Abstract
Fog computing has been introduced in recent years to extend cloud services to the network edge in order to minimize network delay and network congestion and overcome cloud computing limitations. However, several challenges are yet to be addressed in order to achieve the full benefits of the fog-IoT paradigm for low latency applications. The foremost crucial challenge is designing efficient resource management schemes capable of maximizing the throughput and minimizing the delay of IoT application. In this paper, we propose a QoS-aware greedy edge placement scheme that defines the way in which application modules are distributed across fog devices in order to minimize the end-to-end latency of real-time IoT applications. The proposed scheme is composed of two stages: a greedy-delay minimizing application module selection stage and a greedy-delay minimizing application module placement stage. The first stage aims to reduce the end-to-end latency by determining the order in which the application modules are placed across fog devices to maintain high QoS of real-time applications. The second stage uses the depth first search algorithm to select the fog node that meets application modules’ processing, storage and bandwidth requirements. To evaluate the performance of the proposed scheme intelligent surveillance through distributed camera networks application was used. The application modules are mapped onto fog nodes connected in different configurations. The experimental results demonstrate that the proposed scheme provides high QoS by reducing the end-to-end latency, the network usage and the energy consumption.
Similar content being viewed by others
Data Availability
All data generated or analyzed during this study are included in this article.
Code availability
All software applications used in this study are stated in this article.
References
Aazam, M, Khan, I, Alsaffar, AA, Huh, EN (2014) Cloud of things: integrating internet of things and cloud computing and the issues involved. In proceedings of 2014 11th international Bhurban conference on applied sciences & technology (IBCAST) Islamabad, Pakistan, 14th-18th January, 2014 (pp. 414-419). IEEE
Abreu D, et.al. (2020) A comparative analysis of simulators for the cloud to fog continuum. Simulation and Modelling: practice and Theory 101
Al-khafajiy, M, Baker, T, Al-Libawy, H, Waraich, A, Chalmers, C, Alfandi, O (2018) Fog Computing framework for internet of things applications. In the 2018 11th international conference on developments in eSystems engineering (DeSE) (pp. 71-77). IEEE
Badidia E, Ragmanib A (2020) An architecture for QoS-aware fog service provisioning. Procedia Comput Sci 170:411–418
Bermbach D, Pallas F, Pérez DG, Plebani P, Anderson M, Kat R, Tai S (2017) A research perspective on fog computing. In international conference on service-oriented Computing (pp. 198-210). Springer, Cham
Bittencourt LF, Diaz-Montes J, Buyya R, Rana OF, Parashar M (2017) Mobility-aware application scheduling in fog computing. IEEE Cloud Comput 4(2):26–35
Bonomi, F, Milito, R, Zhu, J, Addepalli, S (2012) Fog computing and its role in the internet of things. In proceedings of the first edition of the MCC workshop on Mobile cloud computing, pp. 13-16
Bonomi F, Milito R, Natarajan P, Zhu, J (2014) Fog computing: a platform for internet of things and analytics. In: Bessis N, Dobre C. (eds) big data and internet of things: a roadmap for smart environments. studies in computational intelligence, vol 546. Springer, Cham. https://doi.org/10.1007/978-3-319-05029-4_7
Brogi A, Forti S (2017) QoS-aware deployment of IoT applications through the fog. IEEE Internet Things J 4(5):1185–1192
Chiang M, Zhang T (2016) Fog and IoT: an overview of research opportunities. IEEE Internet Things J 3(6):854–864
Computing, F (2015) The internet of things: extend the cloud to where the things are. Cisco White Paper
Da Xu L, He W, Li S (2014) Internet of things in industries: a survey. IEEE Trans Indust Inf 10(4):2233–2243
Dastjerdi AV, Buyya R (2016) Fog computing: helping the internet of things realize Its potential in Computer 49(8):112–116. https://doi.org/10.1109/MC.2016.245
Firdhous M, Ghazali O, Hassan S (2014) Fog computing: will it be the future of cloud computing? The third international conference on Informatics & Applications (ICIA2014), pp. 8–15
Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of things (IoT): a vision, architectural elements, and future directions. Futur Gener Comput Syst 29(7):1645–1660
