M. Maack, “Online load balancing on uniform machines with limited migration,”10.1016/j.orl.2023.02.013__Operations Research Letters, vol. 51, no. 3, pp. 220–225, 2023, doi:10.1016/j.orl.2023.02.013 .

H. Karl, M. Maack, F. Meyer auf der Heide, S. Pukrop, and A. Redder, “On-The-Fly Compute Centers II: Execution of Composed Services in Configurable Compute Centers,” in On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412, C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, Eds. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 183–202.

M. Maack, F. Meyer auf der Heide, and S. Pukrop, “Server Cloud Scheduling,”10.1007/s00453-023-01189-x__Algorithmica, 2023, doi:10.1007/s00453-023-01189-x .

M. A. Deppert, K. Jansen, M. Maack, S. Pukrop, and M. Rau, “Scheduling with Many Shared Resources,”10.1109/ipdps54959.2023.00049__2023, doi:10.1109/ipdps54959.2023.00049 .

C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023.

S. B. Schneider, S. Werner, R. Khalili, A. Hecker, and H. Karl, “mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks,” presented at the IEEE/IFIP Network Operations and Management Symposium (NOMS), Budapest, 2022.

L. Epstein, A. Lassota, A. Levin, M. Maack, and L. Rohwedder, “Cardinality Constrained Scheduling in Online Models,”10.4230/LIPIcs.STACS.2022.28__in 39th International Symposium on Theoretical Aspects of Computer Science, STACS 2022, March 15-18, 2022, Marseille, France (Virtual Conference), 2022, vol. 219, p. 28:1–28:15, doi:10.4230/LIPIcs.STACS.2022.28 .

A. Redder, A. Ramaswamy, and H. Karl, “Age of Information Process under Strongly Mixing Communication -- Moment Bound, Mixing Rate and Strong Law,” presented at the 58th Allerton Conference on Communication, Control, and Computing, 2022.

A. Redder, A. Ramaswamy, and H. Karl, “Multi-agent Policy Gradient Algorithms for Cyber-physical Systems with Lossy Communication,”10.5220/0010845400003116__2022, doi:10.5220/0010845400003116 .

A. Redder, A. Ramaswamy, and H. Karl, “Distributed gradient-based optimization in the presence of dependent  aperiodic communication,” arXiv:2201.11343. 2022.

A. Redder, A. Ramaswamy, and H. Karl, “Asymptotic Convergence of Deep Multi-Agent Actor-Critic Algorithms,” arXiv:2201.00570. 2022.

A. Redder, A. Ramaswamy, and H. Karl, “Practical Network Conditions for the Convergence of Distributed Optimization,” IFAC-PapersOnLine, vol. 55, no. 13, pp. 133–138, 2022.

M. Maack, S. Pukrop, and A. R. Rasmussen, “(In-)Approximability Results for Interval, Resource Restricted, and Low Rank Scheduling,”10.4230/LIPIcs.ESA.2022.77__in 30th Annual European Symposium on Algorithms, ESA 2022, September 5-9, 2022, Berlin/Potsdam, Germany, 2022, vol. 244, p. 77:1–77:13, doi:10.4230/LIPIcs.ESA.2022.77 .

S. Werner, S. B. Schneider, and H. Karl, “Use What You Know: Network and Service Coordination Beyond Certainty,” presented at the IEEE/IFIP Network Operations and Management Symposium (NOMS), Budapest, 2022.

M. Maack, F. Meyer auf der Heide, and S. Pukrop, “Server Cloud Scheduling,” in Approximation and Online Algorithms, Cham: Springer International Publishing, 2022.

A. Hasnain and H. Karl, “Learning Flow Scheduling,” in 2021 IEEE 18th Annual Consumer Communications &; Networking Conference (CCNC), Las Vegas, USA.

A. Hasnain and H. Karl, “Learning Coflow Admissions,” in IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Vancouver BC Canada.

S. B. Schneider, H. Qarawlus, and H. Karl, “Distributed Online Service Coordination Using Deep Reinforcement Learning,” in IEEE International Conference on Distributed Computing Systems (ICDCS), Washington, DC, USA, 2021.

S. B. Schneider, M. Jürgens, and H. Karl, “Divide and Conquer: Hierarchical Network and Service Coordination,” in IFIP/IEEE International Symposium on Integrated Network Management (IM), Bordeaux, France, 2021.

S. B. Schneider et al., “Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning,” Transactions on Network and Service Management, 2021.