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A Fuzzy Scheduling Strategy for Intelligent Workflow Decision Making in Uncertain Edge-Cloud Environments [article]

Bing Lin, Chaowei Lin, Xing Chen, Neal N. Xiong, Qiang Shen
2021 arXiv   pre-print
The experimental results show that our strategy can effectively reduce the workflow execution cost in uncertain edge-cloud environments, compared with other benchmark solutions.  ...  In this study, we focus on reducing the execution cost of workflow applications mainly caused by task computation and data transmission, while satisfying the workflow deadline in uncertain edge-cloud environments  ...  Workflow Scheduling in Uncertain Environments Uncertain environments mean that there are fluctuations during workflow scheduling and execution.  ... 
arXiv:2107.01405v3 fatcat:npij5edfo5cnfghskw33r5553e

Online Multi-User Workflow Scheduling Algorithm for Fairness and Energy Optimization

Emile Cadorel, Helene Coullon, Jean-Marc Menaud
2020 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID)  
This article tackles the problem of scheduling multiuser scientific workflows with unpredictable random arrivals and uncertain task execution times in a Cloud environment from the Cloud provider point  ...  Scheduling workflows in a private Cloud environment is a difficult optimization problem as capacity constraints must be fulfilled additionally to dependencies constraints between tasks of the workflows  ...  arrivals of workflows, and uncertain task execution times; (2) user fairness, in other word, be able to schedule a multi-user workload with a fair sharing of the available resources; (3) energy minimization  ... 
doi:10.1109/ccgrid49817.2020.00-36 dblp:conf/ccgrid/CadorelCM20 fatcat:nrcgtk3z6zdwxojbzbpknnouoy

Multiple Workflows Scheduling in Multi-tenant Distributed Systems: A Taxonomy and Future Directions [article]

Muhammad H. Hilman, Maria A. Rodriguez, Rajkumar Buyya
2019 arXiv   pre-print
We open up the problems and challenges to shove up the research on multiple workflows scheduling in multi-tenant distributed systems.  ...  To cater to the broader needs, multi-tenant platforms for executing workflows were began to be built.  ...  entry task (i.e., t-level/top-level) and exit task (i.e., b-level/bo om-level) to assign the priorities between tasks.  ... 
arXiv:1809.05574v2 fatcat:qnjb3ubmrbayhol2u3ujccflom

Resource-sharing Policy in Multi-tenant Scientific Workflow-as-a-Service Cloud Platform [article]

Muhammad H. Hilman, Maria A. Rodriguez, Rajkumar Buyya
2020 arXiv   pre-print
Increased adoption of scientific workflows in the community has urged for the development of multi-tenant platforms that provide these workflow executions as a service.  ...  A traditional WMS is usually designed to execute a single workflow in a dedicated process while WaaS cloud platforms enhance the process by exploiting multiple workflows execution in a multi-tenant environment  ...  The entry task(s) in the first level of a workflow are scheduled first, followed by their successors in the next level until it reaches the exit task(s).  ... 
arXiv:1903.01113v3 fatcat:3ugx3lhdmncz3bf7tmrxny7zce

Utility functions for adaptively executing concurrent workflows

Kevin Lee, Norman W. Paton, Rizos Sakellariou, Alvaro A. A. Fernandes
2010 Concurrency and Computation  
By contrast, in workflow scheduling, Yu et al. [13] , use a utility measure to give a value to assignments of tasks to resources, in an adaptive scheduling system where the overall problem is divided into  ...  Experiment 1: Montage workflow progress plots, showing when each job (task) is queued and executed, with an adaptive workflow execution strategy using the utility based on the response time.  ...  Adaptive workflow execution promises to provide more robust performance in uncertain environments.  ... 
doi:10.1002/cpe.1673 fatcat:pioheom4s5anfmdzyjai3h2v2q

A Robust Algorithm for Deadline Constrained Scheduling in IaaS Cloud Environment

Bilkisu Larai MUHAMMAD-BELLO, Masayoshi ARITSUGI
2018 IEICE transactions on information and systems  
Experimental evaluations using CloudSim with synthetic workflows of various sizes show that our proposal is robust to fluctuations in estimates of task runtimes and is able to produce high quality schedules  ...  Our proposal is a static scheduling algorithm aimed at addressing the uncertainties related to: the estimation of task execution times; and, the delay in provisioning computational Cloud resources.  ...  Dynamic scheduling algorithms on the other hand produce schedules with lower quality due to the limited, task-level view of the entire workflow, but adapt well to Cloud specificities since they are able  ... 
doi:10.1587/transinf.2018pap0016 fatcat:wjmgoshe5bc5hkeize4buerdpy

Trust-based robust scheduling and runtime adaptation of scientific workflow

Mingzhong Wang, Kotagiri Ramamohanarao, Jinjun Chen
2009 Concurrency and Computation  
To deal with exceptions during the execution of a schedule, we adapt and evolve the schedule at runtime by interleaving the processes of evaluating, scheduling, executing and monitoring in the life cycle  ...  Robustness and reliability with respect to the successful completion of a schedule are crucial requirements for scheduling in scientific workflow management systems because service providers are becoming  ...  Figure 5 . 5 System success probability with variant constraint levels Figure 6 . 6 Comparison of estimation by plan evaluation and simulated outcome by plan scheduling ROBUST SCHEDULING AND EXECUTION  ... 
doi:10.1002/cpe.1456 fatcat:w7n7icz4s5a3zmqwt5livd52g4

Resource scheduling of workflow multi-instance migration based on the shuffled leapfrog algorithm

