1 code implementation • 9 Oct 2024 • Anastasiya Danilenka, Alireza Furutanpey, Victor Casamayor Pujol, Boris Sedlak, Anna Lackinger, Maria Ganzha, Marcin Paprzycki, Schahram Dustdar
Specifically, we introduce a conceptual agent for heterogeneous pervasive systems that permits setting global systems constraints as high-level SLOs.
no code implementations • 26 Sep 2024 • Boris Sedlak, Victor Casamayor Pujol, Andrea Morichetta, Praveen Kumar Donta, Schahram Dustdar
The current scenario of IoT is witnessing a constant increase on the volume of data, which is generated in constant stream, calling for novel architectural and logical solutions for processing it.
1 code implementation • 25 Mar 2024 • Alireza Furutanpey, Qiyang Zhang, Philipp Raith, Tobias Pfandzelter, Shangguang Wang, Schahram Dustdar
Further, it embeds context and leverages inter-tile dependencies to lower transfer costs with negligible overhead.
no code implementations • 29 Nov 2023 • Ilir Murturi, Praveen Kumar Donta, Victor Casamayor Pujol, Andrea Morichetta, Schahram Dustdar
To overcome such challenges, we present a novel learning-driven ZT conceptual architecture designed for DCCS.
no code implementations • 29 Nov 2023 • Abhishek Hazra, Andrea Morichetta, Ilir Murturi, Lauri Lovén, Chinmaya Kumar Dehury, Victor Casamayor Pujol, Praveen Kumar Donta, Schahram Dustdar
Zero-touch network is anticipated to inaugurate the generation of intelligent and highly flexible resource provisioning strategies where multiple service providers collaboratively offer computation and storage resources.
no code implementations • 29 Nov 2023 • Ilir Murturi, Praveen Kumar Donta, Schahram Dustdar
Federated Learning (FL) has emerged as a promising paradigm to train machine learning models collaboratively while preserving data privacy.
no code implementations • 28 Nov 2023 • Boris Sedlak, Victor Casamayor Pujol, Praveen Kumar Donta, Schahram Dustdar
We present our framework for collaborative edge intelligence enabling individual edge devices to (1) develop a causal understanding of how to enforce their SLOs, and (2) transfer knowledge to speed up the onboarding of heterogeneous devices.
no code implementations • 17 Nov 2023 • Boris Sedlak, Victor Casamayor Pujol, Praveen Kumar Donta, Schahram Dustdar
Compute Continuum (CC) systems comprise a vast number of devices distributed over computational tiers.
no code implementations • 17 Nov 2023 • Boris Sedlak, Victor Casamayor Pujol, Praveen Kumar Donta, Schahram Dustdar
Machine Learning (ML) is a common tool to interpret and predict the behavior of distributed computing systems, e. g., to optimize the task distribution between devices.
no code implementations • 2 Jun 2023 • Ying Li, Xingwei Wang, Rongfei Zeng, Praveen Kumar Donta, Ilir Murturi, Min Huang, Schahram Dustdar
FDG combines the strengths of federated learning (FL) and domain generalization (DG) techniques to enable multiple source domains to collaboratively learn a model capable of directly generalizing to unseen domains while preserving data privacy.
no code implementations • 29 May 2023 • Amin Beheshti, Jian Yang, Quan Z. Sheng, Boualem Benatallah, Fabio Casati, Schahram Dustdar, Hamid Reza Motahari Nezhad, Xuyun Zhang, Shan Xue
We introduce ProcessGPT as a new technology that has the potential to enhance decision-making in data-centric and knowledge-intensive processes.
no code implementations • 25 May 2023 • Sukhpal Singh Gill, Minxian Xu, Panos Patros, Huaming Wu, Rupinder Kaur, Kamalpreet Kaur, Stephanie Fuller, Manmeet Singh, Priyansh Arora, Ajith Kumar Parlikad, Vlado Stankovski, Ajith Abraham, Soumya K. Ghosh, Hanan Lutfiyya, Salil S. Kanhere, Rami Bahsoon, Omer Rana, Schahram Dustdar, Rizos Sakellariou, Steve Uhlig, Rajkumar Buyya
ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data.
1 code implementation • 9 May 2023 • Alireza Furutanpey, Johanna Barzen, Marvin Bechtold, Schahram Dustdar, Frank Leymann, Philipp Raith, Felix Truger
We discuss the necessity, challenges, and solution approaches for extending existing work on classical edge computing to integrate QPUs.
1 code implementation • 21 Feb 2023 • Alireza Furutanpey, Philipp Raith, Schahram Dustdar
The rise of mobile AI accelerators allows latency-sensitive applications to execute lightweight Deep Neural Networks (DNNs) on the client side.
no code implementations • 21 Nov 2022 • Shiqiang Zhu, Ting Yu, Tao Xu, Hongyang Chen, Schahram Dustdar, Sylvain Gigan, Deniz Gunduz, Ekram Hossain, Yaochu Jin, Feng Lin, Bo Liu, Zhiguo Wan, Ji Zhang, Zhifeng Zhao, Wentao Zhu, Zuoning Chen, Tariq Durrani, Huaimin Wang, Jiangxing Wu, Tongyi Zhang, Yunhe Pan
In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications.
1 code implementation • 3 May 2022 • Henna Kokkonen, Lauri Lovén, Naser Hossein Motlagh, Abhishek Kumar, Juha Partala, Tri Nguyen, Víctor Casamayor Pujol, Panos Kostakos, Teemu Leppänen, Alfonso González-Gil, Ester Sola, Iñigo Angulo, Madhusanka Liyanage, Mehdi Bennis, Sasu Tarkoma, Schahram Dustdar, Susanna Pirttikangas, Jukka Riekki
We claim that to support the constantly growing requirements of intelligent applications in the device-edge-cloud computing continuum, resource orchestration needs to embrace edge AI and emphasize local autonomy and intelligence.
1 code implementation • 20 Apr 2022 • Bharath Sudharsan, Dineshkumar Sundaram, Pankesh Patel, John G. Breslin, Muhammad Intizar Ali, Schahram Dustdar, Albert Zomaya, Rajiv Ranjan
The majority of IoT devices like smartwatches, smart plugs, HVAC controllers, etc., are powered by hardware with a constrained specification (low memory, clock speed and processor) which is insufficient to accommodate and execute large, high-quality models.
no code implementations • 27 Nov 2021 • Aaron Yi Ding, Ella Peltonen, Tobias Meuser, Atakan Aral, Christian Becker, Schahram Dustdar, Thomas Hiessl, Dieter Kranzlmuller, Madhusanka Liyanage, Setareh Magshudi, Nitinder Mohan, Joerg Ott, Jan S. Rellermeyer, Stefan Schulte, Henning Schulzrinne, Gurkan Solmaz, Sasu Tarkoma, Blesson Varghese, Lars Wolf
Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI.
2 code implementations • 11 Oct 2021 • Shreshth Tuli, Sukhpal Singh Gill, Minxian Xu, Peter Garraghan, Rami Bahsoon, Schahram Dustdar, Rizos Sakellariou, Omer Rana, Rajkumar Buyya, Giuliano Casale, Nicholas R. Jennings
The worldwide adoption of cloud data centers (CDCs) has given rise to the ubiquitous demand for hosting application services on the cloud.
3 code implementations • ICLR 2022 • Shizhan Liu, Hang Yu, Cong Liao, Jianguo Li, Weiyao Lin, Alex X. Liu, Schahram Dustdar
Accurate prediction of the future given the past based on time series data is of paramount importance, since it opens the door for decision making and risk management ahead of time.