. Serv. Manag. (2022).

[97]

Lam Nguyen Tran Thanh, Nguyen Ngoc Phien, Hong Khanh Vo, Hoang Huong Luong, Tuan Dao Anh, Khoi Nguyen Huynh Tuan, Ha Xuan Son, et al. 2021. IoHT-MBA: An internet of healthcare things (IoHT) platform based on microservice and brokerless architecture. Int. J. Adv. Comput. Sci. Applic. 12, 7 (2021).

[98]

Muhammad Tirmazi, Adam Barker, Nan Deng, Md E. Haque, Zhijing Gene Qin, Steven Hand, Mor Harchol-Balter, and John Wilkes. 2020. Borg: The next generation. In Proceedings of the 15th European Conference on Computer Systems. 1–14.

Digital Library

[99]

Prateeksha Varshney and Yogesh Simmhan. 2020. Characterizing application scheduling on edge, fog, and cloud computing resources. Softw.: Pract. Exper. 50, 5 (2020), 558–595.

[100]

Jagannathan Venkatesh, Baris Aksanli, Christine S. Chan, Alper S. Akyürek, and Tajana S. Rosing. 2017. Scalable-application design for the IoT. IEEE Softw. 34, 1 (2017), 62–70.

Digital Library

[101]

Massimo Villari, Maria Fazio, Schahram Dustdar, Omer Rana, and Rajiv Ranjan. 2016. Osmotic computing: A new paradigm for edge/cloud integration. IEEE Cloud Comput. 3, 6 (2016), 76–83.

[102]

Hao Wang, Yong Wang, Guanying Liang, Yunfan Gao, Weijian Gao, and Wenping Zhang. 2021. Research on load balancing technology for microservice architecture. In Proceedings of the MATEC Web of Conferences, Vol. 336. EDP Sciences, 08002.

[103]

Shangguang Wang, Yan Guo, Ning Zhang, Peng Yang, Ao Zhou, and Xuemin Shen. 2019. Delay-aware microservice coordination in mobile edge computing: A reinforcement learning approach. IEEE Trans. Mob. Comput. 20, 3 (2019), 939–951.

[104]

Muhammad Waseem, Peng Liang, and Mojtaba Shahin. 2020. A systematic mapping study on microservices architecture in DevOps. J. Syst. Softw. 170 (2020), 110798.

[105]

Hiroki Watanabe, Tomonori Sato, Takao Kondo, and Fumio Teraoka. 2021. AFC: A mechanism for distributed data processing in edge/fog computing. In Proceedings of the IEEE Global Communications Conference (GLOBECOM’21). IEEE, 01–07.

[106]

Zhenyu Wen, Tao Lin, Renyu Yang, Shouling Ji, Rajiv Ranjan, Alexander Romanovsky, Changting Lin, and Jie Xu. 2019. GA-Par: Dependable microservice orchestration framework for geo-distributed clouds. IEEE Trans. Parallel Distrib. Syst. 31, 1 (2019), 129–143.

Digital Library

[107]

Roy Woodhead, Paul Stephenson, and Denise Morrey. 2018. Digital construction: From point solutions to IoT ecosystem. Autom. Construct. 93 (2018), 35–46.

[108]

Fulong Xu, Zhenyu Yin, Ai Gu, Feiqing Zhang, and Yue Li. 2020. A service redundancy strategy and ant colony optimization algorithm for multiservice fog nodes. In Proceedings of the IEEE 6th International Conference on Computer and Communications (ICCC’20). IEEE, 1567–1572.

[109]

Yangchuan Xu, Lulu Chen, Zhihui Lu, Xin Du, Jie Wu, and Patrick C. K. Hung. 2023. An Adaptive Mechanism for Dynamically Collaborative Computing Power and Task Scheduling in Edge Environment. IEEE Internet of Things Journal 10, 4 (2023), 3118–3129.

[110]

Saqing Yang, Yi Ren, Jianfeng Zhang, Jianbo Guan, and Bao Li. 2021. KubeHICE: Performance-aware container orchestration on heterogeneous-ISA architectures in cloud-edge platforms. In Proceedings of the IEEE International Conference on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom). IEEE, 81–91.

[111]

Ashkan Yousefpour, Caleb Fung, Tam Nguyen, Krishna Kadiyala, Fatemeh Jalali, Amirreza Niakanlahiji, Jian Kong, and Jason P. Jue. 2019. All one needs to know about fog computing and related edge computing paradigms: A complete survey. J. Syst. Archit. 98 (2019), 289–330.

Digital Library

[112]

Wei Zhang, Quan Chen, Kaihua Fu, Ningxin Zheng, Zhiyi Huang, Jingwen Leng, and Minyi Guo. 2022. Astraea: Towards QoS-aware and resource-efficient multi-stage GPU services. In Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems. 570–582.

Digital Library

[113]

Hailiang Zhao, Shuiguang Deng, Zijie Liu, Jianwei Yin, and Schahram Dustdar. 2019. Distributed redundant placement for microservice-based applications at the edge. arXiv preprint arXiv:1911.03600 (2019).

[114]

Hailiang Zhao, Shuiguang Deng, Zijie Liu, Jianwei Yin, and Schahram Dustdar. 2022. Distributed redundancy scheduling for microservice-based applications at the edge. IEEE Transactions on Services Computing 15, 3 (2022), 1732–1745.

