Abstract
Advancements in the Internet of Things and Information Communication and Technologies have increased the demand for real-time services. Thus computing resources are migrated from the cloud to fog networks to give the users near real-time experiences. Fog computing resources containing storage and networks that are shifted from core to edge to minimize the latency while using the applications-application implementation nearest to fog nodes that reduce the latency however burden leans on the density of users. The fog network performance degrades because of the over-subscription of fog nodes. In this work, we have proposed a method that depends on alliance establishment for resource management while using the model that will charge according to the usage of network resources. We assume that the cluster contains one prime node with several fog nodes. Firstly, the customer needs information regarding the application requirement for the clusters then the prime node evaluates the capacity of the fog node, which fulfills desired demands of the end user. According to end-user requirements, the prime node among the cluster selects the specific symmetry batch nodes. Additionally, in this work, we have suggested an extension of resource handling regarding fog networks, combining end-user demands for the service and allocating individual nodes against the batch application.
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Aazam, M., Huh, E.-N., St-Hilaire, M., Lung, C.-H., Lambadaris, I.: Cloud customer’s historical record based resource pricing. IEEE Trans. Parallel Distrib. Syst. 27(7), 1929–1940 (2015)
Abedin, S.F., Alam, Md.G.R., Kazmi, S.M.A.hsan., Tran, N.H., Niyato, D., Hong, C.S.: Resource allocation for ultra-reliable and enhanced mobile broadband IoT applications in fog network. IEEE Trans. Commun. 67(1), 489–502, (2018)
Awaisi, K.S., et al.: Towards a fog enabled efficient car parking architecture. IEEE Access. 7 , 159100–159111 (2019)
Chakraborty, A., Mondal, A., Misra, S.: Cache-enabled sensor-cloud: the economic facet. In: 2018 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–6. IEEE (2018)
Chakraborty, A., Mondal, A., Roy, A., Misra, S.: Dynamic trust enforcing pricing scheme for sensors-as-a-service in sensor-cloud infrastructure. IEEE Trans. Serv. Comput. 14(5), 1345–1356 (2018)
Farooq, M.J., Zhu, Q.: QoE based revenue maximizing dynamic resource allocation and pricing for fog-enabled mission-critical IoT applications. IEEE Trans. Mob. Comput. 20(12), 3395–3408 (2020)
Halima, R.B., Kallel, S., Gaaloul, W., Maamar, Z., Jmaiel, M.: Toward a correct and optimal time-aware cloud resource allocation to business processes. Future Gener. Comput. Syst. 112,pp. 751–766 (2020)
Subhas Chandra Misra and Ayan Mondal: FOGPRIME: dynamic pricing-based strategic resource management in fog networks. IEEE Trans. Veh. Technol. 70(8), 8227–8236 (2021)
Misra, S., Schober, R., Chakraborty, A.: Race: QoI-aware strategic resource allocation for provisioning Se-aaS. IEEE Trans. Serv. Comput. (2020)
Nguyen, D.T., Le, L.B., Bhargava, V.K.: A market-based framework for multi-resource allocation in fog computing. IEEE/ACM Trans. Networking. 27(3), 1151–1164 (2019)
Raja, F.Z., Khattak, H.A., Aloqaily, M., Hussain, R.: Carpooling in connected and autonomous vehicles Current solutions and future directions. ACM Comput. Surv. 1(1), 1–35 (2021)
Yang, Y., Huang, J., Zhang, T., Weinman, J.: Challenges and practices of fog computing, communication, networking, strategy, and economics, Fog and fogonomics (2020)
Zafar, F., Khattak, H.A., Aloqaily, M., Hussain, H.: Carpooling in connected and autonomous vehicles current solutions and future directions. ACM Computing Surveys (CSUR), 54(10s), 1–36 (2022)
Zhao, Z., et al.: On the design of computation offloading in fog radio access networks. IEEE Trans. Veh. Techno.68(7), pp. 7136–7149 (2019)
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Khan, Z., Khattak, H.A., Abbas, A., Khan, S.U. (2023). Fog Resource Sharing to Enable Pay-Per-Use Model. In: Haas, Z.J., Prakash, R., Ammari, H., Wu, W. (eds) Wireless Internet. WiCON 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 464. Springer, Cham. https://doi.org/10.1007/978-3-031-27041-3_10
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DOI: https://doi.org/10.1007/978-3-031-27041-3_10
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