A new resource-aware approach to improve schedule workflows in cloud computing environment

Cloud computing has emerged as an efficient environment to execute scientific workflows. In a cloud computing, users can rent Virtual Machines (VMs) to execute their computational tasks. Additionally, users are charged based on a number of resources they rent using pay-per-use cost model. In such ca...

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Main Author: Tawfiq Ahmad Alarawashdeh (Author)
Format: Thesis Book
Language:English
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001 0000099266
005 20210107090000.0
008 200922s2020 my eng
040 |a UniSZA 
050 0 0 |a QA76.5915 
090 0 0 |a QA76.5915   |b .T39 2020 
100 0 |a Tawfiq Ahmad Alarawashdeh   |e author  
245 0 2 |a A new resource-aware approach to improve schedule workflows in cloud computing environment   |c Tawfiq Ahmad Alarawashdeh. 
264 0 |c 2020. 
300 |a xiv,198 leaves:   |b colour illustrations;   |c 31cm. 
336 |a text  |2 rdacontent 
337 |a unmediated  |2 rdamedia 
338 |a volume  |2 rdacarrier 
502 |a Thesis (Doctor of Philosophy) - Universiti Sultan Zainal Abidin,2020 
504 |a Includes bibliographical references (leaves 132-149) 
505 0 |a 1. Introduction -- 2. Literature review -- 3. Research methodology -- 4. Evaluation and discussion -- 5. Conclusions and future works. 
520 |a Cloud computing has emerged as an efficient environment to execute scientific workflows. In a cloud computing, users can rent Virtual Machines (VMs) to execute their computational tasks. Additionally, users are charged based on a number of resources they rent using pay-per-use cost model. In such case, determining the right number of resources to rent is a challenging task. Over-renting increases the execution cost, where, under-renting results in increasing the execution time. To address this problem, this work focuses on maximization the utilization of resources. By improving the utilization of the resource, this study aims to improve the execution time and cost, since the utilization of the resources influences the execution time and cost. This research considers two variations concerning this problem thet can be denoted as single workflow scheduling and multiple workflows scheduling. In single workflow scheduling problem, the input is considered to be single workflow with a set of available resources. Whereby in multiple workflows scheduling problem, the input is assumed to be multiple workflow submitted by several users with a set of available resources. The single workflow scheduling problem is addressed by proposing the Level-Based Clustering (LBC) algorithm. By considering each level of tasks as a single object (cluster), this algorithm aims to establish a relationship between the execution requirement for each cluster, and the number of resources that must be used to execute the entire workflow. To address the multiple workflow scheduling problem, establishing a fair division of the resources between the users (input workflows) is considered as part of the objective function. A modified version of this algorithm termed as LBC-Multiple (LBCM) is presented. In the LBCM algorithm, a number of resources assigned to each workflow depends on the computational requirement for these workflows. This is established by a time-slot mechanism that determines the largest acceptable execution time for each workflow level tasks. The LBC algorithm performance is compared against three well-known algorithms from the literature, and the result shows that the LBC algorithm achieves 50%, 25%, 50% on average improvement in term of cost, makespan and the number of resources used, respectively. In addition, in most situations, the LBCM achieves 20% on average improvement compared to the LBC algorithm. The proposed algorithms take into consideration of the structure of  
610 0 0 |a Universiti Sultan Zainal Abidin --   |x Dissertations  
650 0 |a Ubiquitous computing  
650 0 |a Cloud computing --   |x Management.  
710 2 |a Universiti Sultan Zainal Abidin  
999 |a 1000180267  |b Thesis  |c Reference  |e Tembila Thesis Collection