Biography

Since October 2011 Professor Dr. Ramin Yahyapour is managing director of GWDG, a joint compute and IT competence center of the university and the Max Planck Society. At the same time, he became full professor for Practical Computer Science at the Georg-August-Universität Göttingen. Before, he was Professor at the Technische Universität Dortmund, director of the IT & Media Center, and CIO of the university.

Professor Yahyapour holds a doctoral degree in Electrical Engineering. His research focus is on efficient resource management and its application on service-oriented infrastructures, clouds, and data management.

Professor Yahyapour was and is active in several national and international research projects. He was e.g. scientific coordinator of the FP7 integrated project SLA@SOI or executive member of the CoreGRID Network of Excellence. Professor Yahyapour serves regularly as reviewer for funding agencies and consultant for IT organizations. He is organizer and program committee member of several conferences and workshops as well as reviewer for multiple journals.

Research Interests

• resource management and scheduling
• service-oriented infrastructures and service computing
• cloud computing
• data management

Recent Publications

2022

• Online Orchestration of Collaborative Caching for Multi-Bitrate Videos in Edge Computing (Song Yang, Lei Jiao, Ramin Yahyapour, Jiannong Cao), 2022-01-01 DOI BibTeX

2021

• A two-phase virtual machine placement policy for data-intensive applications in cloud (Samaneh Sadegh, Kamran Zamanifar, Piotr Kasprzak, Ramin Yahyapour), 2021-01-01 DOI BibTeX
• An Optimized Single Sign-On Schema for Reliable Multi -Level Security Management in Clouds (Aytaj Badirova, Shirin Dabbaghi, Faraz Fatemi-Moghaddam, Philipp Wieder, Ramin Yahyapour), In Proceedings of FiCloud 2021 – 8th International Conference on Future Internet of Things and Cloud, 2021-01-01 DOI BibTeX
• Recent Advances of Resource Allocation in Network Function Virtualization (Song Yang, Fan Li, Stojan Trajanovski, Ramin Yahyapour, Xiaoming Fu), 2021-01-01 DOI BibTeX
• Sekundäre Nutzung von hausärztlichen Routinedaten ist machbar – Bericht vom RADAR Projekt (Johannes Hauswaldt, Thomas Bahls, Arne Blumentritt, Iris Demmer, Johannes Drepper, Roland Groh, Stephanie Heinemann, Wolfgang Hoffmann, Valérie Kempter, Johannes Pung, Otto Rienhoff, Falk Schlegelmilch, Philipp Wieder, Ramin Yahyapour, Eva Hummers), 2021-01-01 BibTeX

2019

• CBase: Fast Virtual Machine storage data migration with a new data center structure (Fei Zhang, Guangming Liu, Bo Zhao, Piotr Kasprzak, Xiaoming Fu, Ramin Yahyapour), 2019-01-01 DOI BibTeX
• Cloud Security Distributary Set (CSDS): A Policy-Based Framework to Define Multi-Level Security Structure in Clouds (Faraz Fatemi Moghaddam, Philipp Wieder, Süleyman Berk Çemberci, Ramin Yahyapour), In COINS '19 Proceedings of the International Conference on Omni-Layer Intelligent Systems, 2019-01-01 BibTeX
• Das Ökosystem der Datenwissenschaften (Thomas Ludwig, Wolfgang E. Nagel, Ramin Yahyapour), 2019-01-01 DOI BibTeX
• Delay-Sensitive and Availability-Aware Virtual Network Function Scheduling for NFV (Song Yang, Fan Li, Ramin Yahyapour, Xiaoming Fu), 2019-01-01 DOI BibTeX
• Loyal Consumers or One-Time Deal Hunters: Repeat Buyer Prediction for E-Commerce (Bo Zhao, Atsuhiro Takasu, Ramin Yahyapour, Xiaoming Fu), In 2019 International Conference on Data Mining Workshops (ICDMW), 2019-01-01 DOI BibTeX

