Topic
Testbed
About: Testbed is a research topic. Over the lifetime, 10858 publications have been published within this topic receiving 147147 citations. The topic is also known as: test bed.
Papers published on a yearly basis
Papers
More filters
••
TL;DR: The proposed algorithm gradually balances the AP loads for the available multiple bit rate choices in a distributed manner and shows the improvement of the fairness via computer simulation.
Abstract: With the development of IEEE 802.11 MAC (medium access control) protocols, efficient utilization of wireless local area networks (WLANs) has become a very important issue. In typical IEEE 802.11 networks, the association between mobile users (MUs) and access point (AP) is based on the signal strength information. As a result, it often results in the extremely unfair bandwidth allocation among MUs. In this paper, we propose a distributed association algorithm to achieve load balancing among the APs. The proposed algorithm gradually balances the AP loads for the available multiple bit rate choices in a distributed manner. We analyze the stability and overhead of the proposed algorithm, and show the improvement of the fairness via computer simulation. Additionally, we have implemented a prototype on a testbed to prove its feasibility.
75 citations
••
TL;DR: A description is given of five testbeds developed to examine gigabit applications and network technologies: Aurora, Blanca, Casa, Nectar, and Vistanet.
Abstract: A description is given of five testbeds developed to examine gigabit applications and network technologies: Aurora, Blanca, Casa, Nectar, and Vistanet. Aurora is an experimental wide-area network testbed whose main objective is to explore and evaluate technologies for phase three of the proposed gigabit National Research and Education Network. The goals of the Blanca network research program are to develop technologies supporting gigabit/second networks, to develop programming tools supporting advanced network-based applications, and to explore the relationships between network technology paradigms and application requirements. The intent of the Casa testbed is to demonstrate that distributed supercomputing using wide-area high-speed networks can provide new levels of computational resources for leading-edge scientific problems. For the Nectar testbed project, a gigabit/second or higher experimental network will be developed to connect a variety of high-performance hosts. The Vistanet research project is intended to help determine whether networks based on emerging public-network standards will satisfy the goals of the National Research and Education Network and to provide information on specifications for those standards.
75 citations
••
TL;DR: This paper identifies the complexity of the optimal traffic awareness in 5G C-RAN and design a framework for traffic-aware energy optimization and demonstrates that this framework results in almost 25% daily energy savings and 35% increased energy efficiency with a negligible overhead.
Abstract: Next generation 5G wireless networks envision innovative radio technologies for ultra dense deployment with improved coverage and higher data rates. However, the deployment of ultra dense 5G networks, with relatively smaller cells, raises significant challenges in network energy consumption. Emerging green cloud radio access networks (C-RANs) are providing assurance of energy efficient cellular operations for reduction of both greenhouse emissions and operators’ energy bill. Cellular traffic dynamics play a significant role in efficient network energy management. In this paper, we first identify the complexity of the optimal traffic awareness in 5G C-RAN and design a framework for traffic-aware energy optimization. The virtual base station cluster (VBSC) of C-RAN exploits an information theoretic approach to model and analyze the uncertainty of cellular traffic, captured by remote radio heads (RRH). Subsequently, using an online, stochastic game theoretic algorithm, the VBS instances optimize and learn the cellular traffic patterns. Efficient learning makes the C-RAN aware of the near-future traffic. Traffic awareness helps in selective switching of a subset of RRHs, thus reducing the overall energy consumption. Our VBS prototype implementation, testbed experiments, and simulation results, performed with actual cellular traffic traces, demonstrate that our framework results in almost 25% daily energy savings and 35% increased energy efficiency with a negligible overhead.
75 citations
••
TL;DR: A data-driven IDS is designed by analyzing the link load behaviors of the Road Side Unit in the IoV against various attacks leading to the irregular fluctuations of traffic flows and a deep learning architecture based on the Convolutional Neural Network is designed to extract the features of link loads, and detect the intrusion aiming at RSUs.
Abstract: As an industrial application of Internet of Things (IoT), Internet of Vehicles (IoV) is one of the most crucial techniques for Intelligent Transportation System (ITS), which is a basic element of smart cities. The primary issue for the deployment of ITS based on IoV is the security for both users and infrastructures. The Intrusion Detection System (IDS) is important for IoV users to keep them away from various attacks via the malware and ensure the security of users and infrastructures. In this paper, we design a data-driven IDS by analyzing the link load behaviors of the Road Side Unit (RSU) in the IoV against various attacks leading to the irregular fluctuations of traffic flows. A deep learning architecture based on the Convolutional Neural Network (CNN) is designed to extract the features of link loads, and detect the intrusion aiming at RSUs. The proposed architecture is composed of a traditional CNN and a fundamental error term in view of the convergence of the backpropagation algorithm. Meanwhile, a theoretical analysis of the convergence is provided by the probabilistic representation for the proposed CNN-based deep architecture. We finally evaluate the accuracy of our method by way of implementing it over the testbed.
75 citations
••
TL;DR: This demonstration will be the presentation of a new testbed for joint activity of heterogeneous teams, similar to the classic AI planning problem of Blocks World extended into what the authors are calling Blocks World for Teams (BW4T).
Abstract: This demonstration will be the presentation of a new testbed for joint activity. The domain for this demonstration will be similar to the classic AI planning problem of Blocks World (BW) extended into what we are calling Blocks World for Teams (BW4T). By teams, we mean at least two, but usually more members. Additionally, we do not restrict the membership to artificial agents, but include and in fact expect human team members. Study of joint activity of heterogeneous teams is the main function of the BW4T testbed.
74 citations