Application Offloading Strategy for Hierarchical Fog Environment Through Swarm Optimization

dc.contributor.author Adhikari, Mainak
dc.contributor.author Srirama, Satish Narayana
dc.contributor.author Amgoth, Tarachand
dc.date.accessioned 2022-03-27T06:03:55Z
dc.date.available 2022-03-27T06:03:55Z
dc.date.issued 2020-05-01
dc.description.abstract Nowadays, billions of Internet-of-Things devices generate various types of delay-sensitive tasks to process within a limited time frame. By processing the tasks at the network edge using distributed fog devices can efficiently overcome the deficiency of the centralized cloud data center (CDC), i.e., long latency and network congestion. Moreover, to overcome the inefficiency of the local fog devices, i.e., limited processing and storage capabilities, we investigate the collaboration between distributed fog devices and centralized CDC, where the delay-sensitive tasks can preferably be offloaded on the local fog devices, whereas the resource-intensive tasks are offloaded on the resource-rich CDC. However, one of the challenging tasks in the fog-cloud environment is to find a suitable computing device for each real-time task by considering tradeoff between the latency and cost. To meet the above-mentioned challenge, in this article, we introduce an optimal application offloading strategy in the hierarchical fog-cloud environment using the accelerated particle swarm optimization (APSO) technique. The proposed APSO-based strategy finds an optimal computing device (i.e., fog device or cloud server) for each real-time task using multiple quality-of-service parameters, namely, cost and resource utilization (RU). The performance of the proposed algorithm is evaluated using four different real-time data sets with various performance matrices. The experimental results indicate that the proposed strategy outperforms the existing schemes in terms of average delay, computation time, RU, and average cost by 18%, 21%, 27%, and 23%, respectively.
dc.identifier.citation IEEE Internet of Things Journal. v.7(5)
dc.identifier.uri 10.1109/JIOT.2019.2958400
dc.identifier.uri https://ieeexplore.ieee.org/document/8931777/
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/9242
dc.subject Accelerated particle swarm optimization (APSO) technique
dc.subject application offloading
dc.subject delay-sensitive application
dc.subject fog computing
dc.subject Internet of Things (IoT)
dc.subject multiobjective optimization
dc.title Application Offloading Strategy for Hierarchical Fog Environment Through Swarm Optimization
dc.type Journal. Article
dspace.entity.type
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