2,370 research outputs found
Measuring the Internet during Covid-19 to Evaluate Work-from-Home
The Covid-19 pandemic has radically changed our lives. Under different
circumstances, people react to it in various ways. One way is to work-from-home
since lockdown has been announced in many regions around the world. For some
places, however, we don't know if people really work from home due to the lack
of information. Since there are lots of uncertainties, it would be helpful for
us to understand what really happen in these places if we can detect the
reaction to the Covid-19 pandemic. Working from home indicates that people have
changed the way they interact with the Internet. People used to access the
Internet in the company or at school during the day. Now it is more likely that
they access the Internet at home in the daytime. Therefore, the network usage
changes in one place can be used to indicate if people in this place actually
work from home. In this work, we reuse and analyze Trinocular outages data
(around 5.1M responsive /24 blocks) over 6 months to find network usage changes
by a new designed algorithm. We apply the algorithm to sets of /24 blocks in
several cities and compare the detected network usage changes with real world
covid-19 events to verify if the algorithm can capture the changes reacting to
the Covid-19 pandemic. By applying the algorithm to all measurable /24 blocks
to detect network usages changes, we conclude that network usage can be an
indicator of the reaction to the Covid-19 pandemic
DNA Mapping Algorithms: The DNA Simulator
This report documents the intent and use of a suite of programs for simulating the production of DNA restriction fragment data, as might come from the biological laboratory doing work in DNA mapping. This suite includes programs for (a) creating a random strand of DNA, (b) creating random clones given a strand of DNA, (c) taking a clone and applying a restriction enzyme to create restriction fragments, and (d) creating a nucleotide map of how the clones relate to one another within the original DNA strand. Besides this fundamental software, there are a number of a programs for introducing different forms of random error (nre, nce) intro the restriction fragments produced, and aggregating and filtering the clones in different ways to select those with appropriate properties
Energy efficient network reconfiguration for mostlyoff sensor networks
Abstract — A new class of sensor network applications are mostly off. Exemplified by Intel’s FabApp, in these applications the network alternates between being off for hours or weeks, then activating to collect data for a few minutes. While configuration of traditional sensornet applications is occasional and so need not be optimized, these applications may spend half their time while awake configuring, so they require new approaches to quickly restart after a long downtime, in effect, “sensor network suspend and resume”. While there are many network services that may need to be restarted, this paper focuses on the key question of when the network can determine that all nodes are now awake and ready to interact. Current resume approaches assume worst-case clock drift and so must conservatively take minutes to reconfigure after a month-long sleep. We propose two energy efficient reconfiguration protocols to address this challenge. The first approach is low-power listening with flooding, where the network restarts quickly by flooding a control message as soon as one node can determine the whole network is up. The second protocol uses local update with suppression, where nodes only notify their one-hop neighbors about the network state, avoiding the cost of flooding. Both protocols are fully distributed algorithms. Through analysis and simulations, we show that both protocols are more energy efficient than current approaches. Flooding works best in sparse networks with 6 neighbors or less, while local update with suppression works best in dense networks (more than 6 neighbors). I
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