@article{MTMT:34695021,
	title = {Structure-Aware Scheduling Algorithm for Deadline-Constrained Scientific Workflows in the Cloud},
	url = {https://m2.mtmt.hu/api/publication/34695021},
	author = {Al-Haboobi, Ali and Kecskeméti, Gábor},
	doi = {10.14569/IJACSA.2024.0150280},
	journal-iso = {IJACSA},
	journal = {INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS},
	volume = {15},
	unique-id = {34695021},
	issn = {2158-107X},
	abstract = {Cloud computing provides pay-per-use IT services through the Internet. Although cloud computing resources can help scientific workflow applications, several algorithms face the problem of meeting the user’s deadline while minimising the cost of workflow execution. In the cloud, selecting the appropriate type and the exact number of VMs is a major challenge for scheduling algorithms, as tasks in workflow applications are distributed very differently. Depending on workflow requirements, algorithms need to decide when to provision or de-provision VMs. Therefore, this paper presents an algorithm for effectively selecting and allocating resources. Based on the workflow structure, it decides the type and number of VMs to use and when to lease and release them. For some structures, our proposed algorithm uses the initial rented VMs to schedule all tasks of the same workflow to minimise data transfer costs. We evaluate the performance of our algorithm by simulating it with synthetic workflows derived from real scientific workflows with different structures. Our algorithm is compared with Dyna and CGA approaches in terms of meeting deadlines and execution costs. The experimental results show that the proposed algorithm met all the deadline factors of each workflow, while the CGA and Dyna algorithms met 25% and 50%, respectively, of all the deadline factors of all workflows. The results also show that the proposed algorithm provides more cost-efficient schedules than CGA and Dyna.},
	year = {2024},
	eissn = {2156-5570},
	pages = {792-802},
	orcid-numbers = {Kecskeméti, Gábor/0000-0001-5716-8857}
}

@article{MTMT:33585957,
	title = {Simulating IoT Workflows in DISSECT-CF-Fog},
	url = {https://m2.mtmt.hu/api/publication/33585957},
	author = {Márkus, András and Al-Haboobi, Ali and Kecskeméti, Gábor and Kertész, Attila},
	doi = {10.3390/s23031294},
	journal-iso = {SENSORS-BASEL},
	journal = {SENSORS},
	volume = {23},
	unique-id = {33585957},
	abstract = {The modelling of IoT applications utilising the resources of cloud and fog computing is not straightforward because they have to support various trigger-based events that make human life easier. The sequence of tasks, such as performing a service call, receiving a data packet in the form of a message sent by an IoT device, and managing actuators or executing a computational task on a virtual machine, are often associated with and composed of IoT workflows. The development and deployment of such IoT workflows and their management systems in real life, including communication and network operations, can be complicated due to high operation costs and access limitations. Therefore, simulation solutions are often applied for such purposes. In this paper, we introduce a novel simulator extension of the DISSECT-CF-Fog simulator that leverages the workflow scheduling and its execution capabilities to model real-life IoT use cases. We also show that state-of-the-art simulators typically omit the IoT factor in the case of the scientific workflow evaluation. Therefore, we present a scalability study focusing on scientific workflows and on the interoperability of scientific and IoT workflows in DISSECT-CF-Fog.},
	year = {2023},
	eissn = {1424-8220},
	orcid-numbers = {Kecskeméti, Gábor/0000-0001-5716-8857; Kertész, Attila/0000-0002-9457-2928}
}

@article{MTMT:33395482,
	title = {Developing a Workflow Management System Simulation for Capturing Internal IaaS Behavioural Knowledge},
	url = {https://m2.mtmt.hu/api/publication/33395482},
	author = {Al-Haboobi, Ali and Kecskeméti, Gábor},
	doi = {10.1007/s10723-022-09638-7},
	journal-iso = {J GRID COMPUT},
	journal = {JOURNAL OF GRID COMPUTING},
	volume = {21},
	unique-id = {33395482},
	issn = {1570-7873},
	abstract = {Scientific workflows are becoming increasingly important for complex scientific applications. Conducting real experiments for large-scale workflows is challenging because they are very expensive and time consuming. A simulation is an alternative approach to a real experiment that can help evaluating the performance of workflow management systems (WMS) and optimise workflow management techniques. Although there are several workflow simulators available today, they are often user-oriented and treat the cloud as a black box. Unfortunately, this behaviour prevents the evaluation of the infrastructure level impact of the various decisions made by the WMSs. To address these issues, we have developed a WMS simulator (called DISSECT-CF-WMS) on DISSECT-CF that exposes the internal details of cloud infrastructures. DISSECT-CF-WMS enables better energy awareness by allowing the study of schedulers for physical machines. It also enables dynamic provisioning to meet the resource needs of the workflow application while considering the provisioning delay of a VM in the cloud. We evaluated our simulation extension by running several workflow applications on a given infrastructure. The experimental results show that we can investigate different schedulers for physical machines on different numbers of virtual machines to reduce energy consumption. The experiments also show that DISSECT-CF-WMS is up to 295× faster than WorkflowSim and still provides equivalent results. The experimental results of auto-scaling show that it can optimise makespan, energy consumption and VM utilisation in contrast to static VM provisioning.},
	year = {2023},
	eissn = {1572-9184},
	orcid-numbers = {Al-Haboobi, Ali/0000-0001-7632-2485; Kecskeméti, Gábor/0000-0001-5716-8857}
}

