Wu-chang Feng

Panoptes: scalable low-power video sensor networking technologies

Video-based sensor networks can provide important visual information in a number of applications including: environmental monitoring, health care, emergency response, and video security. This article describes the Panoptes video-based sensor networking architecture, including its design, implementation, and performance. We describe two video sensor platforms that can deliver high-quality video over 802.11 networks with a power requirement less than 5 watts. In addition, we describe the streaming and prioritization mechanisms that we have designed to allow it to survive long-periods of disconnected operation. Finally, we describe a sample application and bitmapping algorithm that we have implemented to show the usefulness of our platform. Our experiments include an in-depth analysis of the bottlenecks within the system as well as power measurements for the various components of the system.

Measurement-based characterization of a collection of on-line games

On-line games are a rapidly growing Internet application. Because of the cost in supporting on-line games and the unpredictable load on servers, companies are moving toward sharing infrastructure for game hosting. To efficiently provision on-line games, it is important to understand game workloads and the behavior of game players. In this paper, we present a comprehensive analysis of a collection of on-line game players and game workloads using data from several sources including: a 13-month trace of an extremely busy game server containing over 2.8 million connections, a two-year trace of the aggregate game populations of over 550 on-line games, and a 4-month trace of a content-distribution network used to deliver games. The key findings from our measurement study are: (1) these gamers are an extremely difficult set of users to satisfy and unless game servers are properly set up and provisioned, gamers quickly choose to go elsewhere, (2) the popularity of these games follows a power law making games difficult to provision at launch time, (3) game workloads are predictable only over short-term intervals, (4) there are significant challenges in hosting games on shared infrastructure due to temporal and geographic synchronization across different games and other interactive applications, and (5) game software updates are a significent burden on game hosting that must be planned for. Our results have implications for both game publishers as well as infrastructure providers.

A long-term study of a popular MMORPG

Over the last decade, Massively Multi-player On-line Role Playing Games (MMORPGs), have become big business. In typical MMORPGs, players pay a monthly subscription to the game publisher who hosts the game and provides periodic content updates. To be successful, game publishers must characterize their player population so that they can provision sufficient resources to support the game and so that they can update the game in a timely manner. To this end, this paper provides the first, long-term study of a popular MMORPG from its launch. Our dataset encompasses the entire lifetime of EVE Online [1, 2], a science-fiction based MMORPG that has supported nearly 1 million unique players, 67 million player sessions, and 17,000 player years of gameplay since its launch in May 2003.

Characterizing online games

Online games are a rapidly growing Internet application. In order to run a successful online game, game companies and game infrastructure providers must properly manage game workloads and content so that they can maximize player satisfaction while minimizing their own costs. Toward this end, this paper provides a comprehensive, long-term analysis of several popular online games and their players using one of the richest data sets available for online games.

Stealth measurements for cheat detection in on-line games

As a result of physically owning the client machine, cheaters in network games currently have the upper-hand when it comes to avoiding detection by anti-cheat software. To address this problem and turn the tables on cheaters, this paper examines an approach for cheat detection based on the use of stealth measurements via tamper-resistant hardware. To support this approach, we examine a range of cheat methods and a number of measurements that such hardware could perform to detect them.

Fides: remote anomaly-based cheat detection using client emulation

As a result of physically owning the client machine, cheaters in online games currently have the upper-hand when it comes to avoiding detection. To address this problem and turn the table on cheaters, this paper presents Fides, an anomaly-based cheat detection approach that remotely validates game execution. With Fides, a server-side Controller specifies how and when a client-side Auditor measures the game. To accurately validate measurements, the Controller partially emulates the client and collaborates with the server. This paper examines a range of cheat methods and initial measurements that counter them, showing that a Fides prototype is able to efficiently detect several existing cheats, including one state-of-the-art cheat that is advertised as undetectable.

The Case for Public Work

Whether it is port scans, spam, or distributed denial-of-service attacks from botnets, unwanted traffic is a fundamental problem in all networked systems. Although proof-of-work has been proposed as a mechanism for thwarting such attacks, few proof-of-work systems have been successfully deployed. One of the problems in the proof-of-work approach is that the systems that issue and verify puzzles are typically located at or near the server edge. Rather than eliminate the denial-of-service problem, such approaches merely shift the problem from the service itself to the proof-of-work systems protecting the service. As a result, adversaries can disable services by flooding the issuer, by flooding the verifier, or by flooding all of the network links that lead to the issuer and verifier. To address this problem, this paper proposes a new approach for building proof-of-work systems based on publicly verifiable client puzzles. The system works by issuing a single public work function that clients must solve for each of its subsequent requests. Because the work function is publicly verifiable, any network device at the clients edge can verify that subsequent traffic will be accepted by the service. The system mitigates floods to the issuer since only a single work function needs to be given per client, thus allowing duplicate requests and replies to be supressed. The system mitigates floods to the verifier and across links leading to the server edge by allowing the verifier to be placed arbitrarily close to the client adversary.

PlayerRating: A reputation system for multiplayer online games

In multiplayer online games, players interact with each other using aliases which unfortunately enable antisocial behavior. Vague rules and limited policing mean that only the very worst offenders are ever disciplined. This paper presents PlayerRating, a distributed reputation system specifically designed for online games. It leverages the prior experiences of a players peers to determine the reputability of all other peers, allowing well-behaved players to safely congregate and avoid interaction with antisocial peers. The system has been implemented as an interface add-on for the game World of Warcraft and is evaluated theoretically and experimentally.

Cascades: scalable, flexible and composable middleware for multi-modal sensor networking applications

This paper describes the design and implementation of Cascades, a scalable, flexible and composable middleware platform for multi-modal sensor networking applications. The middleware is designed to provide a way for application writers to use pre-packaged routines as well as incorporate their own application-tailored code when necessary. As sensor systems become more diverse in both hardware and sensing modalities, such systems support will become critical. Furthermore, the systems software must not only be flexible, but also be efficient and provide high performance. Experimentation in this paper compares and contrasts several possible implementations based upon testbed measurements on embedded devices. Our experimentation shows that such a system can indeed be constructed.

Helping TicketMaster: Changing the Economics of Ticket Robots with Geographic Proof-of-Work

When tickets for popular events such as Hannah Montana concerts go on sale online, they sell out almost instantly. Unfortunately, a significant number of them are purchased by world-wide networks of ticket purchasing robots run by scalpers looking to turn a quick profit. Ticket outlets currently employ CAPTCHAs to slow down fully automated purchasing robots. Since the profit associated with scalping tickets is several orders of magnitude larger than the cost associated with paying humans to solve the CAPTCHAs, this approach has been ineffective. CAPTCHAs have a fundamental flaw when used to protect online tickets: the cost to solve them using humans is fixed and small. To address this problem, this paper explores a novel alternative based on geographically-driven proof-of-work. The crux of the approach exploits the observation that most legitimate clients are located geographically close to the event. By requiring every client to solve a cryptographic puzzle whose difficulty is based on their distance to the event, ticket purchasing robots must be placed close to each event in order to monopolize the tickets. This requirement significantly increases the cost of operating such networks. Using emulation and simulation, we demonstrate the utility of our approach in tackling the online ticketing problem.