Earthquake Disaster based Efficient Resource Utilization Technique in IaaS Cloud

TL;DR

This paper introduces a dynamic resource scheduling framework for cloud computing during earthquake disasters, optimizing resource allocation based on urgency to improve response efficiency and reduce costs.

Contribution

It proposes the Earthquake Disaster Based Resource Scheduling (EDBRS) framework and a novel scheduling algorithm tailored for emergency response in cloud environments.

Findings

The proposed algorithm outperforms existing scheduling algorithms.

It reduces execution cost for cloud workloads.

It decreases response time during earthquake emergencies.

Abstract

Cloud Computing is an emerging area. The main aim of the initial search-and-rescue period after strong earthquakes is to reduce the whole number of mortalities. One main trouble rising in this period is to and the greatest assignment of available resources to functioning zones. For this issue a dynamic optimization model is presented. The model uses thorough descriptions of the operational zones and of the available resources to determine the resource performance and efficiency for different workloads related to the response. A suitable solution method for the model is offered as well. In this paper, Earthquake Disaster Based Resource Scheduling (EDBRS) Framework has been proposed. The allocation of resources to cloud workloads based on urgency (emergency during Earthquake Disaster). Based on this criterion, the resource scheduling algorithm has been proposed. The performance of the proposed algorithm has been assessed with the existing common scheduling algorithms through the CloudSim. The experimental results show that the proposed algorithm outperforms the existing algorithms by reducing execution cost and time of cloud consumer workloads submitted to the cloud.