Related papers: Functional Augmented State Transfer (FAST) Archite…
The collaborative research project 6G-ANNA develops concepts for the 6G radio access network (RAN) architecture and technology components. Previous RAN generations have become inherently more complex and reach their limits in handling…
This paper considers reliable data transfer in a high-speed network (HSN) in which the per-connection capacity is very large. We focus on sliding window protocols employing selective repeat for reliable data transfer and study two…
We address the efficiency issue for the construction of a deep graph neural network (GNN). The approach exploits the idea of representing each input graph as a fixed point of a dynamical system (implemented through a recurrent neural…
In the current era of Big Data, data engineering has transformed into an essential field of study across many branches of science. Advancements in Artificial Intelligence (AI) have broadened the scope of data engineering and opened up new…
Deep convolutional neural networks, assisted by architectural design strategies, make extensive use of data augmentation techniques and layers with a high number of feature maps to embed object transformations. That is highly inefficient…
The deployment of deep neural networks in real-world applications is mostly restricted by their high inference costs. Extensive efforts have been made to improve the accuracy with expert-designed or algorithm-searched architectures.…
With the continued growth in field-programmable gate array (FPGA) capacity and their incorporation into new environments such as datacenters, we have witnessed the introduction of a new class of reconfigurable acceleration devices (RADs)…
Although the cloud has reached a state of robustness, the burden of using its resources falls on the shoulders of programmers who struggle to keep up with ever-growing cloud infrastructure services and abstractions. As a result, state…
The sharing of mobile network infrastructure has become a key topic with the introduction of 5G due to the high costs of deploying such infrastructures, with neutral host models coupled with features such as network function virtualization…
Traditional Smooth Transition Autoregressive (STAR) models offer an effective way to model these dynamics through smooth regime changes based on specific transition variables. In this paper, we propose a novel approach by drawing an analogy…
Recently, Neural Architecture Search (NAS) methods are introduced and show impressive performance on many benchmarks. Among those NAS studies, Neural Architecture Transformer (NAT) aims to improve the given neural architecture to have…
We propose CFS, a distributed file system for large scale container platforms. CFS supports both sequential and random file accesses with optimized storage for both large files and small files, and adopts different replication protocols for…
Network functions virtualization (NFV) allows operators to employ NF chains to realize custom policies, and dynamically add instances to meet demand or for failover. NFs maintain detailed per- and cross-flow state which needs careful…
Selecting the appropriate communication protocol is crucial for optimizing the performance, scalability, and user experience of web applications. In the diverse ecosystem of web technologies, various protocols like RESTful APIs, gRPC,…
Despite constant improvements in efficiency, today's data centers and networks consume enormous amounts of energy and this demand is expected to rise even further. An important research question is whether and how fog computing can curb…
Pattern plays a vital role in software architecture and it is a general reusable solution to commonly occurring problem. Software architecture of a system is the set of structures needed to reason about the system, which comprise software…
The problem of data augmentation in feature space is considered. A new architecture, denoted the FeATure TransfEr Network (FATTEN), is proposed for the modeling of feature trajectories induced by variations of object pose. This architecture…
Data center applications require the network to be scalable and bandwidth-rich. Current data center network architectures often use rigid topologies to increase network bandwidth. A major limitation is that they can hardly support…
Non-differentiable and constrained optimization play a key role in machine learning, signal and image processing, communications, and beyond. For high-dimensional minimization problems involving large datasets or many unknowns, the…
Software as a Service cloud computing model favorites the Multi-Tenancy as a key factor to exploit economies of scale. However Multi-Tenancy present several disadvantages. Therein, our approach comes to assign instances to multi-tenants…