Saikat Guha

Is high-quality vod feasible using P2P swarming?

Peer-to-peer technologies are increasingly becoming the medium of choice for deliveringmedia content, both professional and home-grown, to large user populations. Indeed, current P2P swarming systems have been shown to be very efficient for large-scale content distribution with few server resources.However, such systems have been designed for generic file distribution and provide a limited user experience for viewing media content.For example, users need to wait to download the full video before they can start watching it.In general, the main challenge resides in designing systems that ensure that users can start watching a movie at any point in time, with small start-up times and sustainable playback rates. In this work, we address the issues of providing a Video-on-Demand (VoD) using P2P mesh-based networks. We show that providing high quality VoD using P2P is feasible using a combination of techniquesincluding (a) network coding, (b) optimized resource allocation across different parts of the video, and (c) overlay topology management algorithms.Our evaluation also shows that systems that do not use these techniques and do not optimize all of those dimensions can significantly under-utilize the network resources and result in poor VoD performance.Our results are based on simulations and results from a prototype implementation.

Characterization and measurement of TCP traversal through NATs and firewalls

In recent years, the standards community has developed techniques for traversing NAT/firewall boxes with UDP (that is, establishing UDP flows between hosts behind NATs). Because of the asymmetric nature of TCP connection establishment, however, NAT traversal of TCP is more difficult. Researchers have recently proposed a variety of promising approaches for TCP NAT traversal. The success of these approaches, however, depend on how NAT boxes respond to various sequences of TCP (and ICMP) packets. This paper presents the first broad study of NAT behavior for a comprehensive set of TCP NAT traversal techniques over a wide range of commercial NAT products. We developed a publicly available software test suite that measures the NATs responses both to a variety of isolated probes and to complete TCP connection establishments. We test sixteen NAT products in the lab, and 93 home NATs in the wild. Using these results, as well as market data for NAT products, we estimate the likelihood of successful NAT traversal for home networks. The insights gained from this paper can be used to guide both design of TCP NAT traversal protocols and the standardization of NAT/firewall behavior, including the IPv4-IPv6 translating NATs critical for IPv6 transition.

Challenges in measuring online advertising systems

Online advertising supports many Internet services, such as search, email, and social networks. At the same time, there are widespread concerns about the privacy loss associated with user targeting. Yet, very little is publicly known about how ad networks operate, especially with regard to how they use user information to target users. This paper takes a first principled look at measurement methodologies for ad networks. It proposes new metrics that are robust to the high levels of noise inherent in ad distribution, identifies measurement pitfalls and artifacts, and provides mitigation strategies. It also presents an analysis of how three different classes of advertising -- search, contextual, and social networks, use user profile information today.

NUTSS: a SIP-based approach to UDP and TCP network connectivity

The communications establishment capability of the Session Initiation Protocol is being expanded by the IETF to include establishing network layer connectivity for UDP for a range of scenarios, including where hosts are behind NAT boxes, and host are running IPv6. So far, this work has been limited to UDP because of the assumed impossibility of establishing TCP connections through NAT, and because of the difficulty of predicting port assignments on certain common types of NATs. This paper reports on preliminary success in establishing TCP connections through NAT, and on port prediction. In so doing, we suggest that it may be appropriate for SIP to take a broader architectural role in P2P network layer connectivity for both IPv4 and IPv6.

Sextant: a unified node and event localization framework using non-convex constraints

Determining node and event locations is a canonical task for many wireless network applications. Yet dedicated infrastructure for determining position information is expensive, energy-consuming, and simply unavailable in many deployment scenarios. This paper presents an accurate, cheap and scalable framework, called Sextant, for determining node position and event location in sensor networks. Sextant operates by setting up and solving a system of geographic constraints based on connectivity information from the underlying communication network. Sextant achieves high accuracy by enabling non-convex constraints to be used to refine position estimates. It represents position estimates as potentially non-contiguous collections of points. This general representation enables Sextant to use _negative information_, that is, information on where a node or event is not located, to refine location estimates. Sextant unifies both node and event detection within the same general framework. It can provide high precision without dedicated localization hardware by aggressively extracting constraints from the link layer, representing areas precisely with Bézier-enclosed polygons and probability distributions, and using event detection to refine node position estimates. A compact representation and a fully distributed implementation make the framework practical for resource-limited devices. The framework has been implemented, deployed and tested on laptops, PDAs and Mica-2 motes. Physical experiments show that a large number (98%) of the nodes in a network can determine their positions based on a small number (30%) of landmark nodes and that a large number (90%) of events can be located with low median error.

