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SLA Aware Optimized Task Scheduling Model for Faster Execution of Workloads Among Federated Clouds

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Abstract

The evolvement of data intensive applications in the cloud computing platform increased the burden of the cloud and resulted in the violation of the service level agreement (SLA). Moreover, the single cloud scenario offers no flexibility to switch between cloud service providers (CPs), leading to limited resource utilization and slower execution. To resolve these issues, this article introduces a hierarchical framework for task scheduling in a federated cloud scenario with multiple datacenters (DCs). The dynamic tasks with different resource requirements are considered to arrive at the federated cloud environment for successful execution. Initially, the task agent receives the tasks and clusters them using the proposed enhanced density peaks clustering (EDPC) algorithm. The proposed clustering algorithm clusters the tasks based on their resource requirements and results in two clusters such as CPU demanding tasks and I/O demanding tasks. After clustering, the tasks are sent to the federation layer, where the scheduling decisions are taken for the tasks. The federated cloud manager (FCM) within the cloud service provider (CP) communicates with the available DCs regarding resource availability. If the resources cannot satisfy the needs, they extend communication with the neighboring FCMs within the federation to complete the execution of tasks. After acquiring the availability status of the entire federation, the FCM executes the African vultures optimization algorithm (AVOA) based task scheduling framework to make the scheduling decision. The performance of the proposed model is evaluated using the GWT T-12 Bit Brains dataset by implementation in the CloudSim tool. The proposed model proved its efficacy over the compared metaheuristics in different metrics.

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  1. School of Computer Science and Applications, REVA University, Bengaluru, Karnataka, 560064, India

    Divya Kshatriya & Vijayalakshmi A. Lepakshi

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  1. Divya Kshatriya
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  2. Vijayalakshmi A. Lepakshi
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Divya Kshatriya and Vijayalakshmi A Lepakshi have equal contributions to this work.

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Correspondence to Divya Kshatriya.

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Kshatriya, D., Lepakshi, V.A. SLA Aware Optimized Task Scheduling Model for Faster Execution of Workloads Among Federated Clouds. Wireless Pers Commun 135, 1635–1661 (2024). https://doi.org/10.1007/s11277-024-11135-x

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