@article{2_114612,

	abstract = {"In the traditional video streaming service provisioning paradigm, users typically request video contents through nearby Content Delivery Network (CDN) server(s). However, because of the uncertain wide area networks delays, the (remote) users usually suffer from long video streaming delay, which affects the quality of experience. Multi-Access Edge Computing (MEC) offers caching infrastructures in closer proximity to end users than conventional Content Delivery Networks (CDNs). Yet, for video caching, MEC's potential has not been fully unleashed as it overlooks the opportunities of collaborative caching and multi-bitrate video transcoding. In this paper, we model and formulate an Integer Linear Program (ILP) to capture the long-term cost minimization problem for caching videos at MEC, allowing joint exploitation of MEC with CDN and real-time video transcoding to satisfy arbitrary user demands. While this problem is intractable and couples the caching decisions for adjacent time slots, we design a polynomial-time online orchestration framework which first relaxes and carefully decomposes the problem into a series of subproblems solvable in each individual time slot and then converts the fractional solutions into integers without violating constraints. We have formally proved a parameterized-constant competitive ratio as the performance guarantee for our approach, and also conducted extensive evaluations to confirm its superior practical performance. Simulation results demonstrate that our proposed algorithm outperforms the state-of-the-art algorithms, with 13.6% improvement on average in terms of total cost."},
	author = {Song Yang and Lei Jiao and Ramin Yahyapour and Jiannong Cao},
	doi = {10.1109/TPDS.2022.3182022},
	grolink = {https://resolver.sub.uni-goettingen.de/purl?gro-2/114612},
	month = {01},
	title = {Online Orchestration of Collaborative Caching for Multi-Bitrate Videos in Edge Computing},
	type = {article},
	year = {2022},
}

@article{2_97749,

	abstract = {"Zusammenfassung Ziel der Studie „Real world“-Daten aus der ambulanten Gesundheitsversorgung sind in Deutschland nur schwer systematisch und longitudinal zu erlangen. Unsere Vision ist eine permanente Datenablage mit repräsentativen, de-identifizierten Patienten- und Versorgungsdaten, längsschnittlich, fortwährend aktualisiert und von verschiedenen Versorgern, mit der Möglichkeit zur Verknüpfung mit weiteren Daten, etwa aus Patientenbefragungen oder biologischer Forschung, zugänglich für andere Forscher. Wir berichten methodische Vorgehensweisen und Ergebnisse aus dem RADAR Projekt.Methodik Untersuchung des Rechtsrahmens, Entwicklung prototypischer technischer Abläufe und Lösungen, mit Machbarkeitsstudie zur Evaluation von technischer und inhaltlicher Funktionalität sowie Eignung für Fragestellungen der Versorgungsforschung.Ergebnisse Ab 2016 entwickelte ein interdisziplinäres Wissenschaftlerteam ein Datenschutzkonzept für Exporte von Versorgungsdaten aus elektronischen Praxisverwaltungssystemen. Eine technische und organisatorische Forschungsinfrastruktur im ambulanten Sektor wurden entwickelt und im Anwendungsfall „Orale Antikoagulation“ (OAK) umgesetzt. In 7 niedersächsischen Hausarztpraxen wurden 100 Patienten gewonnen und nach informierter Einwilligung ihre ausgewählten Behandlungsdaten, reduziert auf 40 relevante Datenfelder, über die Behandlungsdatentransfer-Schnittstelle extrahiert, unmittelbar vor Ort in identifizierende bzw. medizinische Daten getrennt und verschlüsselt zur Treuhandstelle (THS) bzw. an den Datenhalter übertragen. 75 Patienten, die die Einschlusskriterien erfüllten (mind. 1 Jahr Behandlung mit OAK), erhielten einen Lebensqualitäts-Fragebogen über die THS per Post. Von 66 Rücksendungen wurden 63 Fragebogenergebnisse mit den Behandlungsdaten in der Datenablage verknüpft.Schlussfolgerung Die rechtskonforme Machbarkeit der Gewinnung von pseudonymisierten hausärztlichen Routinedaten mit expliziter informierter Patienteneinwilligung und deren wissenschaftliche Nutzung einschließlich Re-Kontaktierung und Einbindung von Fragebogendaten konnte nachgewiesen werden. Die Schutzkonzepte Privacy by design und Datenminimierung (Artikel 25 mit Erwägungsgrund 78 DSGVO) wurden systematisch in das RADAR Projekt integriert und begründen wesentlich, dass der Machbarkeitsnachweis rechtskonformer Primärdatengewinnung und sekundärer Nutzung für Forschungszwecke gelang. Eine Nutzung hinreichend anonymisierter, aber noch sinnvoller hausärztlicher Gesundheitsdaten ohne individuelle Einwilligung ist im bestehenden Rechtsrahmen in Deutschland schwerlich umsetzbar."},
	author = {Johannes Hauswaldt and Thomas Bahls and Arne Blumentritt and Iris Demmer and Johannes Drepper and Roland Groh and Stephanie Heinemann and Wolfgang Hoffmann and Valérie Kempter and Johannes Pung and Otto Rienhoff and Falk Schlegelmilch and Philipp Wieder and Ramin Yahyapour and Eva Hummers},
	grolink = {https://resolver.sub.uni-goettingen.de/purl?gro-2/97749},
	month = {01},
	title = {Sekundäre Nutzung von hausärztlichen Routinedaten ist machbar – Bericht vom RADAR Projekt},
	type = {article},
	year = {2021},
}