@article{MTMT:32531775,
	title = {Execution Time Reduction in Function Oriented Scientific Workflows},
	url = {https://m2.mtmt.hu/api/publication/32531775},
	author = {Al-Haboobi, Ali and Kecskeméti, Gábor},
	doi = {10.14232/actacyb.288489},
	journal-iso = {ACTA CYBERN-SZEGED},
	journal = {ACTA CYBERNETICA},
	volume = {25},
	unique-id = {32531775},
	issn = {0324-721X},
	year = {2021},
	eissn = {2676-993X},
	pages = {131-150},
	orcid-numbers = {Al-Haboobi, Ali/0000-0001-7632-2485; Kecskeméti, Gábor/0000-0001-5716-8857}
}

@{MTMT:32186258,
	title = {Improving Auto-Scaling Mechanism for Reducing the Makespan and Cost of Workflow Execution in the Cloud},
	url = {https://m2.mtmt.hu/api/publication/32186258},
	author = {Al-Haboobi, Ali and Kecskeméti, Gábor},
	booktitle = {XXIV. Tavaszi Szél Konferencia 2021: Absztrakt kötet},
	unique-id = {32186258},
	abstract = {Scientific workflows are an increasingly important field for complex scientific applications.
		Workflows need Workflow Management Systems (WMSs) to run them on distributed computing
		platforms at different scales. Cloud computing is fast becoming a key instrument in executing
		workflows. A workflow has phases during the execution that there are different numbers of jobs in
		each phase of the workflow which all could require different levels of computing resources. To cope
		up with the demand of workflow execution, the cloud computing provides the auto-scaling
		mechanism that has the ability to automatically increase or decrease the computational resources
		delivered to a cloud workload based on need. It can add more Virtual Machines (VMs) for
		processing the jobs in a certain phase. However, this might cause a resource over-provisioning issue
		for other phases. Several auto-scaling mechanisms do not consider the number of jobs in each
		workflow phase as well as the workflow's structure. Furthermore, awareness and efficient techniques
		for dealing with VM provisioning and de-provisioning delays are required. To overcome these
		challenges and resource under- and over-provisioning issues, we have designed and implemented an
		auto-scaling mechanism on the DISSECT-CF simulation framework. Firstly, it can provision and deprovision
		virtual machines based on the number of jobs in each workflow phase during the
		execution. Moreover, it analyses the structure of workflow before the execution to prepare the
		required number of VMs in each phase in advance. Finally, it starts VMs earlier in a planning cycle
		with the purpose to prevent jobs from having to be delayed because of provisioning times. We
		evaluated the auto-scaling mechanisms with five realistic workflows from diverse scientific
		applications. We have chosen these workflows due to the complexity of their structure, large-scale
		nature, data dependencies, and data size differences. The experimental results show that our
		proposed mechanism can reduce the execution time and cost by comparing with some currently
		available auto-scaling mechanisms.},
	year = {2021},
	pages = {1},
	orcid-numbers = {Kecskeméti, Gábor/0000-0001-5716-8857}
}

@inproceedings{MTMT:31925040,
	title = {Improving Existing WMS for Reduced Makespan of Workflows with Lambda},
	url = {https://m2.mtmt.hu/api/publication/31925040},
	author = {Al-Haboobi, Ali and Kecskeméti, Gábor},
	booktitle = {Euro-Par 2020: Parallel Processing Workshops},
	doi = {10.1007/978-3-030-71593-9_21},
	unique-id = {31925040},
	year = {2021},
	pages = {261-272},
	orcid-numbers = {Kecskeméti, Gábor/0000-0001-5716-8857}
}

@CONFERENCE{MTMT:31383116,
	title = {Reducing Execution Time of An Existing Lambda based Scientific Workflow System},
	url = {https://m2.mtmt.hu/api/publication/31383116},
	author = {Al-Haboobi, Ali and Kecskeméti, Gábor},
	booktitle = {The 12th Conference of PhD Students in Computer Science},
	unique-id = {31383116},
	year = {2020},
	pages = {3-6},
	orcid-numbers = {Kecskeméti, Gábor/0000-0001-5716-8857}
}