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Relevant bibliographies by topics / Heterogeneous Earliest Finish Time (HEFT) algorithm

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Academic literature on the topic 'Heterogeneous Earliest Finish Time (HEFT) algorithm'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Heterogeneous Earliest Finish Time (HEFT) algorithm"

1

Nasser, Thaar Habeb, Ekhlas Kadhum Hamza, and Ahmed Mudheher Hasan. "MOCAB/HEFT algorithm of multi radio wireless communication improved achievement assessment." Bulletin of Electrical Engineering and Informatics 12, no. 1 (2023): 224–31. http://dx.doi.org/10.11591/eei.v12i1.4078.

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Network-wide conveying is vital in remote associations, and the great part of these broadcasts are built on single-channel single-radio (SC-SR) network frameworks. The problem of the current work is divided into two parts. The first part shows that increasing broadcast and redundancy lead to an increase in time consumption. The second problem is solving complexity problems when tasks are scheduled in a heterogeneous manner in a computing system, where the processors in the network may not be identical and take different time periods to carry out the same task. The goals of this work are to red

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Chaudhuri, Pranay, and Jeffrey Elcock. "Process Scheduling in Heterogeneous Multiprocessor Systems Using Task Duplication." International Journal of Business Data Communications and Networking 6, no. 1 (2010): 58–69. http://dx.doi.org/10.4018/jbdcn.2010010104.

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Scheduling tasks in heterogeneous parallel and distributed computing environments continues to be a challenging problem. In this paper, the authors investigate the Heterogeneous Earliest Finish Time (HEFT) algorithm, along with alternative scheduling policies for task prioritising phases and the Critical Path on a Processor (CPOP) for scheduling tasks on a heterogeneous multiprocessor system. The authors show that by combining the HEFT algorithm selection policy with the task duplication strategy, it is possible to further reduce the schedule length produced by both HEFT and CPOP. The process

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Li, Yuzhong, Wenming Tang, and Guixiong Liu. "HPEFT for Hierarchical Heterogeneous Multi-DAG in a Multigroup Scan UPA System." Electronics 8, no. 5 (2019): 498. http://dx.doi.org/10.3390/electronics8050498.

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Multidirected acyclic graph (DAG) workflow scheduling is a key problem in the heterogeneous distributed environment in the distributed computing field. A hierarchical heterogeneous multi-DAG workflow problem (HHMDP) was proposed based on the different signal processing workflows produced by different grouping and scanning modes and their hierarchical processing in specific functional signal processing modules in a multigroup scan ultrasonic phased array (UPA) system. A heterogeneous predecessor earliest finish time (HPEFT) algorithm with predecessor pointer adjustment was proposed based on the

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Hilda, Jabanjalin, and Srimathi Chandrasekaran. "Cost and Time Economical Planning Algorithm for Scientific Workflows in Cloud Computing." Future Internet 13, no. 10 (2021): 263. http://dx.doi.org/10.3390/fi13100263.

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A heterogeneous system can be portrayed as a variety of unlike resources that can be locally or geologically spread, which is exploited to implement data-intensive and computationally intensive applications. The competence of implementing the scientific workflow applications on heterogeneous systems is determined by the approaches utilized to allocate the tasks to the proper resources. Cost and time necessity are evolving as different vital concerns of cloud computing environments such as data centers. In the area of scientific workflows, the difficulties of increased cost and time are highly

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Hilda, Jabanjalin, and Srimathi Chandrasekaran. "Cost and Time Economical Planning Algorithm for Scientific Workflows in Cloud Computing." Future Internet 13, no. 10 (2021): 263. http://dx.doi.org/10.3390/fi13100263.

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A heterogeneous system can be portrayed as a variety of unlike resources that can be locally or geologically spread, which is exploited to implement data-intensive and computationally intensive applications. The competence of implementing the scientific workflow applications on heterogeneous systems is determined by the approaches utilized to allocate the tasks to the proper resources. Cost and time necessity are evolving as different vital concerns of cloud computing environments such as data centers. In the area of scientific workflows, the difficulties of increased cost and time are highly

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Gupta, Sachi, Sailesh Iyer, Gaurav Agarwal, et al. "Efficient Prioritization and Processor Selection Schemes for HEFT Algorithm: A Makespan Optimizer for Task Scheduling in Cloud Environment." Electronics 11, no. 16 (2022): 2557. http://dx.doi.org/10.3390/electronics11162557.

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Cloud computing is one of the most commonly used infrastructures for carrying out activities using virtual machines known as processing units. One of the most fundamental issues with cloud computing is task scheduling. The optimal determination of scheduling criteria in cloud computing is a non-deterministic polynomial-time (NP)-complete optimization problem, and several procedures to manage this problem have been suggested by researchers in the past. Among these methods, the Heterogeneous Earliest Finish Time (HEFT) algorithm is recognized to produce optimal outcomes in a shorter time period

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D. Hanabaratti, Kavita, and Rudragoud Patil. "Efficient algorithm for replanning web service composition." Indonesian Journal of Electrical Engineering and Computer Science 31, no. 1 (2023): 491. http://dx.doi.org/10.11591/ijeecs.v31.i1.pp491-500.

