Metaheuristicsbased Task Offloading Framework in Fog Computing for Latency-sensitive Internet of Things Applications

Title

Metaheuristicsbased Task Offloading Framework in Fog Computing for Latency-sensitive Internet of Things Applications

Creator

Thomas P.; Jose D.V.

Description

The Internet of Things (IoT) applications have tremendously increased its popularity within a short span of time due to the wide range of services it offers. In the present scenario, IoT applications rely on cloud computing platforms for data storage and task offloading. Since the IoT applications are latency-sensitive, depending on a remote cloud datacenter further increases the delay and response time. Most of the IoT applications shift from cloud to fog computing for improved performance and to lower the latency. Fog enhances the Quality of service (QoS) of the connected applications by providing low latency. Different task offloading schemes in fog computing are proposed in literature to enhance the performance of IoT-fog-cloud integration. The proposed methodology focuses on constructing a metaheuristic based task offloading framework in the three-tiered IoT-fog-cloud network to enable efficient execution of latency-sensitive IoT applications. The proposed work utilizes two effective optimization algorithms such as Flamingo search algorithm (FSA) and Honey badger algorithm (HBA). Initially, the FSA algorithm is executed in an iterative manner where the objective function is optimized in every iteration. The best solutions are taken in this algorithm and fine tuning is performed using the HBA algorithm to refine the solution. The output obtained from the HBA algorithm is termed as the optimized outcome of the proposed framework. Finally, evaluations are carried out separately based on different scenarios to prove the performance efficacy of the proposed framework. The proposed framework obtains the task offloading time of 71s and also obtains less degree of imbalance and lesser latency when compared over existing techniques. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Networks and Systems, Vol-689 LNNS, pp. 221-239.

Date

2023-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Cloud computing; Fog computing; Internet of things; Latency-sensitive IoT; Quality of service; Task offloading

Coverage

Thomas P., CHRIST (Deemed to Be University), Karnataka, Bangalore, India; Jose D.V., CHRIST (Deemed to Be University), Karnataka, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981992321-2

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-99-2322-9_17

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