Ensuring the freshness of client data is a fundamental problem for applications that rely on cloud infrastructure to store data and mediate sharing. Thialfi is a notification service developed at Google to simplify this task. Thialfi supports applications written in multiple programming languages and running on multiple platforms, e.g., browsers, phones, and desktops. Applications register their interest in a set of shared objects and receive notifications when those objects change. Thialfi servers run in multiple Google data centers for availability and replicate their state asynchronously. Thialfi's approach to recovery emphasizes simplicity: all server state is soft, and clients drive recovery and assist in replication. A principal goal of our design is to provide a straightforward API and good semantics despite a variety of failures, including server crashes, communication failures, storage unavailability, and data center failures.

Privacy -- the protection of information from unauthorized disclosure -- is increasingly scarce on the Internet. The lack of privacy is particularly true for popular peer-to-peer data sharing applications such as BitTorrent where user behavior is easily monitored by third parties. Anonymizing overlays such as Tor and Freenet can improve user privacy, but only at a cost of substantially reduced performance. Most users are caught in the middle, unwilling to sacrifice either privacy or performance.

Distributed hash tables (DHTs) provide scalable, key-based lookup of objects in dynamic network environments. Although DHTs have been studied extensively from an analytical perspective, only recently have wide deployments enabled empirical examination. This paper reports measurements of the Azureus BitTorrent client's DHT, which is in active use by more than 1 million nodes on a daily basis. The Azureus DHT operates on untrusted, unreliable end-hosts, offering a glimpse into the implementation challenges associated with making structured overlays work in practice. Our measurements provide characterizations of churn, overhead, and performance in this environment. We leverage these measurements to drive the design of a modified DHT lookup algorithm that reduces median DHT lookup time by an order of magnitude for a nominal increase in overhead.

The study of physical models for knots has recently received much interest in the mathematics community. In this paper, we consider the ropelength model, which considers knots tied in an idealized rope. This model is interesting in pure mathematics, and has been applied to the study of a variety of problems in the natural sciences as well. Modeling and visualizing the tightening of knots in this idealized rope poses some interesting challenges in computer graphics. In particular, self-contact in a deformable rope model is a difficult problem which cannot be handled by standard techniques. In this paper, we describe a solution based on reformulating the contact problem and using constrained-gradient techniques from nonlinear optimization. The resulting animations reveal new properties of the tightening flow and provide new insights into the geometric structure of tight knots and links.