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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
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Proceedings ArticleDOI
12 Jun 2011
TL;DR: Main focus in this paper compared to previous work is to address the perspective of both users and operators on how to experiment or respectively operate a WSN testbed based on WISEBED technology.
Abstract: Current surveys and forecast predict that the number of wireless devices is going to increase tremendously. These wireless devices can be computers of all kinds, notebooks, netbooks, Smartphones and sensor nodes that evolve into real-world scenarios forming a “Real-World-Internet” in the future. In our work we focus on the Future Internet with small battery driven devices forming the “Internet of Things”. In recent networking research, testbeds gain more and more attention, especially in the context of Future Internet and wireless sensor networks (WSNs). This development stems from the fact that simulations and even emulations are not considered sufficient for the deployment of new technologies as they often lack realism. Experimental research on testbeds is a promising alternative that can help to close the gap. The deployment of testbeds is challenging and user and operator requirements need to be considered carefully. Therefore, the goal is to design an architecture that allows operators of WSN testbeds to offer numerous users access to their testbeds in a standardized flexible way that matches these requirements. In this paper we first identify some of the requirements, then introduce the architecture and general concepts of our WISEBED approach and show how this architecture meets the requirements of both groups. We give an overview of existing WISEBED-compatible WSN testbeds that can be used for experimentation today. Main focus in this paper compared to previous work is to address the perspective of both users and operators on how to experiment or respectively operate a WSN testbed based on WISEBED technology.

48 citations

28 Oct 2005
TL;DR: The National Weather Radar Testbed (NWRT) is a 10-cm phased array radar for use in studying and developing faster and more accurate warning, analysis and forecast techniques for severe and hazardous weather as mentioned in this paper.
Abstract: A new national asset for weather radar research is now operational in Norman, Oklahoma. The National Weather Radar Testbed (NWRT) is a 10-cm phased array radar for use in studying and developing faster and more accurate warning, analysis and forecast techniques for severe and hazardous weather. As reported at previous Interactive Information Processing Systems (IIPS) conferences, Forsyth, (2002, 2003), the NWRT was developed by a government/university/ industry team consisting of the National Oceanic and Atmospheric Administration’s National Severe Storms Laboratory, the Tri-Agencies’ (Department of Commerce, Defense & Transportation) Radar Operations Center (ROC), the United States Navy’s Office of Naval Research, Lockheed Martin Corporation, the University of Oklahoma’s Electrical Engineering Department and School of Meteorology, the Oklahoma State Regents for Higher Education, and the Federal Aviation Administration’s William J. Hughes Technical Center. The NWRT uses a converted Navy SPY-1 phased array antenna system, thus providing the first phased array radar available on a full-time basis to the meteorological research community. The NWRT became operational in September 2003, but problems with the velocity channel delayed initial data collection until May 2004. Our initial efforts have focused on ensuring that the data is of high quality. Qualitative comparisons with a WSR-88D (KTLX-Twin Lakes, OK) appear to be similar. In this paper, we will describe the data quality improvements, recent upgrades, future plans and present some examples of the first tornadic data set obtained with this new national facility.

48 citations

Proceedings ArticleDOI
06 Jul 2003
TL;DR: The MSM-CDN provides a new platform for media delivery, and the testbed prototype that was built based on these architectural principles is described, and a number of research directions related to the MSM- CDN are described.
Abstract: Delivering media to large numbers of mobile users presents challenges due to the stringent requirements of streaming media, mobility, wireless, and scaling to support large numbers of users. This paper presents a mobile streaming media content delivery network (MSM-CDN) designed to overcome these challenges. The MSM-CDN is a network overlay consisting of overlay servers on top of the existing network; these overlay servers are control points that facilitate end-to-end media delivery and mid-network media services. This paper presents an overview of the MSM-CDN system architecture, and describes the testbed prototype that we built based on these architectural principles. The MSM-CDN provides a new platform for media delivery, and we describe a number of research directions related to the MSM-CDN.

48 citations

Journal ArticleDOI
TL;DR: An integrated heterogeneous networking scheme for multi-access edge computing and fiber-wireless access networks that uses network virtualization to achieve the dynamic orchestration of the network, storage, and computing resources to meet diverse application demands is proposed.
Abstract: With the widespread use of smart mobile devices, the exponential growth of mobile Internet traffic and newly emerging services, such as Internet of Things, virtual reality/augmented reality, and serious games, the network performance requirements for delay and bandwidth are increasing. The inherent long-distance propagation and possible network congestion of mobile cloud computing may lead to excessive latency, which cannot satisfy the new delay-sensitive mobile applications. The proximity of edge computing provides the possibility of low-latency access and raises increasing interest from non-mobile operators; therefore, edge computing faces a variety of access network technologies, including wired (fixed) and wireless (mobile) access. In this paper, we propose an integrated heterogeneous networking scheme for multi-access edge computing and fiber-wireless access networks that uses network virtualization to achieve the dynamic orchestration of the network, storage, and computing resources to meet diverse application demands. The global view and centralized control of the entire network and the unified scheduling of the resources in the scheme anticipate the convergence of various types of access networks and the edge cloud. The multipath transmission of the service flows is further combined as an instance of integrated edge cloud networking. An experimental testbed is established in the laboratory, and the performance of the multi-access edge computing and networking is evaluated to verify the feasibility and effectiveness of the scheme. The results demonstrate that the scheme can effectively improve the network performance.

48 citations

Journal ArticleDOI
TL;DR: Numerical results show that near-optimal RWA can be obtained with the ML approach, while reducing computational time up to 93% in comparison to a traditional optimization approach based on integer linear programming.
Abstract: Recently, machine learning (ML) has attracted the attention of both researchers and practitioners to address several issues in the optical networking field. This trend has been mainly driven by the huge amount of available data (i.e., signal quality indicators, network alarms, etc.) and to the large number of optimization parameters which feature current optical networks (such as, modulation format, lightpath routes, transport wavelength, etc.). In this paper, we leverage the techniques from the ML discipline to efficiently accomplish the routing and wavelength assignment (RWA) for an input traffic matrix in an optical WDM network. Numerical results show that near-optimal RWA can be obtained with our approach, while reducing computational time up to 93% in comparison to a traditional optimization approach based on integer linear programming. Moreover, to further demonstrate the effectiveness of our approach, we deployed the ML classifier into an ONOS-based software defined optical network laboratory testbed, where we evaluate the performance of the overall RWA process in terms of computational time.

48 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023917
20222,046
2021499
2020590
2019693
2018639