Related papers: A Light-Weight Forwarding Plane for Content-Centri…
The growing disparity between computational power and on-chip communication bandwidth is a critical bottleneck in modern Systems-on-Chip (SoCs), especially for data-parallel workloads like AI. Efficient point-to-multipoint (P2MP) data…
Named data networking is one of the recommended {\color{red}architectures} for the future of the Internet. In this communication architecture, the content name is used instead of the IP address. To achieve this purpose, a new data structure…
Content-Centric Networking (CCN) is an emerging network architecture designed to overcome limitations of the current IP-based Internet. One of the fundamental tenets of CCN is that data, or content, is a named and addressable entity in the…
Deep learning models have become popular in the analysis of tabular data, as they address the limitations of decision trees and enable valuable applications like semi-supervised learning, online learning, and transfer learning. However,…
Today's networks are used primarily to move content. To cater to this requirement Information Centric Networks (ICN) were introduced. One of the main architectures of ICN is Content Centric Networking (CCN) and its derivative, Named Data…
SMART NoC, which transmits unconflicted flits to distant processing elements (PEs) in one cycle through the express bypass, is a high-performance NoC design proposed recently. However, if contention occurs, flits with low priority would not…
This paper proposes Navigo, a location based packet forwarding mechanism for vehicular Named Data Networking (NDN). Navigo takes a radically new approach to address the challenges of frequent connectivity disruptions and sudden network…
One of the most discussed features offered by Information-centric Networking (ICN) architectures is the ability to support packet-level caching at every node in the network. By individually naming each packet, ICN allows routers to turn…
In-network caching is a central aspect of Information-Centric Networking (ICN). It enables the rapid distribution of content across the network, alleviating strain on content producers and reducing content delivery latencies. ICN has…
Early-exit deep neural networks enable adaptive inference by terminating computation when sufficient confidence is achieved, reducing cost for edge AI accelerators in resource-constrained settings. Existing methods, however, rely on…
Social network companies maintain complete visibility and ownership of the data they store. However users should be able to maintain full control over their content. For this purpose, we propose WARP, an architecture based upon…
In Named Data Networking (NDN), there is a need for routing protocols to populate Forwarding Information Base (FIB) tables so that the Interest messages can be forwarded. To populate FIBs, clients and routers require some routing…
Today's Internet is heavily used for multimedia streaming from cloud backends, while the Internet of Things (IoT) reverses the traditional data flow, with high data volumes produced at the network edge. Information Centric Networking (ICN)…
A content can be replicated in more than one node, in Information Centric Networks (ICNs). Thus, more than one path can be followed to reach the same content, and it is necessary to decide the interface(s) to be selected in every network…
A fog-aided wireless network architecture is studied in which edge-nodes (ENs), such as base stations, are connected to a cloud processor via dedicated fronthaul links, while also being endowed with caches. Cloud processing enables the…
In this article, we leverage Network Function Virtualization (NFV) and Multi-Access Edge Computing (MEC) technologies, proposing a system which integrates ICN (Information-Centric Network) with CDN (Content Delivery Network) to provide an…
As in-vehicle communication becomes more complex, the automotive community is exploring various architectural options such as centralized and zonal architectures for their numerous benefits. Zonal architecture reduces the wiring cost by…
Convolutional Neural Networks (CNNs), a prominent type of Deep Neural Networks (DNNs), have emerged as a state-of-the-art solution for solving machine learning tasks. To improve the performance and energy efficiency of CNN inference, the…
Information-centric networking (ICN) is one of the promising solutions that cater to the challenges of IP-based networking. ICN shifts the IP-based access model to a data-centric model. Named Data Networking (NDN) is a flexible ICN…
A core feature of Content-Centric Networking (CCN) is opportunistic content caching in routers. It enables routers to satisfy content requests with in-network cached copies, thereby reducing bandwidth utilization, decreasing congestion, and…