University of Bremen

About: University of Bremen is a education organization based out in Bremen, Germany. It is known for research contribution in the topics: Population & Context (language use). The organization has 14563 authors who have published 37279 publications receiving 970381 citations. The organization is also known as: Universität Bremen.

Adaptive Congestion Control for Unpredictable Cellular Networks

Abstract: Legacy congestion controls including TCP and its variants are known to perform poorly over cellular networks due to highly variable capacities over short time scales, self-inflicted packet delays, and packet losses unrelated to congestion. To cope with these challenges, we present Verus, an end-to-end congestion control protocol that uses delay measurements to react quickly to the capacity changes in cellular networks without explicitly attempting to predict the cellular channel dynamics. The key idea of Verus is to continuously learn a delay profile that captures the relationship between end-to-end packet delay and outstanding window size over short epochs and uses this relationship to increment or decrement the window size based on the observed short-term packet delay variations. While the delay-based control is primarily for congestion avoidance, Verus uses standard TCP features including multiplicative decrease upon packet loss and slow start. Through a combination of simulations, empirical evaluations using cellular network traces, and real-world evaluations against standard TCP flavors and state of the art protocols like Sprout, we show that Verus outperforms these protocols in cellular channels. In comparison to TCP Cubic, Verus achieves an order of magnitude (> 10x) reduction in delay over 3G and LTE networks while achieving comparable throughput (sometimes marginally higher). In comparison to Sprout, Verus achieves up to 30% higher throughput in rapidly changing cellular networks.

Carbon Monoxide, Methane and Carbon Dioxide Columns Retrieved from SCIAMACHY by WFM-DOAS: Year 2003 Initial Data Set

Abstract: . The near-infrared nadir spectra measured by SCIAMACHY on-board ENVISAT contain information on the vertical columns of important atmospheric trace gases such as carbon monoxide (CO), methane (CH4), and carbon dioxide (CO2). The scientific algorithm WFM-DOAS has been used to retrieve this information. For CH4 and CO2 also column averaged mixing ratios (XCH4 and XCO2) have been determined by simultaneous measurements of the dry air mass. All available spectra of the year 2003 have been processed. We describe the algorithm versions used to generate the data (v0.4; for methane also v0.41) and show comparisons of monthly averaged data over land with global measurements (CO from MOPITT) and models (for CH4 and CO2). We show that elevated concentrations of CO resulting from biomass burning have been detected in reasonable agreement with MOPITT. The measured XCH4 is enhanced over India, south-east Asia, and central Africa in September/October 2003 in line with model simulations, where they result from surface sources of methane such as rice fields and wetlands. The CO2 measurements over the Northern Hemisphere show the lowest mixing ratios around July in qualitative agreement with model simulations indicating that the large scale pattern of CO2 uptake by the growing vegetation can be detected with SCIAMACHY. We also identified potential problems such as a too low inter-hemispheric gradient for CO, a time dependent bias of the methane columns on the order of a few percent, and a few percent too high CO2 over parts of the Sahara.