Tracking the Evolution and Diversity in Network Usage of Smartphones

ABSTRACT We analyze the evolution of smartphone usage from a dataset obtained from three, 15-day-long, user-side, measurements with over 1500 recruited smartphone users in the Greater Tokyo area from 2013 to 2015. This dataset shows users across a diverse range of networks; cellular access (3G to LTE), WiFi access (2.4 to 5GHz), deployment of more public WiFi access points (APs), as they use diverse applications such as video, file synchronization, and major software updates. Our analysis shows that smartphone users select appropriate network interfaces taking into account the deployment of emerging technologies, their bandwidth demand, and their economic constraints. Thus, users show diversity in both how much traffic they send, as well as on what networks they send it. We show that users are gradually but steadily adopting WiFi at home, in offices, and public spaces over these three years. The majority of light users have been shifting their traffic to WiFi. Heavy hitters acquire more bandwidth via WiFi, especially at home. The percentage of users explicitly turning off their WiFi interface during the day decreases from 50% to 40%. Our results highlight that the offloading environment has been improved during the three years, with more than 40% of WiFi users connecting to multiple WiFi APs in one day. WiFi offload at offices is still limited in our dataset due to a few accessible APs, but WiFi APs in public spaces have been an alternative to cellular access for users who request not only simple connectivity but also bandwidth-consuming applications such as video streaming and software updates. Categories and Subject Descriptors General Terms Measurement Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Two Homologous Putative Protein Tyrosine Phosphatases, OsPFA-DSP2 and AtPFA-DSP4, Negatively Regulate the Pathogen Response in Transgenic Plants

Protein phosphatases, together with protein kinases, regulate protein phosphorylation and dephosphorylation, and play critical roles in plant growth and biotic stress responses. However, little is known about the biological functions of plant protein tyrosine dual-specificity phosphatase (PFA-DSP) in biotic stresses. Here, we found that OsPFA-DSP2 was mainly expressed in calli, seedlings, roots, and young panicles, and localized in cytoplasm and nucleus. Ectopic overexpression of OsPFA-DSP2 in rice increased sensitivity to Magnaporthe grisea (M. grisea Z1 strain), inhibited the accumulation of hydrogen peroxide (H2O2) and suppressed the expression of pathogenesis-related (PR) genes after fungal infection. Interestingly, transgenic Arabidopsis plants overexpressing AtPFA-DSP4, which is homologous to OsPFA-DSP2, also exhibited sensitivity to Pseudomonas syringae pv. tomato DC3000 (Pst DC3000), reduced accumulation of H2O2 and decreased photosynthesic capacity after infection compared with Col-0. These results indicate that OsPFA-DSP2 and AtPFA-DSP4 act as negative regulators of the pathogen response in transgenic plants

Poptrie: A Compressed Trie with Population Count for Fast and Scalable Software IP Routing Table Lookup

ABSTRACT Internet of Things leads to routing table explosion. An inexpensive approach for IP routing table lookup is required against ever growing size of the Internet. We contribute by a fast and scalable software routing lookup algorithm based on a multiway trie, called Poptrie. Named after our approach to traversing the tree, it leverages the population count instruction on bit-vector indices for the descendant nodes to compress the data structure within the CPU cache. Poptrie outperforms the state-of-the-art technologies, Tree BitMap, DXR and SAIL, in all of the evaluations using random and real destination queries on 35 routing tables, including the real global tier-1 ISP's full-route routing table. Poptrie peaks between 174 and over 240 Million lookups per second (Mlps) with a single core and tables with 500-800k routes, consistently 4-578% faster than all competing algorithms in all the tests we ran. We provide the comprehensive performance evaluation, remarkably with the CPU cycle analysis. This paper shows the suitability of Poptrie in the future Internet including IPv6, where a larger route table is expected with longer prefixes

Poptrie: A Compressed Trie with Population Count for Fast and Scalable Software IP Routing Table Lookup

ABSTRACT Internet of Things leads to routing table explosion. An inexpensive approach for IP routing table lookup is required against ever growing size of the Internet. We contribute by a fast and scalable software routing lookup algorithm based on a multiway trie, called Poptrie. Named after our approach to traversing the tree, it leverages the population count instruction on bit-vector indices for the descendant nodes to compress the data structure within the CPU cache. Poptrie outperforms the state-of-the-art technologies, Tree BitMap, DXR and SAIL, in all of the evaluations using random and real destination queries on 35 routing tables, including the real global tier-1 ISP's full-route routing table. Poptrie peaks between 174 and over 240 Million lookups per second (Mlps) with a single core and tables with 500-800k routes, consistently 4-578% faster than all competing algorithms in all the tests we ran. We provide the comprehensive performance evaluation, remarkably with the CPU cycle analysis. This paper shows the suitability of Poptrie in the future Internet including IPv6, where a larger route table is expected with longer prefixes