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      Earthquake Disaster based Efficient Resource Utilization Technique in IaaS Cloud

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          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.

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          Cloud Computing and Grid Computing 360-Degree Compared

          Cloud Computing has become another buzzword after Web 2.0. However, there are dozens of different definitions for Cloud Computing and there seems to be no consensus on what a Cloud is. On the other hand, Cloud Computing is not a completely new concept; it has intricate connection to the relatively new but thirteen-year established Grid Computing paradigm, and other relevant technologies such as utility computing, cluster computing, and distributed systems in general. This paper strives to compare and contrast Cloud Computing with Grid Computing from various angles and give insights into the essential characteristics of both.
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            A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments

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              Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities

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                Author and article information

                Journal
                27 June 2013
                2014-01-27
                Article
                1306.6597
                266edf85-e45c-4515-83e4-ba49a4482429

                http://creativecommons.org/licenses/publicdomain/

                History
                Custom metadata
                97P70
                IJARCET - 6831
                International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 2, Issue 6, 2013, 1933-1938
                6 Pages including 4 figures, Published by IJARCET
                cs.DC

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