Abstract
The emergence of a new generation of applications such as the Internet of Things, Artificial Intelligence, and 5G has brought fog computing as cloud development toward the edge network. It is done by adding an extra layer of resources to meet low latency, high performance, mobility, and interoperability challenges. The development of fog markets and new beneficial business paradigms such as fog services considerably affect the future of fogonomics (which is defined as the economics of fog computing). Thus, it is a challenging issue to design a market-oriented model to deal with the economics-based resource management in fog computing, which adjusts the resource supply of Fog Resource Providers (FRPs) and the demands of User Services (USs) based on users’ requirements while satisfying all parties’ utilities. This paper proposes the Fog-Marketing scheme consisting of a Resource Propagation Component (RPC) and a Contract-aware Market Selection Component (CMSC) for resource provisioning in multi-tier fog computing. The RPC is deployed in each fog node to perform hierarchical resource propagation of FRPs to auction-based Fog Decentralized Markets (FDMs) close to USs to increase revenue opportunities, and embedded CMSC in the user agent applies a matching strategy to assign USs and FDMs aims to promote USs’ utility. The simulation results under extensive experiments confirmed that the proposed scheme succeeded in reducing the Round-Trip-Time, increasing the revenue of FRPs, and improving the utility of USs compared to existing models.
Similar content being viewed by others
Data availability
The data of this paper are the result of simulation and all the data are presented in the form of graphs inside the paper. There is no private data in this article.
References
Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of Things (IoT): a vision, architectural elements, and future directions. Future Gener Comput Syst 29(7):1645–1660
OpenFog Consortium (2017) The OpenFog consortium reference architecture. https://www.iiconsortium.org/pdf/OpenFog_Reference_Architecture_2_09_17.pdf. Accessed 10 June 2023
Chiang M, Zhang T (2016) Fog and IoT: an overview of research opportunities. IEEE Internet Things J 3(6):854–864
Hu P, Dhelim S, Ning H, Qiu T (2017) Survey on fog computing: architecture, key technologies, applications and open issues. J Netw Comput Appl 98:27–42
Mouradian C, Naboulsi D, Yangui S, Glitho RH, Morrow MJ, Polakos PA (2017) A comprehensive survey on fog computing: state-of-the-art and research challenges. IEEE Commun Surv Tutor 20(1):416–464
Sabireen H, Neelanarayanan VJ (2021) A review on fog computing: architecture, fog with IoT, algorithms and research challenges. Ict Express 7(2):162–176
Yang Y, Huang J, Zhang T, Weinman J (2020) Fog and fogonomics: challenges and practices of fog computing, communication, networking, strategy, and economics. Wiley, Hoboken
Hong CH, Varghese B (2019) Resource management in fog/edge computing: a survey on architectures, infrastructure, and algorithms. ACM Comput Surv (CSUR) 52(5):1–37
Ma Z, Zou S (2020) Efficient auction games: theories, algorithms and applications in smart grids & electric vehicle charging. Springer, Singapore
Sharghivand N, Derakhshan F, Siasi N (2021) A comprehensive survey on auction mechanism design for cloud/edge resource management and pricing. IEEE Access 9:126502–126529
Xu J, Palanisamy B, Ludwig H, Wang Q (2017) Zenith: utility-aware resource allocation for edge computing. In: 2017 IEEE International Conference on Edge Computing (EDGE), pp 47–54
Tasiopoulos A, Ascigil O, Psaras I, Pavlou G (2018) Edge-MAP: auction markets for edge resource provisioning. In: 2018 IEEE 19th International Symposium on “A World of Wireless, Mobile and Multimedia Networks”(WoWMoM), pp 14–22
Li C, Cai Q, Zhang C, Ma B, Luo Y (2021) Computation offloading and service allocation in mobile edge computing. J Supercomput 77(12):13933–13962
Landa R, Charalambides M, Clegg RG, Griffin D, Rio M (2016) Self-tuning service provisioning for decentralized cloud applications. IEEE Trans Netw Serv Manag 13(2):197–211
Tasiopoulos A, Ascigil, O, Psaras I, Toumpis S, Pavlou G (2018) On-path cloudlet pricing for low latency application provisioning. In: 2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), pp 31–36
Siasi N, Jasim M, Ghani N (2020) Service function chain mapping in fog networks. IEEE Commun Lett 25(1):99–102
