Learning Flow Scheduling
A. Hasnain, H. Karl, in: 2021 IEEE 18th Annual Consumer Communications &; Networking Conference (CCNC), IEEE Computer Society, n.d.

Learning Coflow Admissions
A. Hasnain, H. Karl, in: IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE Communications Society, n.d.

Coflow Scheduling with Performance Guarantees for Data Center Applications
A. Hasnain, H. Karl, in: 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID), IEEE Computer Society, 2020.

An Exact Branch-and-Price Algorithm for Scheduling Rescue Units during Disaster Response
G. Rauchecker, G. Schryen, European Journal of Operational Research 272 (2019) 352–363.

Using High Performance Computing for Unrelated Parallel Machine Scheduling with Sequence-Dependent Setup Times: Development and Computational Evaluation of a Parallel Branch-and-Price Algorithm
G. Rauchecker, G. Schryen, Computers &; Operations Research (2019) 338–357.

Deep reinforcement learning for scheduling in large-scale networked control systems
A. Redder, A. Ramaswamy, D. Quevedo, in: Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems, 2019.

A Data Structure for Planning Based Workload Management of Heterogeneous HPC Systems
A. Keller, in: D. Klusádek, W. Cirne, N. Desai (Eds.), Proc. Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP), Springer, 2018, pp. 132–151.

Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief
G. Rauchecker, G. Schryen, in: Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management, 2018.

An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling
J. Bossek, C. Grimme, in: 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017, pp. 1–8.

Inter-Datacenter Scheduling of Large Data Flows
R. Cohen, G. Polevoy, Cloud Computing, IEEE Transactions On PP (2015) 1–1.

High-Performance Computing for Scheduling Decision Support: A Parallel Depth-First Search Heuristic
G. Rauchecker, G. Schryen, in: Australasian Conference on Information Systems, 2015, pp. 1–13.

Over effective hard real-time hardware tasks scheduling and allocation
Z. Guettatfi, O. Kermia, A. Khouas, in: 25th International Conference on Field Programmable Logic and Applications (FPL), Imperial College, 2015.

On the Admission of Dependent Flows in Powerful Sensor Networks
R. Cohen, I. Nudelman, G. Polevoy, Networking, IEEE/ACM Transactions On 21 (2013) 1461–1471.

Assertion-Based Verification of RTOS Properties
M.F.S. Oliveira, H. Zabel, W. Müller, in: Proceedings of DATE’10, IEEE, Dresden, 2010.

Accurate RTOS Modelling and Analysis with SystemC
H. Zabel, W. Müller, A. Gerstlauer, in: W. Ecker, W. Müller, R. Dömer (Eds.), Hardware Dependent Software - Principles and Practice, Springer Verlag, Dordrecht, 2009, pp. 233–260.

Increased Accuracy through Noise Injection in Abstract RTOS Simulation
H. Zabel, W. Müller, in: Proceedings of DATE’09, Nice, France, 2009.

Server-based execution of periodic tasks on dynamically reconfigurable hardware
K. Danne, R. Mühlenbernd, M. Platzner, IET Computers Digital Techniques 1 (2007) 295–302.

Visual Modeling and 3D-Representation with a Complete Visual Programming Language --- A Case Study in Manufacturing
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