Related papers: A Performance Comparison of Network Simulators for…
This paper conducts a detailed simulation study of stateless anycast routing in a mobile wireless ad hoc network. The model covers all the fundamental aspects of such networks with a routing mechanism using a scheme of orientation-dependent…
The increasing trend on wireless-connected devices makes opportunistic networking a promising alternative to existing infrastructure-based networks. However, on these networks there is neither guarantee about the availability of the…
In this work, we consider the popular OPNET simulator as a tool for performance evaluation of algorithms operating in peer-to-peer (P2P) networks. We created simple framework and used it to analyse the flooding search algorithm which is a…
This paper presents a performance evaluation of Wireless Sensor Networks (WSN) based on Impulse Radio Ultra Wideband (IR-UWB) over a new simulation platform developed for this purpose. The simulation platform is built on an existing network…
Network-on-chip (NoC) is the most promising design paradigm for the interconnect architecture of a multiprocessor system-on-chip (MPSoC). On the downside, a NoC has a significant impact on the overall energy consumption of the system. NoC…
The devices designed for the Internet-of-Things encompass a large variety of distinct processor architectures, forming a highly heterogeneous zoo. In order to tackle this, we employ a simulator to estimate the performance of the…
In recent years, network function virtualization and a software defined focus has allowed networks to become flexible and extensible in ways not possible previously. Although network modeling tools such as NS-2, NS-3, and OMNet++ have been…
In this report, we provide a comparative analysis of different techniques for user intent classification towards the task of app recommendation. We analyse the performance of different models and architectures for multi-label classification…
Testing new, innovative technologies is a crucial task for safety and acceptance. But how can new systems be tested if no historical real-world data exist? Simulation provides an answer to this important question. Classical simulation tools…
Addressing the neural network-based optical channel equalizers, we quantify the trade-off between their performance and complexity by carrying out the comparative analysis of several neural network architectures, presenting the results for…
Understanding the complexity of biological neural networks like the human brain is one of the scientific challenges of our century. The organization of the brain can be described at different levels, ranging from small neural networks to…
Fitting network models to neural activity is an important tool in neuroscience. A popular approach is to model a brain area with a probabilistic recurrent spiking network whose parameters maximize the likelihood of the recorded activity.…
We present the architecture and analyze the applications of a metropolitan-scale quantum network that requires only limited hardware resources for end users. Using NetSquid, a quantum network simulation tool based on discrete events, we…
We present a clock-driven Spiking Neural Network simulator which is up to 3x faster than the state of the art while, at the same time, being more general and requiring less programming effort on both the user's and maintainer's side. This…
The field of parallel network simulation frameworks is evolving at a great pace. That is also because of the growth of Intelligent Transportation Systems (ITS) and the necessity for cost-effective large-scale trials. In this contribution,…
Simulation software is a powerful tool for robotics research, allowing the virtual representation of the real world. However with the rise of the Robot Operating System (ROS), there are new simulation software packages that have not been…
Peer-to-peer networks consist of thousands or millions of nodes that might join and leave arbitrarily. The evaluation of new protocols in real environments is many times practically impossible, especially at design and testing stages. The…
Network performance modeling is a field that predates early computer networks and the beginning of the Internet. It aims to predict the traffic performance of packet flows in a given network. Its applications range from network planning and…
Analog electrical networks have long been investigated as energy-efficient computing platforms for machine learning, leveraging analog physics during inference. More recently, resistor networks have sparked particular interest due to their…
A major step in developing robust wireless systems is to test and validate the design under a variety of circumstances. As wireless networks become more complex, it is impractical to perform testing on a real deployment. As a result, the…