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Network slicing is an emerging technique for providing resources to diverse wireless services with heterogeneous quality-of-service needs. However, beyond satisfying end-to-end requirements of network users, network slicing needs to also…
To support on-device inference, the next-generation mobile networks are expected to support real-time model downloading services to mobile users. However, powerful AI models typically have large model sizes, resulting in excessive…
A sophisticated and efficient network slicing architecture is needed to support the orchestration of network slices across multiple administrative domains. Such multi-domain architecture shall be agnostic of the underlying virtualization…
Network slicing is emerging as a promising method to provide sought-after versatility and flexibility to cope with ever-increasing demands. To realize such potential advantages and to meet the challenging requirements of various network…
We propose a new problem formulation and a corresponding evaluation framework to advance research on unsupervised domain adaptation for semantic image segmentation. The overall goal is fostering the development of adaptive learning systems…
The use of satellite networks has increased significantly in recent years due to their advantages over purely terrestrial systems, such as higher availability and coverage. However, to effectively provide these services, satellite networks…
The increased availability of the multi-view data (data on the same samples from multiple sources) has led to strong interest in models based on low-rank matrix factorizations. These models represent each data view via shared and individual…
For the layer 'System Level Functionality' of the Phyisical Internet, it is needed to estimate end-to-end performance characteristics of transportations that visit multiple logistic domains. This paper proposes an approach based on a…
Effective network slicing requires an infrastructure/network provider to deal with the uncertain demand and real-time dynamics of network resource requests. Another challenge is the combinatorial optimization of numerous resources, e.g.,…
Towards addressing spectral scarcity and enhancing resource utilization in 5G networks, network slicing is a promising technology to establish end-to-end virtual networks without requiring additional infrastructure investments. By…
The customization of services in Fifth-generation (5G) and Beyond 5G (B5G) networks relies heavily on network slicing, which creates multiple virtual networks on a shared physical infrastructure, tailored to meet specific requirements of…
Recent advances in split learning (SL) have established it as a promising framework for privacy-preserving, communication-efficient distributed learning at the network edge. However, SL's sequential update process is vulnerable to even a…
Network slicing, a cornerstone technology for future networks, enables the creation of customized virtual networks on a shared physical infrastructure. This fosters innovation and agility by providing dedicated resources tailored to…
In this paper, we propose a general cross-layer optimization framework in which we explicitly consider both the heterogeneous and dynamically changing characteristics of delay-sensitive applications and the underlying time-varying network…
Historical fragmentation in spectrum access models accentuates the need for novel concepts that allow for efficient sharing of already available but underutilized spectrum. The emerging Licensed Shared Access (LSA) regulatory framework is…
Split learning (SL) is an emergent distributed learning framework which can mitigate the computation and wireless communication overhead of federated learning. It splits a machine learning model into a device-side model and a server-side…
Since the 6th Generation (6G) of wireless networks is expected to provide a new level of network services and meet the emerging expectations of the future, it will be a complex and intricate networking system. 6Gs sophistication and…
The state-of-the-art online learning models generally conduct a single online gradient descent when a new sample arrives and thus suffer from suboptimal model weights. To this end, we introduce an online broad learning system framework with…
Network slicing is considered a key mechanism to serve the multitude of tenants (e.g. vertical industries) targeted by forthcoming 5G systems in a flexible and cost-efficient manner. In this paper, we present a SDN/NFV architecture with…
The fifth generation (5G) and beyond wireless networks are foreseen to operate in a fully automated manner, in order to fulfill the promise of ultra-short latency, meet the exponentially increasing resource requirements, and offer the…