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Web-service-composition (WSC) workload execution inside a hybrid cloud environment is challenging. A dynamic approach for allocating resources to various tasks, as well as associated sub-tasks having a satisfactory quality-ofservice (QoS) requirement, is necessary for the present real-time demand. As a result of focusing primarily on decreasing processing time as well as cost, current approaches improve latency as well as energy while executing a given workload. This study introduces an efficient re-planning (ERP) algorithm for running many scientific workloads inside a heterogeneous cloud env

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Kavita, D. Hanabaratti, and Patil Rudragoud. "Efficient algorithm for replanning web service composition." Efficient algorithm for replanning web service composition 31, no. 1 (2023): 491–500. https://doi.org/10.11591/ijeecs.v31.i1.pp491-500.

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Abstract:

Web-service-composition (WSC) workload execution inside a hybrid cloud environment is challenging. A dynamic approach for allocating resources to various tasks, as well as associated sub-tasks having a satisfactory quality-ofservice (QoS) requirement, is necessary for the present real-time demand. As a result of focusing primarily on decreasing processing time as well as cost, current approaches improve latency as well as energy while executing a given workload. This study introduces an efficient re-planning (ERP) algorithm for running many scientific workloads inside a heterogeneous cloud env

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Aziz, Maslina Abdul, and Izuan Hafez Ninggal. "Scalable workflow scheduling algorithm for minimizing makespan and failure probability." Bulletin of Electrical Engineering and Informatics 8, no. 1 (2019): 283–90. http://dx.doi.org/10.11591/eei.v8i1.1436.

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This paper presents an algorithm called Failure-Aware Workflow Scheduling (FAWS). The proposed algorithm discussed in this paper schedules parallel applications on homogeneous systems without sacrificing the two conflicting objectives: reliability and makespan. The proposed algorithm handles unexpected failure causes rescheduling of the failed task to available resources. In order to analyse the performance of the FAWS algorithm, it will be compared with the popular scheduling algorithm namely Heterogeneous Earliest Finish Time (or HEFT) and Critical Path (CP). A simulation-driven analysis bas

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Maslina, Abdul Aziz, and Hafez Ninggal Izuan. "Scalable workflow scheduling algorithm for minimizing makespan and failure probability." Bulletin of Electrical Engineering and Informatics 8, no. 1 (2019): 283–90. https://doi.org/10.11591/eei.v8i1.1436.

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Abstract:

This paper presents an algorithm called Failure-Aware Workflow Scheduling (FAWS). The proposed algorithm discussed in this paper schedules parallel applications on homogeneous systems without sacrificing the two conflicting objectives: reliability and makespan. The proposed algorithm handles unexpected failure causes rescheduling of the failed task to available resources. In order to analyse the performance of the FAWS algorithm, it will be compared with the popular scheduling algorithm namely Heterogeneous Earliest Finish Time (or HEFT) and Critical Path (CP). A simulation-driven analysis bas

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Book chapters on the topic "Heterogeneous Earliest Finish Time (HEFT) algorithm"

1

Alam, Mahfooz, Mohammad Shahid, and Suhel Mustajab. "Security Prioritized Heterogeneous Earliest Finish Time Workflow Allocation Algorithm for Cloud Computing." In Lecture Notes on Data Engineering and Communications Technologies. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9416-5_17.

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Zhao, Henan, and Rizos Sakellariou. "An Experimental Investigation into the Rank Function of the Heterogeneous Earliest Finish Time Scheduling Algorithm." In Euro-Par 2003 Parallel Processing. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45209-6_28.

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Elcock, Jeffrey, and Pranay Chaudhuri. "Process Scheduling Using Task Duplication in Heterogeneous Distributed Systems." In Next Generation Data Communication Technologies. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-61350-477-2.ch014.

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Task scheduling in heterogeneous parallel and distributed computing environments continues to be one of the most challenging problems. In this chapter, the authors investigate the Heterogeneous Earliest Finish Time (HEFT) algorithm, along with its alternative scheduling policies for the task prioritising phases, and the Critical Path on a Processor (CPOP) for scheduling tasks on a heterogeneous multiprocessor system. It is shown that, by combining the HEFT algorithm selection policy with the task duplication strategy, it is possible to further reduce the schedule length produced by both HEFT a

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Conference papers on the topic "Heterogeneous Earliest Finish Time (HEFT) algorithm"

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Samadi, Yassir, Mostapha Zbakh, and Claude Tadonki. "E-HEFT: Enhancement Heterogeneous Earliest Finish Time algorithm for Task Scheduling based on Load Balancing in Cloud Computing." In 2018 International Conference on High Performance Computing & Simulation (HPCS). IEEE, 2018. http://dx.doi.org/10.1109/hpcs.2018.00100.

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Mazrekaj, Artan, Arlinda Sheholli, Dorian Minarolli, and Bernd Freisleben. "The Experiential Heterogeneous Earliest Finish Time Algorithm for Task Scheduling in Clouds." In 9th International Conference on Cloud Computing and Services Science. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007722203710379.

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Bittencourt, Luiz F., Rizos Sakellariou, and Edmundo R. M. Madeira. "DAG Scheduling Using a Lookahead Variant of the Heterogeneous Earliest Finish Time Algorithm." In 2010 18th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). IEEE, 2010. http://dx.doi.org/10.1109/pdp.2010.56.

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Kang, Hui, Huiping Fei, and Fang Mei. "Research and implementation of the heterogeneous earliest finish time algorithm based on Pi-Calculus." In 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016). Atlantis Press, 2016. http://dx.doi.org/10.2991/amitp-16.2016.70.

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