Abstract
The devices in the Internet of Things (IoT) communicate through the Internet without human intervention. An enormous number of devices and their generated data leads to several challenges such as data processing at appropriate devices, resource discovery, mapping, and provisioning. The proposed work addresses the management of the workload of devices by offering resources through the fog computing paradigm with less cost and energy consumption. Distributed provision solves the problem of multiple requests having similar response time requirements. It categorizes such requests into different swarms and provides the resources through various fog devices existing in several fog colonies. Each swarm gets mapped to one or more fog colonies considering response time, total resource capacity, and distance between them. Fitness value for all the tasks in a swarm is calculated for binding to fog colony using Multi-Objective Particle Swarm Optimization (MOPSO). In each swarm, the existing requests are mapped to suitable fog devices for processing and avoid overloading and under-provision of fog devices. The performance of the proposed model is evaluated in the CloudSim-Plus framework by the varying capacity of fog instances in terms of small, medium, high, and mixed resources set, tasks/cloudlet length, and response time of requests.
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Acknowledgements
The authors thank Basaveshwar Engineering College, Bagalkot and BLDEA’s V.P. Dr. P. G. Halakatti College of Engineering and Technology, Vijayapur for providing the facilities and support in doing the work.
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Hatti, D.I., Sutagundar, A.V. (2022). Resource Provisioning in Fog-Based IoT. In: Smys, S., Balas, V.E., Palanisamy, R. (eds) Inventive Computation and Information Technologies. Lecture Notes in Networks and Systems, vol 336. Springer, Singapore. https://doi.org/10.1007/978-981-16-6723-7_33
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