Exploring VoD in P2P Swarming Systems

Digital media companies have recently started embracing P2P networks as an alternative distribution mechanism. However, with current P2P swarming systems users need to download the full video, and hence have to wait a long time before they can start watching it. While a lot of effort has gone into optimizing the distribution of large files, little research has been done on enabling Video-on-Demand (VoD) functionality with P2P swarming systems. The main challenges reside in ensuring that users can start watching a movie at any point in time, with small start-up times and sustainable playback rates. In this work, we address the issues of providing VoD using P2P mesh-based networks. We investigate scheduling techniques, and network coding in particular. Using both simulations and a prototype implementation, we show that high-quality VoD is feasible, and give guidelines to build play-as-you-download P2P swarming systems with high playback rates and low start-up delays.

Measuring and fingerprinting click-spam in ad networks

Advertising plays a vital role in supporting free websites and smartphone apps. Click-spam, i.e., fraudulent or invalid clicks on online ads where the user has no actual interest in the advertisers site, results in advertising revenue being misappropriated by click-spammers. While ad networks take active measures to block click-spam today, the effectiveness of these measures is largely unknown. Moreover, advertisers and third parties have no way of independently estimating or defending against click-spam. In this paper, we take the first systematic look at click-spam. We propose the first methodology for advertisers to independently measure click-spam rates on their ads. We also develop an automated methodology for ad networks to proactively detect different simultaneous click-spam attacks. We validate both methodologies using data from major ad networks. We then conduct a large-scale measurement study of click-spam across ten major ad networks and four types of ads. In the process, we identify and perform in-depth analysis on seven ongoing click-spam attacks not blocked by major ad networks at the time of this writing. Our findings highlight the severity of the click-spam problem, especially for mobile ads.

RadioJockey: mining program execution to optimize cellular radio usage

Many networked applications that run in the background on a mobile device incur significant energy drains when using the cellular radio interface for communication. This is mainly due to the radio-tail, where the cellular radio remaining in a high energy state for up to 20s after each communication spurt. In order to cut down energy consumption, many recent devices employ fast dormancy, a feature that forces the client radio to quickly go into a low energy state after a fixed short idle period. However, aggressive idle timer values for fast dormancy can increase signaling overhead due to frequent state transitions, which negatively impacts the network. In this work, we have designed and implemented RadioJockey, a system that uses program execution traces to predict the end of communication spurts, thereby accurately invoking fast dormancy without increasing network signaling load. We evaluate RadioJockey on a broad range of background applications and show that it achieves 20-40\% energy savings with negligible increase in signaling overhead compared to fixed idle timer-based approaches.

Generalized resource allocation for the cloud

Resource allocation is an integral, evolving part of many data center management problems such as virtual machine placement in data centers, network virtualization, and multi-path network routing. Since the problems are inherently NP-Hard, most existing systems use custom-designed heuristics to find a suitable solution. However, such heuristics are often rigid, making it difficult to extend them as requirements change. In this paper, we present a novel approach to resource allocation that permits the problem specification to evolve with ease. We have built Wrasse, a generic and extensible tool that cloud environments can use to solve their specific allocation problem. Wrasse provides a simple yet expressive specification language that captures a wide range of resource allocation problems. At the back-end, it leverages the power of GPUs to provide solutions to the allocation problems in a fast and timely manner. We show the extensibility of Wrasse by expressing several allocation problems in its specification language. Our experiments show that Wrasses solution quality is as good as with heuristics, and sometimes even better, while maintaining good performance. In one case, Wrasse packed 71% more instances than a custom heuristic.

ViceROI: catching click-spam in search ad networks

Click-spam in online advertising, where unethical publishers use malware or trick users into clicking ads, siphons off hundreds of millions of advertiser dollars meant to support free websites and apps. Ad networks today, sadly, rely primarily on security through obscurity to defend against click-spam. In this paper, we present Viceroi, a principled approach to catching click-spam in search ad networks. It is designed based on the intuition that click-spam is a profit-making business that needs to deliver higher return on investment (ROI) for click-spammers than other (ethical) business models to offset the risk of getting caught. Viceroi operates at the ad network where it has visibility into all ad clicks. Working with a large real-world ad network, we find that the simple-yet-general Viceroi approach catches over six very different classes of click-spam attacks (e.g., malware-driven, search-hijacking, arbitrage) without any tuning knobs.