Title: An IoT-based two-factor divide and conquer task scheduler and deep resource allocator for cloud computing

Authors: Sripriya Arun; Sundara Rajan

Addresses: Alpha Arts & Science College, Porur, No.30, Tundalam Road, Chettiyar Agaram Road, Behind Ramachandra Hospital, Porur, Chennai, Tamil Nadu 600116, India ' Government Arts College for Men, No.329, Annasalai, Nandanam, Chennai – 600035, India

Abstract: The epidemic developing rate of the networking technologies has resulted in an impressive sizeable scope of the associated computing framework. Internet-of-things (IoT) is considered a substitute for acquiring high performance by the improved potentialities in task scheduling, resource allocations and information exchanges. However, the current IoT is experiencing the gridlock of the task scheduling and resource allocation due to the higher level of dependency while scheduling and convoluted service contributing frameworks. With task scheduling and resource allocation considered with salient characteristics of cloud computing (CC) environment, this paper proposes a method called two-factor task scheduler and deep resource allocator (TFTS-DRA) based on IoT. In this method, each task is processed before its actual allocation to the cloud resources by cost and time-based divide and conquer task scheduling model. The resources are allocated using deep resource allocation model, which considers the auto encoder (AE) and fully connected neural network (FCNN) with energy consumption and transmission delay of cloud resources as constraints. Simulation results show that the proposed TFTS-DRA method performs in an extensive manner with higher throughput rate. The numerical results shows that proposed deep resource allocator algorithm in an IoT-CC environment, both the bandwidth utilisation and energy consumption can be improved.

Keywords: internet of things; IoT; cloud computing; two factors; task scheduler; deep resource allocator; auto encoder; fully connected neural network.

DOI: 10.1504/IJITST.2022.119678

International Journal of Internet Technology and Secured Transactions, 2022 Vol.12 No.1, pp.61 - 79

Received: 29 Apr 2020
Accepted: 28 Sep 2020
Published online: 14 Dec 2021 *