Related papers: Edge-Cloud Collaboration Enabled Video Service Enh…
Clustered federated Multitask learning is introduced as an efficient technique when data is unbalanced and distributed amongst clients in a non-independent and identically distributed manner. While a similarity metric can provide client…
This paper considers one-hop device-to-device (D2D)-assisted wireless caching networks that cache video files of varying quality levels, with the assumption that the base station can control the video quality but cache-enabled devices…
The combination of edge caching and coded multicasting is a promising approach to improve the efficiency of content delivery over cache-aided networks. The global caching gain resulting from content overlap distributed across the network in…
As users conveniently stream their favorite online videos, video request records are automatically stored by video content providers, which have a high chance of privacy leakage. Unfortunately, most existing privacy-enhancing approaches are…
Pervasive mobile AI applications primarily employ one of the two learning paradigms: cloud-based learning (with powerful large models) or on-device learning (with lightweight small models). Despite their own advantages, neither paradigm can…
Multimedia conferencing is the conversational exchange of multimedia content between multiple parties. It has a wide range of applications (e.g. Massively Multiplayer Online Games (MMOGs) and distance learning). Many multimedia conferencing…
Many IoT applications at the network edge demand intelligent decisions in a real-time manner. The edge device alone, however, often cannot achieve real-time edge intelligence due to its constrained computing resources and limited local…
Delivering an immersive experience to virtual reality (VR) users through wireless connectivity offers the freedom to engage from anywhere at any time. Nevertheless, it is challenging to ensure seamless wireless connectivity that delivers…
Federated learning has received great attention for its capability to train a large-scale model in a decentralized manner without needing to access user data directly. It helps protect the users' private data from centralized collecting.…
Efficient video processing is a critical component in many IoMT applications to detect events of interest. Presently, many window optimization techniques have been proposed in event processing with an underlying assumption that the incoming…
Edge Machine Learning (Edge ML), which shifts computational intelligence from cloud-based systems to edge devices, is attracting significant interest due to its evident benefits including reduced latency, enhanced data privacy, and…
By pre-fetching popular videos into the local caches of edge nodes, wireless edge caching provides an effective means of reducing repeated content deliveries. To meet the various viewing quality requirements of multimedia users, scalable…
Nowadays, video cameras are deployed in large scale for spatial monitoring of physical places (e.g., surveillance systems in the context of smart cities). The massive camera deployment, however, presents new challenges for analyzing the…
We introduce a Unity based benchmark XRFlux for evaluating Virtual Reality (VR) delivery systems using edge-cloud caching. As VR applications and systems progress, the need to meet strict latency and Quality of Experience (QoE) requirements…
Two main trends in today's internet are of major interest for video streaming services: most content delivery platforms coincide towards using adaptive video streaming over HTTP and new network architectures allowing caching at intermediate…
We propose a new scheme for increasing the throughput of video files in cellular communications systems. This scheme exploits (i) the redundancy of user requests as well as (ii) the considerable storage capacity of smartphones and tablets.…
This paper studies content caching in cloud-aided wireless networks where small cell base stations with limited storage are connected to the cloud via limited capacity fronthaul links. By formulating a utility (inverse of service delay)…
After the advent of the Internet of Things and 5G networks, edge computing became the center of attraction. The tasks demanding high computation are generally offloaded to the cloud since the edge is resource-limited. The Edge Cloud is a…
We propose a novel edge-assisted multi-user collaborative augmented reality framework in a large indoor environment. In Collaborative Augmented Reality, data communication that synchronizes virtual objects has large network traffic and high…
The rise of End-Edge-Cloud Collaboration (EECC) offers a promising paradigm for Artificial Intelligence (AI) model training across end devices, edge servers, and cloud data centers, providing enhanced reliability and reduced latency.…