Gupta H, Vahid Dastjerdi A, Ghosh SK, Buyya R (2017) iFogSim: A toolkit for modeling and simulation of resource management techniques in the internet of things, edge and fog computing environments. Softw Practice Exp 47(9):1275–1296
Hong, CH, Varghese, B (2018) Resource Management in fog/edge Computing: a survey. arXiv preprint arXiv:1810.00305
Huang X, Cui Y, Chen Q, Zhang J (2020) Joint Task Offloading and QoS-aware resource allocation in fog-enabled internet-of-things networks in IEEE Internet Things J 7(8):7194–7206. https://doi.org/10.1109/JIOT.2020.2982670
Hussain MI (2017). Internet of things: challenges and research opportunities. CSI transactions on ICT 5(1):87–95. https://doi.org/10.1007/s40012-016-0136-6
Jiang Y, Huang Z, Tsang DH (2018) Challenges and Solutions in Fog computing orchestration in IEEE Network 32(3):122–129. https://doi.org/10.1109/MNET.2017.1700271
Kashani M, Rahmani A, Navimipour N (2020) Quality of service-aware approaches in fog computing. Int J Commun Syst 33(4):1–34. https://doi.org/10.1002/dac.4340
Kosmatos EA, Tselikas ND, Boucouvalas AC (2011) Integrating RFIDs and smart objects into a UnifiedInternet of things architecture. Adv Int Things 1(01):5–12. https://doi.org/10.4236/ait.2011.11002
Lai, CF, Song, DY, Hwang, RH, Lai, YX (2016) A QoS-aware streaming service over fog computing infrastructures. In 2016 Digital Media Industry & Academic Forum (DMIAF), pp. 94-98
Lee I, Lee K (2015) The internet of things (IoT): applications, investments, and challenges for enterprises. Bus Horiz 58(4):431–440
Madakam S, Ramaswamy R, Tripathi S (2015) Internet of things (IoT): a literature review. J Comput Commun 3(05):164–173
Maiti, P, Shukla, J, Sahoo, B, Turuk, AK (2018) QoS-aware fog nodes placement. In 2018 4th Int. Conf. on Recent Advances in Information Technology (RAIT),pp. 1–6. https://doi.org/10.1109/RAIT.2018.8389043
Maiti P et al. (2019) QoS-aware service provisioning in heterogeneous fog computing supporting IoT applications. In proc. IEEE Int. Conf. on Vision Towards Emerging Trends in Communication and Networking (ViTECoN)
Mohan, N, Kangasharju, J (2016) Edge-fog cloud: a distributed cloud for internet of things computations. In 2016 Cloudification of the internet of things (CIoT), pp. 1–6. https://doi.org/10.1109/CIOT.2016.7872914
Murtazaa F, Akhunzadaab A, Islamc S u, Boudjadard J, Buyya R (2020) QoS-aware service provisioning in fog computing. J Netw Comput Appl 165:102674
Peng D, Sun L, Zhou R, Wang YL (2022) Study QoS-aware Fog Computing for Disease Diagnosis and Prognosis Mobile Netw Appl. https://doi.org/10.1007/s11036-022-01957-z
Saharan, KP, Kumar, A (2015) Fog in comparison to cloud: a survey. Int J Comput Appl, 122(3)
Sofla M, Kashani M, Mahdipour E, Mirzaee R (2022) Towards effective offloading mechanisms in fog computing. Multimed Tools Appl 81:1997–2042
Solutions, CFC (2015) Unleash the power of the Internet of Things. Cisco Systems Inc
Stankovic JA (2014) Research directions for the internet of things. IEEE Internet Things J 1(1):3–9
Wang R, Lu J (2021) QoS-Aware Service Discovery and Selection Management for Cloud-Edge Computing Using a Hybrid Meta-Heuristic Algorithm in IoT Wireless Pers Commun. https://doi.org/10.1007/s11277-021-09052-4
White G, Nallur V, Clarke S (2017) Quality of service approaches in IoT: a systematic mapping. J Syst Softw 132:186–203
Whitmore A, Agarwal A, Da Xu L (2015) The internet of things—a survey of topics and trends. Inf Syst Front 17(2):261–274. https://doi.org/10.1007/s10796-014-9489-2
Yao J, Ansari N (2019) QoS-aware fog resource provisioning and Mobile device power control in IoT networks. IEEE Trans Netw Serv Manag 16(1):167–175
Yi, S, Li, C, Li, Q (2015) A survey of fog computing: concepts, applications and issues. In proceedings of the 2015 workshop on mobile big data (pp. 37-42)
Yousefpour A, Ishigaki G, Gour R, Jue JP (2018) On reducing IoT service delay via fog offloading. IEEE Internet Things J 5(2):998–1010
Zhao D, Zou Q, Zadeh M (2022) A QoS-aware IoT service placement mechanism in fog computing based on open-source development model. J Grid Computing 20(12). https://doi.org/10.1007/s10723-022-09604-3
Funding
This research was not funded.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflicts of interest
This article has no potential conflicts of interest.
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
Abu-Amssimir, N., Al-Haj, A. A QoS-aware resource management scheme over fog computing infrastructures in IoT systems. Multimed Tools Appl 82, 28281–28300 (2023). https://doi.org/10.1007/s11042-023-14856-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-023-14856-6