Zobrazeno 1 - 10
of 839
pro vyhledávání: '"Sasu, P"'
Digital Twins (DTs) are set to become a key enabling technology in future wireless networks, with their use in network management increasing significantly. We developed a DT framework that leverages the heterogeneity of network access technologies as
Externí odkaz:
http://arxiv.org/abs/2407.15520
The Sustainable Development Goals (SDGs) aim to resolve societal challenges, such as eradicating poverty and improving the lives of vulnerable populations in impoverished areas. Those areas rely on road infrastructure construction to promote accessib
Externí odkaz:
http://arxiv.org/abs/2406.11282
Autor:
Zhou, Pengyuan, Wang, Lin, Liu, Zhi, Hao, Yanbin, Hui, Pan, Tarkoma, Sasu, Kangasharju, Jussi
This paper offers an insightful examination of how currently top-trending AI technologies, i.e., generative artificial intelligence (Generative AI) and large language models (LLMs), are reshaping the field of video technology, including video generat
Externí odkaz:
http://arxiv.org/abs/2404.16038
In today's digital world, Generative Artificial Intelligence (GenAI) such as Large Language Models (LLMs) is becoming increasingly prevalent, extending its reach across diverse applications. This surge in adoption has sparked a significant increase i
Externí odkaz:
http://arxiv.org/abs/2312.14647
As privacy concerns continue to grow, federated learning (FL) has gained significant attention as a promising privacy-preserving technology, leading to considerable advancements in recent years. Unlike traditional machine learning, which requires cen
Externí odkaz:
http://arxiv.org/abs/2312.12091
The evolution towards 6G architecture promises a transformative shift in communication networks, with artificial intelligence (AI) playing a pivotal role. This paper delves deep into the seamless integration of Large Language Models (LLMs) and Genera
Externí odkaz:
http://arxiv.org/abs/2311.05842
The growing number of AI-driven applications in mobile devices has led to solutions that integrate deep learning models with the available edge-cloud resources. Due to multiple benefits such as reduction in on-device energy consumption, improved late
Externí odkaz:
http://arxiv.org/abs/2311.05739
The network edge's role in Artificial Intelligence (AI) inference processing is rapidly expanding, driven by a plethora of applications seeking computational advantages. These applications strive for data-driven efficiency, leveraging robust AI capab
Externí odkaz:
http://arxiv.org/abs/2311.03375
Autor:
Tuohino, Sasu, Vadimov, Vasilii, Teixeira, Wallace S., Malmelin, Tommi, Silveri, Matti, Möttönen, Mikko
We consider a superconducting half-wavelength resonator that is grounded at its both ends and contains a single Josephson junction. Previously this circuit was considered as a unimon qubit in the single-mode approximation where dc-phase-biasing the j
Externí odkaz:
http://arxiv.org/abs/2309.09732
Information-Centric Networking (ICN), with its data-oriented operation and generally more powerful forwarding layer, provides an attractive platform for distributed computing. This paper provides a systematic overview and categorization of different
Externí odkaz:
http://arxiv.org/abs/2309.08973