Detecting pulsing denial-of-service attacks with nondeterministic attack intervals

2008-2009 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

WLC35-4: Optimizing Energy Efficiency in Polling-Based Wireless Networks with Stability Constraints

In this paper we consider the problem of minimizing the total energy for all devices in a wireless infrastructure network. The wireless devices use transmission power control and power saving mode to conserve energy. In particular we consider a polling-based MAC protocol which determines optimal power schedules (therefore the transmission rates) for all devices. Moreover, we have considered two grouping schedules: Phase Grouping (PG) and Mobile Grouping (MG). Through an iterative algorithm, we compute and compare the suboptimal energy consumptions for the two schedules based on the number of bits transmitted per joule of energy. Extensive results show that the MG schedule is much more energy efficient than the PG schedule, and the main sources of energy saving come from the reception and mode transition phases. Moreover, we evaluate the impact of an uncooperative user, who does not follow the optimal power allocation, on its own and others' energy-delay performance.Department of ComputingRefereed conference pape

Method for measurement of network path capacity with minimum delay difference

US8531952; US8531952 B2; US8531952B2; US8,531,952; US 8,531,952 B2; 8531952; Appl. No. 12/626,965US2013-2014 > Other Outputs > Patents grantedVersion of Recor

Method for measurement of asymmetric network capacities

US8885473; US8885473 B2; US8885473B2; US8,885,473; US 8,885,473 B2; 8885473; Appl. No. 13/688,464US2014-2015 > Other Outputs > Patents grantedVersion of Recor

Editorial : Signal processing applications in network intrusion detection systems: editorial

Version of RecordPublishe

Time to measure the Pi

The Raspberry Pi platform is increasingly being used for network measurement due to its low cost, ease of de-ployment, and ability to run Linux. Timestamps are a critical part of measurement data, yet the suitability of the Pi for timing has not been established. We use ref-erence hardware to characterize the Pi's STC hardware counter, and to evaluate its performance when paired with a low cost yet powerful GPS 'hat'. We find that the platform can support timing adequate for most mea-surement purposes, but with some caveats

ACM CoNEXT 2016 Student Workshop

12th ACM Conference on Emerging Networking Experiments and Technologies, ACM CoNEXT 2016, Irvine, US, 12-15 December 2016The ACMCoNEXT 2016 StudentWorkshop is held in Irvine, California, USA on December 12, 2016 and co-located with the ACM 12th International Conference on emerging Net- working Experiments and Technologies (CoNEXT 2016). The main objective of the workshop is to provide a platform for graduate students in the area of computer networks and communications to present their ongoing research eorts. The workshop is also a unique opportunity for students to network with other junior researchers as well as more expe- rienced ones, receive constructive feedback, guidance, tips, and learn about cutting-edge research problems being tack- led by the community. We have constructed an exciting program of 24 refereed presentations and posters, and an invited keynote talk (by Prof. Lixia Zhang, UCLA) that will give participating students an opportunity to hear from a senior researcher.Department of Computin

Centralized PSM: An AP-centric power saving Mode for 802.11 infrastructure networks

Energy management in a wireless LAN is an important problem, as the viability of wireless devices depends very much on their battery life. In this paper, we propose a centralized power saving mode (C-PSM), an AP-centric PSM for 802.11 infrastructure networks. Having the AP select optimal PSM parameters, such as the beacon and listen intervals, CPSM is able to maximize the total energy efficiency for all clients. Moreover, C-PSM provides a first-wake-up schedule to further increase the energy efficiency by reducing clients' simultaneous wake-ups. Extensive simulation experiments show that C-PSM outperforms the standard PSM by a very significant margin. In our set of experiments, C-PSM reduces power consumption and increases energy efficiency by as much as 76% and 320%, respectively. As a side benefit, C-PSM also decreases the frame buffering delay at the AP by 88%. The wake-up schedule can save clients' energy consumption by 22% at most. Moreover, the improvement increases with the number of clients.Department of ComputingRefereed conference pape