[115]

Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenhai Li, and Dan Ding. 2018. Fault analysis and debugging of microservice systems: Industrial survey, benchmark system, and empirical study. IEEE Trans. Softw. Eng. 47, 2 (2018), 243–260.

Digital Library

[116]

Yousaf Bin Zikria, Rashid Ali, Muhammad Khalil Afzal, and Sung Won Kim. 2021. Next-generation internet of things (IoT): Opportunities, challenges, and solutions. Sensors 21, 4 (2021), 1174.

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Chen STang HZhao MChen YYang XHu K(2024)Efficient Scheduling of Energy-Constrained Tasks in Internet of Things Edge Computing NetworksInternational Journal of Swarm Intelligence Research10.4018/IJSIR.35022115:1(1-17)Online publication date: 26-Jul-2024
https://dl.acm.org/doi/10.4018/IJSIR.350221
Umamaheswari P(2024)From Theory to PracticeAdvanced Applications in Osmotic Computing10.4018/979-8-3693-1694-8.ch005(73-89)Online publication date: 29-Mar-2024
https://doi.org/10.4018/979-8-3693-1694-8.ch005
Arcas GCioara TAnghel ILazea DHangan A(2024)Edge Offloading in Smart GridSmart Cities10.3390/smartcities70100287:1(680-711)Online publication date: 19-Feb-2024
https://doi.org/10.3390/smartcities7010028
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Index Terms

Placement of Microservices-based IoT Applications in Fog Computing: A Taxonomy and Future Directions
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
2. General and reference
  1. Document types
    1. General literature

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Published In

cover image ACM Computing Surveys

ACM Computing Surveys Volume 55, Issue 14s

December 2023

1355 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3606253

Editor:
Albert Zomaya
University of Sydney, Australia

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Publication History

Published: 17 July 2023

Online AM: 12 April 2023

Accepted: 02 April 2023

Revised: 28 March 2023

Received: 05 January 2023

Published in CSUR Volume 55, Issue 14s

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Cited By

Chen STang HZhao MChen YYang XHu K(2024)Efficient Scheduling of Energy-Constrained Tasks in Internet of Things Edge Computing NetworksInternational Journal of Swarm Intelligence Research10.4018/IJSIR.35022115:1(1-17)Online publication date: 26-Jul-2024
https://dl.acm.org/doi/10.4018/IJSIR.350221
Umamaheswari P(2024)From Theory to PracticeAdvanced Applications in Osmotic Computing10.4018/979-8-3693-1694-8.ch005(73-89)Online publication date: 29-Mar-2024
https://doi.org/10.4018/979-8-3693-1694-8.ch005
Arcas GCioara TAnghel ILazea DHangan A(2024)Edge Offloading in Smart GridSmart Cities10.3390/smartcities70100287:1(680-711)Online publication date: 19-Feb-2024
https://doi.org/10.3390/smartcities7010028
Šatkauskas NVenčkauskas A(2024)Multi-Agent Dynamic Fog Service Placement ApproachFuture Internet10.3390/fi1607024816:7(248)Online publication date: 13-Jul-2024
https://doi.org/10.3390/fi16070248
Zhang XLiang JLu YZhang PBi Y(2024)Differentiated Security Requirements: An Exploration of Microservice Placement Algorithms in Internet of VehiclesElectronics10.3390/electronics1308159713:8(1597)Online publication date: 22-Apr-2024
https://doi.org/10.3390/electronics13081597
El Akhdar ABaidada CKartit A(2024)Adaptability of Microservices Architecture in IoT Systems : A Comprehensive ReviewProceedings of the 7th International Conference on Networking, Intelligent Systems and Security10.1145/3659677.3659734(1-9)Online publication date: 18-Apr-2024
https://dl.acm.org/doi/10.1145/3659677.3659734
He XXu HXu XChen YWang Z(2024)An Efficient Algorithm for Microservice Placement in Cloud-Edge Collaborative Computing EnvironmentIEEE Transactions on Services Computing10.1109/TSC.2024.339965017:5(1983-1997)Online publication date: Sep-2024
https://doi.org/10.1109/TSC.2024.3399650
Böhm SWirtz G(2024)Towards an API-driven Approach for Universal and Lightweight Cloud-Edge Orchestration2024 IEEE International Conference on Service-Oriented System Engineering (SOSE)10.1109/SOSE62363.2024.00012(46-53)Online publication date: 15-Jul-2024
https://doi.org/10.1109/SOSE62363.2024.00012
Shahzaad BBarros AFidge C(2024)Edge-Mapping of Service Function Trees for Sensor Event Processing2024 IEEE International Conference on Web Services (ICWS)10.1109/ICWS62655.2024.00146(1227-1237)Online publication date: 7-Jul-2024
https://doi.org/10.1109/ICWS62655.2024.00146
Kumar KSiddesh GAnanda Babu J(2024)An Empirical Analysis of Load Balancing Issues in Fog Computing Environment2024 Second International Conference on Data Science and Information System (ICDSIS)10.1109/ICDSIS61070.2024.10594459(1-5)Online publication date: 17-May-2024
https://doi.org/10.1109/ICDSIS61070.2024.10594459
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