Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm

Abdulhamid, Shafií Muhammad; Latiff, Muhammad Shafie Abd; Abdul-Salaam, Gaddafi; Madni, Syed Hamid Hussain

doi:10.1371/journal.pone.0158102

Cited by 55 publications

(20 citation statements)

References 42 publications

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“…This is commonly referred as SWOT analysis. Abdulhamid et al [5] have applied LCA for task scheduling in order to minimize makespan, response time and economy of use in cloud computing. Authors have gained remarkable results as compared to popular meta-heuristic algorithms like genetic algorithm, ant colony optimization and traditional algorithms like minmin and maxmin.…”

Section: Related Workmentioning

confidence: 99%

“…Global League Championship Algorithm [5] has implemented successfully with effective reduction in makespan. The algorithm is given below:…”

Section: League Championship Algorithm (Lca) and Its Descriptionmentioning

confidence: 99%

“…This algorithm is applicable on sports league following the round robin time table. Applicability of LCA on task scheduling in cloud computing is depicted by Abdulhamid [5] but adaptivity in algorithm can make LCA even better as only minimization of makespan will not solve the purpose. This article provide scheduling algorithm which is adaptive in nature and along with the adaptivity it reduces cloud utilization for deriving it to be economic in nature.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive League Championship Algorithm (ALCA) for Independent Task Scheduling in Cloud Computing

Gade¹,

Mundukur²,

Thakare³

2019

ISI

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Scheduling is a heart of cloud computing as without appropriate scheduling it is impossible to get the desired results. Primary focus of this article is to focus on minimization of makespan, minimum utilization of resources and make the cloud services economic for an independant task. Out of the various task scheduling strategies, in last few years meta-heuristic algorithms have gained recognition in successful operation of task scheduling algorithms. League Championship based Algorithm (LCA) is fascinated from sports leagues through which best team/task in this case can be find out for scheduling. Task scheduling using Adaptive League Championship Algorithm (ALCA) is employed in this article and thereby it shrinks makespan, cloud utilization and cost. ALCA is implemented with cloudsim simulator using java as a programming tool and scheduling has followed the non-premptive approach. Implementation of ALCA results reducation in makespan by 32.95 %, 20.99 % and 7.29 % against customary Ant Colony Optimization (ACO), Genetic Algorithm (GA) and Global League Championship Algorithm (GBLCA) respectively. ALCA also reduces significantly cloud utilization value and improves economy of scale. ALCA may serve as preferred choice for cloud broker as it proved to be multipurpose in the area of makespan, resource utilization and economy.

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Section: Related Workmentioning

confidence: 99%

“…Global League Championship Algorithm [5] has implemented successfully with effective reduction in makespan. The algorithm is given below:…”

Section: League Championship Algorithm (Lca) and Its Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive League Championship Algorithm (ALCA) for Independent Task Scheduling in Cloud Computing

Gade¹,

Mundukur²,

Thakare³

2019

ISI

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“…It is the process of resource allocation from resource providers to the resource users on the basis of pay-per-use. It also allows to assign and re-assign resources from the cloud providers to the cloud users where the cloud user can efficiently use the available resources of IaaS [2,3].…”

Section: Introductionmentioning

confidence: 99%

Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

et al. 2016

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There are two actors in cloud computing environment cloud providers and cloud users. On one hand cloud providers hold enormous computing resources in the cloud large data centers that rent the resources out to the cloud users on a pay-per-use basis to maximize the profit by achieving high resource utilization. On the other hand cloud users who have applications with loads variation and lease the resources from the providers they run their applications within minimum expenses. One of the most critical issues of cloud computing is resource management in infrastructure as a service (IaaS). Resource management related problems include resource allocation, resource adaptation, resource brokering, resource discovery, resource mapping, resource modeling, resource provisioning and resource scheduling. In this review we investigated resource allocation schemes and algorithms used by different researchers and categorized these approaches according to the problems addressed schemes and the parameters used in evaluating different approaches. Based on different studies considered, it is observed that different schemes did not consider some important parameters and enhancement is required to improve the performance of the existing schemes. This review contributes to the existing body of research and will help the researchers to gain more insight into resource allocation techniques for IaaS in cloud computing in the future.

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“…In recent years, some researchers have proposed many effective and feasible scheduling algorithms. The classical scheduling algorithm includes Global League Championship Algorithm (Abdulhamid, Abd Latiff, Abdul-Salaam, et al, 2016), dynamic clustering league championship algorithm (Abdulhamid, Latiff, Madni, et al, 2016), Heterogeneous Earliest Finish Time (HEFT; Topcuoglu, Hariri, & Wu, 2002), CPOP (Topcuoglu et al, 2002), Dynamic Level Scheduling (Sih & Lee, 1993), Duplication Scheduling Heuristic (Badawi & Shatnawi, 2013), Workflow Task Scheduling Based on Fuzzy Clustering (Guo, Yu, Tian, & Yu, 2015), Genetic Algorithm (Bonyadi & Moghaddam, 2009), Simulated Annealing (Dai, Tang, Giret, Salido, & Li, 2013), Predict Earliest Finish Time (PEFT; Arabnejad & Barbosa, 2014), and Constrained Earliest Finish Time (CEFT; Khan, 2012). The quality of service parameter of these algorithms is minimizing makespan.…”

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confidence: 99%

A scheduling algorithm for applications in a cloud computing system with communication changes

Shao

Xie

2018

Expert Systems

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This paper proposes a scheduling algorithm to solve the problem of task scheduling in a cloud computing system with time‐varying communication conditions. This algorithm converts the scheduling problem with communication changes into a directed acyclic graph (DAG) scheduling problem for existing fuzzy communication task nodes, that is, the scheduling problem for a communication‐change DAG (CC‐DAG). The CC‐DAG contains both computation task nodes and communication task nodes. First, this paper proposes a weighted time‐series network bandwidth model to solve the indefinite processing time (cost) problem for a fuzzy communication task node. This model can accurately predict the processing time of a fuzzy communication task node. Second, to address the scheduling order problem for the computation task nodes, a dynamic pre‐scheduling search strategy (DPSS) is proposed. This strategy computes the essential paths for the pre‐scheduling of the computation task nodes based on the actual computation costs (times) of the computation task nodes and the predicted processing costs (times) of the fuzzy communication task nodes during the scheduling process. The computation task node with the longest essential path is scheduled first because its completion time directly influences the completion time of the task graph. Finally, we demonstrate the proposed algorithm via simulation experiments. The experimental results show that the proposed DPSS produced remarkable performance improvement rate on the total execution time that ranges between 11.5% and 21.2%. In view of the experimental results, the proposed algorithm provides better quality scheduling solution that is suitable for scientific application task execution in the cloud computing environment than HEFT, PEFT, and CEFT algorithms.

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Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm

Cited by 55 publications

References 42 publications

Adaptive League Championship Algorithm (ALCA) for Independent Task Scheduling in Cloud Computing

Adaptive League Championship Algorithm (ALCA) for Independent Task Scheduling in Cloud Computing

Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

A scheduling algorithm for applications in a cloud computing system with communication changes

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