Yang Mingshun, Gao Xinqin, Cao Yuan, Liu Yong, Li Yan
2015 Journal of Industrial Engineering and Management  
While task sequencing refers to priority ordering of the multi tasks allocated to a same resource.  ...  Also, only resource scheduling of multi instance migration in a single workflow model is considered, resource scheduling optimization of multi instance migration in multi workflow models should be further  ... 
doi:10.3926/jiem.1363 fatcat:w66xhxp5ujeg7kysh6qg3jp2yi

Topology-based Workflow Scheduling in Commercial Clouds

2015 KSII Transactions on Internet and Information Systems  
This is also significantly important for the case of providing services to workflow tasks. In this paper, we address the issues of workflow scheduling in commercial clouds.  ...  Workflow scheduling has always been treated as one of the most challenging problems in clouds.  ...  Many other conditions should be considered to meet the needs of practical clouds, for instance uncertain task execution time [28] , task emerging, multi-objectives [29] , fuzzy topologic information  ... 
doi:10.3837/tiis.2015.11.003 fatcat:iyfs7qk3cbd3dpbntzwgy2dhru

Bi-level fuzzy based advanced reservation of Cloud workflow applications on distributed Grid resources

Sahar Adabi, Ali Movaghar, Amir Masoud Rahmani
2013 Journal of Supercomputing  
The Multi-Criteria Advance Reservation (MCAR) algorithm is introduced for this unit to schedule the tasks of each created sub-workflow.  ...  of related tasks with different computational and communication demands on multi-cluster Grid computing environments.  ...  To obtain this objective, we introduced a bi-level scheduling strategy that consists of Global-level scheduling and Local-level scheduling.  ... 
doi:10.1007/s11227-013-0994-8 fatcat:otkogd3nbfbvnlxnzcwfqrdcwu

Efficiency aware scheduling techniques in cloud computing: a descriptive literature review

Muhammad Usman Sana, Zhanli Li
2021 PeerJ Computer Science  
Resource scheduling plays a fundamental role in the well-organized allocation of resources to every task in the cloud environment.  ...  An efficient Scheduling algorithm must enhance the implementation of goals like scheduling cost, load balancing, makespan time, security awareness, energy consumption, reliability, service level agreement  ...  For workflow scheduling, an adaptive, just-in-time scheduling algorithm is proposed by Poola, Ramamohanarao & Buyya (2016) .  ... 
doi:10.7717/peerj-cs.509 pmid:34013035 pmcid:PMC8114819 fatcat:yyyc7wmpmrabreu6ji7bqhs5by

Reinforcement Learning-based Application Autoscaling in the Cloud: A Survey [article]

Yisel Garí, David A. Monge, Elina Pacini, Cristian Mateos, Carlos García Garino
2020 arXiv   pre-print
Therefore, RL appears as a promising approach for Autoscaling in Cloud since it is possible to learn transparent (with no human intervention), dynamic (no static plans), and adaptable (constantly updated  ...  Reinforcement Learning (RL) has demonstrated a great potential for automatically solving decision-making problems in complex uncertain environments.  ...  On the other hand, both independent tasks and workflows applications are more associated with the scheduling problem, assuming a fixed infrastructure.  ... 
arXiv:2001.09957v3 fatcat:gtylvmt4wraqvhfxjfao4zdr3y

A Scalable Pipeline for Transcriptome Profiling Tasks with On-Demand Computing Clouds

Shayan Shams, Nayong Kim, Xiandong Meng, Ming Tai Ha, Shantenu Jha, Zhong Wang, Joohyun Kim
2016 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)  
With an example of Amazon EC2, by harnessing distributed and parallel computing implementations, our pipeline is able to allocate optimally computing resources to tasks of a target workflow in an efficient  ...  of dynamically adaptive executions.  ...  ACKNOWLEDGMENT We are thankful for Amazon EC2 computing time with the AWS research grant program. We thank Colin Dewey and his group member for helping us for the use of DETONATE.  ... 
doi:10.1109/ipdpsw.2016.129 dblp:conf/ipps/ShamsKMHJWK16 fatcat:dh6z5bslu5btpcvk6knddcfklu

Deep Reinforcement Learning-based Methods for Resource Scheduling in Cloud Computing: A Review and Future Directions [article]

Guangyao Zhou, Wenhong Tian, Rajkumar Buyya
2021 arXiv   pre-print
With the acceleration of the Internet in Web 2.0, Cloud computing as a paradigm to provide dynamic, uncertain and elastic services has shown superiorities to meet the computing needs dynamically.  ...  This paper surveys the methods of resource scheduling with focus on DRL-based scheduling approaches in Cloud computing, also reviews the application of DRL as well as discusses challenges and future directions  ...  delay tasks or delay workflows.  ... 
arXiv:2105.04086v1 fatcat:rdfwf2ltffcyxhmohf6kwtqaai

Current trends in cloud computing

Siraj Munir, Computer Science Department, Muhammad Ali Jinnah University
2020 Indian Journal of Science and Technology  
Findings: Our findings show that researchers are working in the area of Job Scheduling while low attention has been given in Resource Scheduling.  ...  Method: The reviewed works are filtered after the rigorous process by using renowned indexing database of ACM and IEEE along with the subject based journals on Cloud Computing of international repute.  ...  Researchers in (47) proposed multi-step workflow model for cloud based instance-intensive environment, due to multi stepping workflow scheduling that was incorporated and proposed favourable results  ... 
doi:10.17485/ijst/v13i24.358 fatcat:mzlwkmkjw5c3lahyvvvdiaqy6i
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