Article
Computer Science, Interdisciplinary Applications
Marwa Mokni, Sonia Yassa, Jalel Eddine Hajlaoui, Mohamed Nazih Omri, Rachid Chelouah
Summary: This article proposes a new approach for efficient scheduling of workflows in Fog-Cloud computing environments, combining partitioning, sequencing, and scheduling algorithms for multi-objective optimization. Experimental results demonstrate the superiority of this approach in reducing makespan compared to other related approaches, while considering resource utilization.
SIMULATION MODELLING PRACTICE AND THEORY
(2023)
Article
Computer Science, Information Systems
Shuo Qin, Dechang Pi, Zhongshi Shao, Yue Xu
Summary: This article investigates the problem of cloud workflow scheduling with the aim of minimizing the total cost of workflow execution under a predetermined deadline. A novel knowledge-based adaptive discrete water wave optimization (KADWWO) algorithm is proposed, which incorporates problem-specific knowledge to adaptively explore the search space and accelerate convergence. Extensive simulation experiments demonstrate that the KADWWO approach outperforms several recent state-of-the-art algorithms.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Information Systems
Wakar Ahmad, Bashir Alam, Sanchit Ahuja, Sahil Malik
Summary: This paper proposes a Dynamic Cost-Efficient Deadline-Aware (DCEDA) heuristic algorithm for scheduling Big Data workflow, which produces the cheapest schedule while achieving the deadline constraints. Experimental analysis shows that DCEDA delivers better performance compared to existing algorithms.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Theory & Methods
Huifang Li, Danjing Wang, Mengchu Zhou, Yushun Fan, Yuanqing Xia
Summary: This paper proposes a Multi-swarm Co-evolution-based Hybrid Intelligent Optimization (MCHO) algorithm for multiple-workflow scheduling. The algorithm uses a multi-swarm co-evolutionary mechanism, incorporates local and global guiding information, and applies genetic algorithm and simulated annealing strategies to improve the scheduling performance.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Marwa Mokni, Sonia Yassa, Jalel Eddine Hajlaoui, Rachid Chelouah, Mohamed Nazih Omri
Summary: The article proposes a hybrid Cloud-Fog multi-agent approach to schedule dependent IoT tasks, modeling them as a multi-objective optimization problem to balance response time, cost, and makespan. Experimental results confirm the method's advantages in terms of cost, makespan, and response time compared to Fog and Cloud computing.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Computer Science, Information Systems
Mohammed Redha Bouzidi, Mourad Daoudi, Benameur Ziani, Kamel Boukhalfa, Chaker Abdelaziz Kerrache, Nasreddine Lagraa
Summary: Workflow scheduling is a challenging issue in cloud computing, with a focus on solving NP-hard problems and improving efficiency. Researchers have proposed the FAMOBACH method based on MOHEFT, which improves running speed by using checkpointing and backtracking methods.
COMPUTER COMMUNICATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Mustafa Ibrahim Khaleel
Summary: This paper proposes a method for modeling scientific workflow scheduling as a multi-objective optimization problem to balance energy consumption and scheduling reliability. By placing tasks with low computational requirements on fog resources and using a reliability-aware stepwise performance-to-power ratio procedure to reduce energy consumption. Simulation results show that this method has higher reliability under minimized energy constraints.
SIMULATION MODELLING PRACTICE AND THEORY
(2022)
Article
Computer Science, Information Systems
Meng Xu, Yi Mei, Shiqiang Zhu, Beibei Zhang, Tian Xiang, Fangfang Zhang, Mengjie Zhang
Summary: Dynamic Workflow Scheduling in Fog Computing is a significant optimization problem that involves the coordination of cloud servers, mobile devices, and edge servers. This article proposes a new problem model and simulator, as well as a Multi-Tree Genetic Programming method to address the problem. Experimental results demonstrate that the proposed method achieves significantly better performance across all tested scenarios.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Chemistry, Analytical
Mohamed Ali Rakrouki, Nawaf Alharbe
Summary: This paper proposes a new scheduling strategy that combines PSO and GSA algorithms to reduce resource consumption and improve SLA compliance based on QoS status analysis.
