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| | Preview | Author(s) | Title | Type | Issue Date |
| 1 | | Dustdar, Schahram | Distributed Computing Continuum Systems | Inproceedings Konferenzbeitrag | 24-Aug-2022 |
| 2 | | Dustdar, Schahram | Distributed Computing Continuum Systems | Inproceedings Konferenzbeitrag | 22-Aug-2022 |
| 3 | | Dehury, Chinmaya Kumar ; Donta, Praveen Kumar ; Dustdar, Schahram ; Srirama, Satish Narayana | CCEI-IoT: Clustered and Cohesive Edge Intelligence in Internet of Things | Inproceedings Konferenzbeitrag  | 2022 |
| 4 | | Amiri, Amirali ; Zdun, Uwe ; van Hoorn, Andre ; Dustdar, Schahram | Cost-Aware Multidimensional Auto-Scaling of Service- and Cloud-Based Dynamic Routing to Prevent System Overload | Inproceedings Konferenzbeitrag | 2022 |
| 5 | | Dustdar, Schahram | Edge Intelligence | Konferenzbeitrag Inproceedings | 2021 |
| 6 | | Nastic, Stefan ; Pusztai, Thomas ; Morichetta, Andrea ; Casamayor Pujol, Victor ; Dustdar, Schahram ; Vij, Deepak ; Xiong, Ying | Polaris Scheduler: Edge Sensitive and SLO Aware Workload Scheduling in Cloud-Edge-IoT Clusters | Konferenzbeitrag Inproceedings | 2021 |
| 7 | | Pusztai, Thomas ; Morichetta, Andrea ; Casamayor Pujol, Victor ; Dustdar, Schahram ; Nastic, Stefan ; Ding, Xiaoning ; Vij, Deepak ; Xiong, Ying | A Novel Middleware for Efficiently Implementing Complex Cloud-Native SLOs | Konferenzbeitrag Inproceedings | 2021 |
| 8 | | Pusztai, Thomas ; Rossi, Fabiana ; Dustdar, Schahram | Pogonip: Scheduling Asynchronous Applications on the Edge | Konferenzbeitrag Inproceedings | 2021 |
| 9 | | Pusztai, Thomas ; Morichetta, Andrea ; Casamayor Pujol, Victor ; Dustdar, Schahram ; Nastic, Stefan ; Ding, Xiaoning ; Vij, Deepak ; Xiong, Ying | SLO Script: A Novel Language for Implementing Complex Cloud-Native Elasticity-Driven SLOs | Konferenzbeitrag Inproceedings | 2021 |
| 10 | | Raith, Philipp ; Dustdar, Schahram | Edge Intelligence as a Service | Konferenzbeitrag Inproceedings | 2021 |
| 11 | | McNamee, Francis ; Dustdar, Schahram ; Kilpatrick, Peter ; Shi, Weisong ; Spence, Ivor ; Varghese, Blesson | The Case for Adaptive Deep Neural Networks in Edge Computing | Konferenzbeitrag Inproceedings | 2021 |
