Related papers: Human-centric Data Dissemination in the IoP: Large…
The increasing traffic demand in cellular networks has recently led to the investigation of new strategies to save precious resources like spectrum and energy. A possible solution employs direct device-to-device (D2D) communications, which…
The next generation of Internet services, such as Metaverse, rely on mixed reality (MR) technology to provide immersive user experiences. However, the limited computation power of MR headset-mounted devices (HMDs) hinders the deployment of…
Mobile online social network services have seen a rapid increase, in which the huge amount of user-generated social media contents propagating between users via social connections has significantly challenged the traditional content…
Decentralized learning enables collaborative training of models across naturally distributed data without centralized coordination or maintenance of a global model. Instead, devices are organized in arbitrary communication topologies, in…
Opportunistic computing is a paradigm for completely self-organised pervasive networks. Instead of relying only on fixed infrastructures as the cloud, users' devices act as service providers for each other. They use pairwise contacts to…
Precise Human Mesh Recovery (HMR) with in-the-wild data is a formidable challenge and is often hindered by depth ambiguities and reduced precision. Existing works resort to either pose priors or multi-modal data such as multi-view or point…
Within the framework of a Device-to-Device (D2D) data offloading system for cellular networks, we propose a Content Delivery Management System (CDMS) in which the instant for transmitting a content to a requesting node, through a D2D…
With the increase in mobile traffic and the bandwidth demand, Device-to-Device (D2D) communication underlaying Long Term Evolution (LTE) networks has gained tremendous interest by the researchers, cellular operators and equipment…
In multicenter biomedical research, integrating data from multiple decentralized sites provides more robust and generalizable findings due to its larger sample size and the ability to account for the between-site heterogeneity. However,…
Out-Of-Distribution (OOD) detection has received broad attention over the years, aiming to ensure the reliability and safety of deep neural networks (DNNs) in real-world scenarios by rejecting incorrect predictions. However, we notice a…
Machine Intelligence (MI) technologies have revolutionized the design and applications of computational intelligence systems, by introducing remarkable scientific and technological enhancements across domains. MI can improve Internet of…
We introduce a new and increasingly relevant setting for distributed optimization in machine learning, where the data defining the optimization are unevenly distributed over an extremely large number of nodes. The goal is to train a…
Content dissemination networks are pervasive in todays Internet. Examples of content dissemination networks include peer-to-peer networks (P2P), content distribution networks (CDN) and information centric networks (ICN). In this paper, we…
With the emergence of smart cities, Internet of Things (IoT) devices as well as deep learning technologies have witnessed an increasing adoption. To support the requirements of such paradigm in terms of memory and computation, joint and…
We investigate the problem of spreading information contents in a wireless ad hoc network with mechanisms embracing the peer-to-peer paradigm. In our vision, information dissemination should satisfy the following requirements: (i) it…
Pervasive computing systems employ distributed and embedded devices in order to raise, communicate, and process data in an anytime-anywhere fashion. Certainly, its most prominent device is the smartphone due to its wide proliferation,…
Employing channel adaptive resource allocation can yield to a large enhancement in almost any performance metric of Device-to-Device (D2D) communications. We observe that D2D users are able to estimate their local Channel State Information…
In Internet of Things (IoT) driven smart-world systems, real-time crowd-sourced databases from multiple distributed servers can be aggregated to extract dynamic statistics from a larger population, thus providing more reliable knowledge for…
Device-to-Device (D2D) communication appears as a key communication paradigm to realizing the vision of Internet of Things (IoT) into reality by supporting heterogeneous objects interconnection in a large scale network. These devices may be…
Determining whether AI systems process information similarly to humans is central to cognitive science and trustworthy AI. While modern AI models can match human accuracy on standard tasks, such parity does not guarantee that their…