Article
Computer Science, Hardware & Architecture
Jakub Beranek, Stanislav Bohm, Vojtech Cima
Summary: Task graphs provide a simple way to describe scientific workflows that can be executed on HPC clusters and in the cloud, with scheduling algorithms being an important aspect. However, previous works have often overlooked the quantification of the impact of scheduling challenges, leading to potentially significant discrepancies in results when compared to more realistic models. Properly describing implementation details of scheduling algorithms is crucial for enabling accurate evaluation and maximizing scheduler performance.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Mani Alaei, Reihaneh Khorsand, Mohammadreza Ramezanpour
Summary: The research aims to develop an adaptive fault detection strategy based on the Improved Differential Evolution algorithm in cloud computing to minimize energy consumption, makespan, total cost, and tolerate faults while scheduling scientific workflows. The proposed method utilizes an adaptive network-based fuzzy inference system prediction model to proactively control resource load fluctuation and applies a reactive fault tolerance technique for processor failures. Experimental results showed significant improvements in scheduling performance, fault tolerance, makespan, energy consumption, task fault ratio, and total cost compared to existing techniques.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Hardware & Architecture
Ke Luo, Tao Ouyang, Zhi Zhou, Xu Chen
Summary: Serverless computing is popular in edge computing due to its flexible features. However, there is limited research on optimizing Serverless workflow scheduling in resource-constrained edge systems. This work proposes a behavior tree-based modeling approach and a tailored system called BeeFlow for edge clusters, achieving significant speedup and robustness compared to the state-of-the-art.
JOURNAL OF SYSTEMS ARCHITECTURE
(2023)
Article
Automation & Control Systems
Quanwang Wu, MengChu Zhou, Junhao Wen
Summary: Cloud platforms have become a popular execution environment for workflow applications, leading to high demand for effective scheduling strategies. This article proposes a new scheduling model, ELSH, which considers endpoint communication contention to minimize workflow makespan. Experimental results show that ELSH outperforms traditional algorithms in practice.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Emmanuel Bugingo, Defu Zhang, Zhaobin Chen, Wei Zheng
Summary: A workflow is a group of tasks processed in order to complete an application, often used for modeling complex big-data applications. Optimizing conflicting objectives in executing complex applications in a distributed system is a common challenge, with most scheduling approaches focusing on single or bi-objective optimization. This paper proposes a multi-objective workflow-scheduling algorithm based on decomposition, capable of finding optimal solutions with a single run.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Hardware & Architecture
Zhao-hong Jia, Lei Pan, Xiao Liu, Xue-jun Li
Summary: This paper presents a workflow scheduling algorithm based on stable matching game theory to minimize workflow completion time and ensure fairness among tasks. By using local optimization methods and a novel evaluation metric, the algorithm's performance is improved and outperforms other algorithms in comprehensive experiments.
JOURNAL OF SUPERCOMPUTING
(2021)
Article
Biochemical Research Methods
Bahareh Behkamal, Mahmoud Naghibzadeh, Andrea Pagnani, Mohammad Reza Saberi, Kamal Al Nasr
Summary: Cryo-electron microscopy (cryo-EM) is an important biophysical method for macromolecular structure determination. This paper proposes an automatic framework to solve the alpha-helix correspondence problem in three-dimensional space, achieving highly efficient, robust, and fast results.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2021)
Article
Multidisciplinary Sciences
Hossein Savari, Hassan Shafiey, Abdorreza Savadi, Nayyereh Saadati, Mahmoud Naghibzadeh
Summary: The article presents data related to the comparison of tandem repeats in different viral families using a newly developed efficient software. It demonstrates a lower frequency of trimer tandem repeats in RNA viruses compared to DNA viruses and focuses on zoonotic viruses from the Coronaviridae family that have caused human crises in the last two decades.
Article
Biology
Mahdie Eghdami, Mahmoud Naghibzadeh
Summary: Protein structure prediction, focusing on beta-sheet structure, is crucial in research, with computational prediction being a more convenient alternative compared to experimental methods.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2021)
Article
Computer Science, Hardware & Architecture
Bagher Salami, Hamid Noori, Mahmoud Naghibzadeh
Summary: This paper proposes a scheduling framework for heterogeneous multi-core processors that considers energy efficiency, shared resource contention, and fairness. The experimental results show that the proposed framework outperforms Linux and four other schedulers in terms of fairness and energy efficiency.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Biochemistry & Molecular Biology
Bahareh Behkamal, Mahmoud Naghibzadeh, Mohammad Reza Saberi, Zeinab Amiri Tehranizadeh, Andrea Pagnani, Kamal Al Nasr
Summary: Cryo-electron microscopy (cryo-EM) is a significant technique for protein structure determination, but limited by its resolution. This study proposes a novel automatic computational method to identify secondary structure elements (SSEs) in a protein's 3D structure, demonstrating efficiency and robustness in experimental evaluation.
