☆ FBS-Radar: Uncovering Fake Base
Stations at Scale in the Wild
✎ Yet another key component of
FBS-Radar precisely identifies malicious fake base
stations (FBSes) and accurately geolocates FBSes based on
crowdsourced data of nearly 100 million users. It protects users
from millions of spam and fraud SMS messages per day, and has
helped the Ministry of Public Security of China arrest hundreds
of FBS operators. Also, we have made a
public website that shows the current locations of detected
FBSes in real time.
Cross-App Cellular Traffic Optimization with Baidu TrafficGuard
✎ As a key component of
Baidu TrafficGuard is a third-party mobile traffic proxy
widely deployed for Android 4.0+ devices in China. It
effectively reduces cellular traffic using a network-layer VPN
that connects a client-side proxy to a centralized traffic
processing cloud. Most importantly, it works transparently
across heterogeneous applications, so is not constrained
to any specific app.
Offline Downloading in China: A Comparative Study
✎ Examining two typical implementations of "offline
downloading" in China: the cloud-based approach
and the smart AP (access point, also known as home
router) based approach. Driven by the
measurement findings, we design and implement an intelligent
middleware called ODR (Offline Downloading Redirector) to help
users achieve the best expected performance.
Towards Network-level Efficiency
for Cloud Storage Services
✎ Addressing a simple yet critical question: Is
the current data sync traffic of cloud storage services
Based on real-world traces and comprehensive experiments, we
discover that a considerable portion of the data sync traffic is
in a sense wasteful, and can be effectively avoided or
significantly reduced via carefully designed data sync
Efficient Batched Synchronization
for Cloud Storage Services
as a middleware between the user's file storage system and a
cloud storage application (e.g. Dropbox), our proposed UDS (i.e.
update-batched delayed sync) mechanism properly batches updates
from clients to minimize the "traffic overuse problem",
while preserving the rapid file synchronization that users
expect from cloud storage services.
scheduling cloud bandwidth into end host peers to
maximize the bandwidth multiplier effect with a fine-grained
model and fast-convergent iterative algorithm ("FIFA").
This work is simulated on the Xuanfeng system trace and is implemented on the
✎ Bridging the format and resolution gap between Internet
videos and mobile
devices by utilizing an intermediate cloud platform. The user
only sends his video request to
Cloud Transcoder which does everything else:
download, transcode, cache, transfer back, and so forth.
✎ Achieving high-quality content distribution (especially for
unpopular videos) by using cloud utilities to guarantee the data
health and enhance the data transfer rate.
Please try the large-scale Xuanfeng Cloud Download
✎ Dynamically tracking and integrating various third-party servers,
contents and data transfer protocols all over the Internet into
a large, open and federated P2SP (peer-to-server/peer) platform,
so as to accelerate the content distribution from servers to
clients and among peer swarms. It also facilitates
load-balancing among the involved servers.
Please try the large-scale Xuanfengsystem!