@article{2_68120,

	abstract = {"Network Function Virtualization (NFV) has been emerging as an appealing solution that transforms complex network functions from dedicated hardware implementations to software instances running in a virtualized environment. Due to the numerous advantages such as flexibility, efficiency, scalability, short deployment cycles, and service upgrade, NFV has been widely recognized as the next-generation network service provisioning paradigm. In NFV, the requested service is implemented by a sequence of Virtual Network Functions (VNF) that can run on generic servers by leveraging the virtualization technology. These VNFs are pitched with a predefined order through which data flows traverse, and it is also known as the Service Function Chaining (SFC). In this article, we provide an overview of recent advances of resource allocation in NFV. We generalize and analyze four representative resource allocation problems, namely, (1) the VNF Placement and Traffic Routing problem, (2) VNF Placement problem, (3) Traffic Routing problem in NFV, and (4) the VNF Redeployment and Consolidation problem. After that, we study the delay calculation models and VNF protection (availability) models in NFV resource allocation, which are two important Quality of Service (QoS) parameters. Subsequently, we classify and summarize the representative work for solving the generalized problems by considering various QoS parameters (e.g., cost, delay, reliability, and energy) and different scenarios (e.g., edge cloud, online provisioning, and distributed provisioning). Finally, we conclude our article with a short discussion on the state-of-the-art and emerging topics in the related fields, and highlight areas where we expect high potential for future research."},
	author = {Song Yang and Fan Li and Stojan Trajanovski and Ramin Yahyapour and Xiaoming Fu},
	doi = {10.1109/TPDS.2020.3017001},
	grolink = {https://resolver.sub.uni-goettingen.de/purl?gro-2/68120},
	month = {01},
	title = {Recent Advances of Resource Allocation in Network Function Virtualization},
	type = {article},
	year = {2021},
}

@inproceedings{2_121153,

	author = {Aytaj Badirova and Shirin Dabbaghi and Faraz Fatemi-Moghaddam and Philipp Wieder and Ramin Yahyapour},
	doi = {10.1109/FiCloud49777.2021.00014},
	grolink = {https://resolver.sub.uni-goettingen.de/purl?gro-2/121153},
	journal = {Proceedings of FiCloud 2021 – 8th International Conference on Future Internet of Things and Cloud},
	month = {01},
	title = {An Optimized Single Sign-On Schema for Reliable Multi -Level Security Management in Clouds},
	type = {inproceedings},
	year = {2021},
}

@article{2_84902,

	author = {Samaneh Sadegh and Kamran Zamanifar and Piotr Kasprzak and Ramin Yahyapour},
	doi = {10.1016/j.jnca.2021.103025},
	grolink = {https://resolver.sub.uni-goettingen.de/purl?gro-2/84902},
	month = {01},
	title = {A two-phase virtual machine placement policy for data-intensive applications in cloud},
	type = {article},
	year = {2021},
}

@inproceedings{2_63192,

	abstract = {"Merchants sometimes run big promotions (e.g., discounts or cash coupons) on particular dates (e.g., Boxing-day Sales, \"Black Friday\" or \"Double 11 (Nov 11th)\", in order to attract a large number of new buyers. Unfortunately, many of the attracted buyers are one-time deal hunters, and these promotions may have little long lasting impact on sales. To alleviate this problem, it is important for merchants to identify who can be converted into repeated buyers. By targeting on these potential loyal customers, merchants can greatly reduce the promotion cost and enhance the return on investment (ROI). It is well known that in the field of online advertising, customer targeting is extremely challenging, especially for fresh buyers. With the long-term user behavior log accumulated by Tmall.com, we get a set of merchants and their corresponding new buyers acquired during the promotion on the \"Double 11\" day. Our goal is to predict which new buyers for given merchants will become loyal customers in the future. In other words, we need to predict the probability that these new buyers would purchase items from the same merchants again within 6 months. A data set containing around 200k users is given for training, while the other of similar size for testing. We extracted as many features as possible and find the key features to train our models. We proposed merged model of different classification models and merged lightGBM model with different parameter sets. The experimental results show that our merged models can bring about great performance improvements comparing with the original models."},
	author = {Bo Zhao and Atsuhiro Takasu and Ramin Yahyapour and Xiaoming Fu},
	doi = {10.1109/ICDMW.2019.00158},
	grolink = {https://resolver.sub.uni-goettingen.de/purl?gro-2/63192},
	journal = {2019 International Conference on Data Mining Workshops (ICDMW)},
	month = {01},
	title = {Loyal Consumers or One-Time Deal Hunters: Repeat Buyer Prediction for E-Commerce},
	type = {inproceedings},
	year = {2019},
}