Article
Biochemical Research Methods
Bahareh Behkamal, Mahmoud Naghibzadeh, Andrea Pagnani, Mohammad Reza Saberi, Kamal Al Nasr
Summary: This article proposes a linear programming-based topology determination method to solve the secondary structure topology problem in three-dimensional geometrical space. It transforms the secondary structure matching problem into a complete weighted bipartite graph matching problem and uses linear programming algorithm to extract the true topology.
Article
Computer Science, Hardware & Architecture
Malihe Hariri, Mostafa Nouri-Baygi, Saeid Abrishami
Summary: Scientific workflows require powerful computing resources to process large amounts of data and perform complex analyses efficiently and cost-effectively. This research presents a hybrid algorithm based on a mathematical model, which reduces task execution costs under deadline constraints.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Computer Science, Hardware & Architecture
Arash Deldari, Abolghasem Yousofi, Mahmoud Naghibzadeh, Alireza Salehan
Summary: This paper presents a scheduling algorithm for scientific workflows that focuses on utilizing multicore resources to reduce execution costs while meeting the user-defined deadline.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Computer Science, Information Systems
Ghazaleh Khojasteh Toussi, Mahmoud Naghibzadeh, Saeid Abrishami, Hoda Taheri, Hamid Abrishami
Summary: This paper proposes a new algorithm, EDQWS, for workflow scheduling in cloud computing. The algorithm adopts a divide and conquer approach to divide the workflow into sub-workflows and introduces a new merging algorithm to reduce the number of instances and minimize the execution cost. Experiments show that EDQWS outperforms other competitors in terms of cost minimization and meeting deadlines.
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS
(2022)
Article
Computer Science, Theory & Methods
Behrooz Zolfaghari, Saeid Abrishami
Summary: This paper proposes a new algorithm for scheduling workflow ensembles in cloud computing, taking advantage of Amazon spot instances. The algorithm classifies workflow tasks and spot instances based on deadlines, priorities, and bid prices, effectively improving the number of completed workflows.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Information Systems
Faeze Ramezani, Saeid Abrishami, Mehdi Feizi
Summary: A federated cloud is an inter-cloud environment in which cloud service providers cooperate for better scalability and service provisioning through communication and resource sharing. This paper introduces a generic resource management framework for inter-federation resource management and proposes a market-based framework to manage the various types of federated clouds. The proposed framework is able to cover a variety of centralized cloud federation models. A resource management model compatible with the framework is implemented and evaluated using the FederatedCloudSim 2.0 toolkit.
JOURNAL OF GRID COMPUTING
(2023)
Article
Computer Science, Software Engineering
Jalal Sakhdari, Behrooz Zolfaghari, Shaghayegh Izadpanah, Samaneh Mahdizadeh Zargar, Mahla Rahati Quchani, Mahsa Shadi, Saeid Abrishami, Abbas Rasoolzadegan
Summary: Edge computing is a new computing paradigm that addresses communication delays in real-time applications by utilizing resources at the network edge. It has gained significant attention from the research community, resulting in a surge in publications. To gain insights into this field, a systematic mapping study (SMS) was conducted, employing a three-tier search method and defined quality criteria. The SMS identified 112 search spaces and 1440 studies, addressing 8 research questions to understand the key topics, architectures, techniques, and other aspects of edge computing.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Information Systems
Hoda Taheri, Saeid Abrishami, Mahmoud Naghibzadeh
Summary: This study introduces a cloud broker for executing Deadline-constrained Periodic scientific Workflows (BDPW), which uses both reserved and on-demand resources to minimize cost. The broker utilizes container technology to decrease VM provisioning delay and adopts a hybrid scheduling method for static planning and dynamic scheduling, adapting to uncertainties.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Bagher Salami, Hamid Noori, Mahmoud Naghibzadeh
Summary: This study investigates the fairness problem and energy efficiency in heterogeneous multi-core processors, proposing a heterogeneous fairness-aware energy efficient framework (HFEE) that employs DVFS to meet fairness constraints and provide energy efficient scheduling. Experimental results indicate that the introduced technique significantly improves energy efficiency and fairness compared to traditional schedulers and other energy efficient schedulers.
IEEE TRANSACTIONS ON COMPUTERS
(2021)
