PABO: Mitigating Congestion via Packet Bounce in Data Center Networks

In today's data center, a diverse mix of throughput-sensitive long flows and delay-sensitive short flows are commonly presented in shallow-buffered switches. Long flows could potentially block the transmission of delay-sensitive short flows, leading to degraded performance. Congestion can also be caused by the synchronization of multiple TCP connections for short flows, as typically seen in the partition/aggregate traffic pattern. While multiple end-to-end transport-layer solutions have been proposed, none of them have tackled the real challenge: reliable transmission in the network. In this paper, we fill this gap by presenting PABO -- a novel link-layer design that can mitigate congestion by temporarily bouncing packets to upstream switches. PABO's design fulfills the following goals: i) providing per-flow based flow control on the link layer, ii) handling transient congestion without the intervention of end devices, and iii) gradually back propagating the congestion signal to the source when the network is not capable to handle the congestion.Experiment results show that PABO can provide prominent advantage of mitigating transient congestions and can achieve significant gain on end-to-end delay

Air Force Institute of Technology Research Report 2003

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, and Engineering Physics

WLAN IEEE 802.11 a/b/g/n Indoor Coverage and Interference Performance Study

An adequate wireless network plan is needed to replace the traditional wired LANs. A full coverage WLAN offers the flexibility to relocate people and equipment or to reconfigure and add more wireless devices to the network. Usually, an IEEE 802.11 variant is chosen based on their bandwidth and their coverage area. However, sometimes there are special cases where the best technology is not the newest one. In addition, suitable positioning of access points (AP) is crucial to determine the efficiency of the network. E.g. in the case where devices are going to transmit at a maximum of 1 Mbps, any choice is acceptable, but when it is required higher performance, other factors must be considered. In this paper, we compare IEEE 802.11a/b/g/n indoor environments to know what technology is better. This comparison will be taken in terms of RSSI, coverage area, and measuring the interferences between channels. These key factors must be optimum to have high performance in the WLAN. This study will help the researchers to choose the best technology depending of their deploying case, and we will see study the best variant for indoors.Sendra, S.; García Pineda, M.; Turró Ribalta, C.; Lloret, J. (2011). WLAN IEEE 802.11 a/b/g/n Indoor Coverage and Interference Performance Study. International Journal On Advances in Networks and Services. 4(1):209-222. http://hdl.handle.net/10251/47035S2092224

A Bibliography of Northeast Historical Archaeology, 1987–2006

A bibliography of Northeast Historical Archaeology, 1987- 2006. A list of published articles, books, master’s theses and doctoral dissertation

Air Force Institute of Technology Research Report 2016

This Research Report presents the FY16 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs)

Air Force Institute of Technology Research Report 2010

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physic

Air Force Institute of Technology Research Report 2011

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Mapping (Dis-)Information Flow about the MH17 Plane Crash

Digital media enables not only fast sharing of information, but also disinformation. One prominent case of an event leading to circulation of disinformation on social media is the MH17 plane crash. Studies analysing the spread of information about this event on Twitter have focused on small, manually annotated datasets, or used proxys for data annotation. In this work, we examine to what extent text classifiers can be used to label data for subsequent content analysis, in particular we focus on predicting pro-Russian and pro-Ukrainian Twitter content related to the MH17 plane crash. Even though we find that a neural classifier improves over a hashtag based baseline, labeling pro-Russian and pro-Ukrainian content with high precision remains a challenging problem. We provide an error analysis underlining the difficulty of the task and identify factors that might help improve classification in future work. Finally, we show how the classifier can facilitate the annotation task for human annotators