@article{2_62710,

	abstract = {"Network Function Virtualization (NFV) has been emerging as an appealing solution that transforms from dedicated hardware implementations to software instances running in a virtualized environment. In NFV, the requested service is implemented by a sequence of Virtual Network Functions (VNF) that can run on generic servers by leveraging the virtualization technology. These VNFs are pitched with a predefined order, and it is also known as the Service Function Chaining (SFC). Considering that the delay and resiliency are two important Service Level Agreements (SLA) in a NFV service, in this paper, we first investigate how to quantitatively model the traversing delay of a flow in both totally ordered and partially ordered SFCs. Subsequently, we study how to calculate the VNF placement availability mathematically for both unprotected and protected SFCs. After that, we study the delay-sensitive Virtual Network Function (VNF) placement and routing problem with and without resiliency concerns. We prove that this problem is NP-hard under two cases. We subsequently propose an exact Integer Nonlinear Programming formulation and an efficient heuristic for this problem in each case. Finally, we evaluate the proposed algorithms in terms of acceptance ratio, average number of used nodes and total running time via extensive simulations."},
	author = {Song Yang and Fan Li and Ramin Yahyapour and Xiaoming Fu},
	doi = {10.1109/TSC.2019.2927339},
	grolink = {https://resolver.sub.uni-goettingen.de/purl?gro-2/62710},
	month = {01},
	title = {Delay-Sensitive and Availability-Aware Virtual Network Function Scheduling for NFV},
	type = {article},
	year = {2019},
}

@article{2_90987,

	author = {Thomas Ludwig and Wolfgang E. Nagel and Ramin Yahyapour},
	doi = {10.1007/s00287-019-01219-5},
	grolink = {https://resolver.sub.uni-goettingen.de/purl?gro-2/90987},
	month = {01},
	title = {Das Ökosystem der Datenwissenschaften},
	type = {article},
	year = {2019},
}

@inproceedings{2_62712,

	abstract = {"Security challenges are the most important obstacles for the advancement of IT-based on-demand services and cloud computing as an emerging technology. In this paper, a structural policy management engine has been introduced to enhance the reliability of managing different policies in clouds and to provide standard as well as dedicated security levels (rings) based on the capabilities of the cloud provider and the requirements of cloud customers. Cloud security ontology (CSON) is an object-oriented framework defined to manage and enable appropriate communication between the potential security terms of cloud service providers. CSON uses two super classes to establish appropriate mapping between the requirements of cloud customers and the capabilities of the service provider."},
	author = {Faraz Fatemi Moghaddam and Philipp Wieder and Süleyman Berk Çemberci and Ramin Yahyapour},
	grolink = {https://resolver.sub.uni-goettingen.de/purl?gro-2/62712},
	journal = {COINS '19 Proceedings of the International Conference on Omni-Layer Intelligent Systems},
	month = {01},
	title = {Cloud Security Distributary Set (CSDS): A Policy-Based Framework to Define Multi-Level Security Structure in Clouds},
	type = {inproceedings},
	year = {2019},
}

@article{2_57358,

	abstract = {"Live Virtual Machine (VM) migration within a data center is an important technology for cloud management, and has brought many benefits to both cloud providers and users. With the development of cloud computing, across-data-center VM migration is also desired. Normally, there is no shared storage system between data centers, hence the storage data (disk image) of a VM will be migrated to the destination data center as well. However, the slow network speed of the Internet and the comparatively large size of VM disk image make VM storage data migration become a bottleneck for live VM migration across data centers. In this paper, based on a detailed analysis of VM deployment models and the nature of VM image data, we design and implement a new migration system, called CBase. The key concept of CBase is a newly introduced central base image repository for reliable and efficient data sharing between VMs and data centers. With this central repository, further performance optimizations to VM storage data migration are made possible. Two migration mechanisms (data deduplication and Peer-to-Peer (P2P) file sharing) are utilized to accelerate base image migration, and a strategy is designed to elevate the synchronization of newly-written disk blocks. The results from an extensive experiment show that CBase significantly outperforms existing migration mechanisms under different conditions regarding total migration time and total network traffic. In particular, CBase with data deduplication is better than P2P file sharing for base image migration in our experimental environment."},
	author = {Fei Zhang and Guangming Liu and Bo Zhao and Piotr Kasprzak and Xiaoming Fu and Ramin Yahyapour},
	doi = {10.1016/j.jpdc.2018.10.001},
	grolink = {https://resolver.sub.uni-goettingen.de/purl?gro-2/57358},
	month = {01},
	title = {CBase: Fast Virtual Machine storage data migration with a new data center structure},
	type = {article},
	year = {2019},
}