Jasim MA, Siasi N, Ghani N (2022) Hierarchy descending SFC provisioning scheme with load balancing in fog computing. IEEE Commun Lett 26(9):2096–2100
Yousefpour A, Fung C, Nguyen T, Kadiyala K, Jalali F, Niakanlahiji A, Jue JP (2019) All one needs to know about fog computing and related edge computing paradigms: a complete survey. J Syst Architect 98:289–330
Ghobaei-Arani M, Souri A, Rahmanian AA (2020) Resource management approaches in fog computing: a comprehensive review. J Grid Comput 18(1):1–42
Abedin SF, Alam MGR, Tran NH, Hong CS (2015) A Fog based system model for cooperative IoT node pairing using matching theory. In: 2015 17th Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, pp 309–314
Aazam M, Huh EN (2015) Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT. In: 2015 IEEE 29th International Conference on Advanced Information Networking and Applications, pp 687–694
Zhang H, Xiao Y, Bu S, Niyato D, Yu FR, Han Z (2017) Computing resource allocation in three-tier IoT fog networks: A joint optimization approach combining Stackelberg game and matching. IEEE Internet Things J 4(5):1204–1215
Siasi N, Jaesim A, Ghani N (2019) Tabu search for efficient service function chain provisioning in fog networks. In: 2019 IEEE 5th International Conference on Collaboration and Internet Computing (CIC), pp 145–150
Yao J, Ansari N (2019) Fog resource provisioning in reliability-aware IoT networks. IEEE Internet Things J 6(5):8262–8269
Santos J, Wauters T, Volckaert B, De Turck F (2021) Towards end-to-end resource provisioning in fog computing over low power wide area networks. J Netw Comput Appl 175:102915
Santos J, Wauters T, Volckaert B, De Turck F (2021) Resource provisioning in fog computing through deep reinforcement learning. In: 2021 IFIP/IEEE International Symposium on Integrated Network Management (IM), pp 431–437
Etemadi M, Ghobaei-Arani M, Shahidinejad A (2021) A learning-based resource provisioning approach in the fog computing environment. J Exp Theor Artif Intell 33(6):1033–1056
Lu S, Wu J, Wang N, Duan Y, Liu H, Zhang J, Fang J (2023) Resource provisioning in collaborative fog computing for multiple delay-sensitive users. Softw Pract Exp 53(2):243–262
Kumar Pg Ali DS, Newaz SS, Rahman FH, Lee GM, Karmakar G, Au TW (2022) Green demand aware fog computing: a prediction-based dynamic resource provisioning approach. Electronics 11(4):608
Miele A, Zárate H, Cassano L, Bolchini C, Ortiz JE (2022) A runtime resource management and provisioning middleware for fog computing infrastructures. ACM Trans Internet Things 3(3):1–29
Habiba U, Maghsudi S, Hossain E (2023) A repeated auction model for load-aware dynamic resource allocation in multi-access edge computing. IEEE Trans Mobile Comput
Chekired DA, Khoukhi L (2018) Multi-tier fog architecture: a new delay-tolerant network for IoT data processing. In: 2018 IEEE International Conference on Communications (ICC), pp 1–6
Andersson T, Erlanson A (2013) Multi-item Vickrey–English–Dutch auctions. Games Econ Behav 81:116–129
Schwartz J, Steger A, Weißl A (2005) Fast algorithms for weighted bipartite matching. In: Experimental and Efficient Algorithms: 4th International Workshop, WEA 2005, Santorini Island, Greece, May 10–13, 2005. Proceedings, vol 4, pp 476–487
Giuliano P, Matranga A (2021) Historical data: where to find them, how to use them. In: Bisin A, Federico G (eds) The handbook of historical economics. Academic Press, Cambridge, pp 95–123
Yousefpour A, Patil A, Ishigaki G, Kim I, Wang X, Cankaya HC, Jue JP (2019) FOGPLAN: A lightweight QoS-aware dynamic fog service provisioning framework. IEEE Internet Things J 6(3): 5080–5096
Acknowledgements
Not applicable.
Funding
No funds, grants, or other support was received.
Author information
Authors and Affiliations
Contributions
All authors contributed to writing the manuscript, reviewed it, and made necessary changes before submission.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflict of interest.
Ethical approval
This paper is the authors’ original work that has not been published and is not submitted simultaneously for publication elsewhere.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Shahinifar, S., Kheirabadi, M.T., Broumandnia, A. et al. Fog-Marketing: auction-based multi-tier decentralized markets for fog resource provisioning. J Supercomput (2024). https://doi.org/10.1007/s11227-024-06081-1
Accepted:
Published:
DOI: https://doi.org/10.1007/s11227-024-06081-1