8456748
Friends Troubleshooting Network: Towards Privacy-Preserving, Automatic Troubleshooting
Content sharing is a popular usage of peer-to-peer systems for its inherent scalability and low cost of maintenance. In this paper, we leverage this nature of peer-to-peer systems to tackle a new problem: automatic misconfiguration troubleshooting. In this setting, machine configurations from the peers are “shared” to diagnose the misconfigurations on a sick machine. A key challenge for such a troubleshooting system is privacy preservation. To this end, we construct Friends Troubleshooting Network (FTN), a peer-to-peer overlay network, where the links between peer machines reflect the friendship of their owners. To preserve privacy, we use historyless and futureless random-walk in the FTN, during which search along with parameter aggregation are carried out for the purpose of troubleshooting. Many of our techniques can be applied to other application scenarios that require privacy-preserving distributed computing and information aggregation. We have also identified a number of open challenges that remain to be addressed.
5266558
Resilient peer-to-peer streaming
We consider the problem of distributing "live" streaming media content to a potentially large and highly dynamic population of hosts. Peer-to-peer content distribution is attractive in this setting because the bandwidth available to serve content scales with demand. A key challenge, however, is making content distribution robust to peer transience. Our approach to providing robustness is to introduce redundance; both in network paths and in data. We use multiple, diverse distribution trees to provide redundancy in network paths and multiple description coding (MDC) to provide redundancy in data. We present a simple tree management algorithm that provides the necessary path diversity and describe an adaptation framework for MDC based on scalable receiver feedback. We evaluate these using MDC applied to real video data coupled with real usage traces from a major news site that experienced a large flash crowd for live streaming content. Our results show very significant benefits in using multiple distribution trees and MDC, with a 22 dB improvement in PSNR in some cases.
1302015
An evaluation of scalable application-level multicast built using peer-to-peer overlays
Structured peer-to-peer overlay networks such as CAN, Chord, Pastry, and Tapestry can be used to implement Internet-scale application-level multicast. There are two general approaches to accomplishing this: tree building and flooding. This paper evaluates these two approaches using two different types of structured overlay: 1) overlays which use a form of generalized hypercube routing, e.g., Chord, Pastry and Tapestry, and 2) overlays which use a numerical distance metric to route through a Cartesian hyperspace, e.g., CAN. Pastry and CAN are chosen as the representatives of each type of overlay. To the best of our knowledge, this paper reports the first head-to-head comparison of CAN-style versus Pastry-style overlay networks, using multicast communication workloads running on an identical simulation infrastructure. The two approaches to multicast are independent of overlay network choice, and we provide a comparison of flooding versus tree-based multicast on both overlays. Results show that the tree-based approach consistently outperforms the flooding approach. Finally, for tree-based multicast, we show that Pastry provides better performance than CAN.
1513566
Passive network tomography using Bayesian inference
In this paper, we investigate the problem of identifying lossy links in the interior of the Internet by passively observing the end-to-end performance of existing traffic between a server and its clients. This is in contrast to the previous work on network tomography (e.g., [1]) that has been based on active probing. The key advantage of a passive approach is that it does not introduce wasteful traffic which might perturb the object of inference, i.e., the link loss rates. Moreover, our techniques depend only on knowing the number of lost and successful packets sent to each client rather than the exact loss sequence required by previous techniques such as [1]. While accuracy of link loss rate inference may consequently suffer, our techniques can still pinpoint the trouble spots in the network (e.g., highly lossy links). We have developed three techniques for passive network tomography: Random Sampling, Linear Optimization, and Bayesian Inference using Gibbs Sampling. We have evaluated these techniques using simulations and traces gathered at a busy Web server. In this paper, we focus on the Gibbs Sampling technique; more information on the three techniques appears in [3].
42916380
Policy-enabled handoffs across heterogeneous wireless networks
"Access is the killer app" is the vision of the Daedalus project at UC Berkeley. Being able to be connected seamlessly anytime anywhere to the best network still remains an unfulfilled goal. Often, even determining the "best" network is a challenging task because of the widespread deployment of overlapping wireless networks. We describe a policy-enabled handoff system that allows users to express policies on what is the "best" wireless system at any moment, and make tradeoffs among network characteristics and dynamics such as cost, performance and power consumption. We designed a performance reporting scheme estimating current network conditions, which serves as input to the policy specification. A primary goal of this work is to make it possible to balance the bandwidth load across networks with comparable performance. To avoid the problem of handoff instability, i.e., many mobile hosts making the same handoff decision at essentially the same time, we designed randomization into our mechanism. Given the current "best" network, our system determines whether the handoff is worthwhile based on the handoff overhead and potential network usage duration.
13895152
ShieldGen: Automatic Data Patch Generation for Unknown Vulnerabilities with Informed Probing
In this paper, we present ShieldGen, a system for automatically generating a data patch or a vulnerability signature for an unknown vulnerability, given a zero-day attack instance. The key novelty in our work is that we leverage knowledge of the data format to generate new potential attack instances, which we call probes, and use a zero-day detector as an oracle to determine if an instance can still exploit the vulnerability; the feedback of the oracle guides our search for the vulnerability signature. We have implemented a ShieldGen prototype and experimented with three known vulnerabilities. The generated signatures have no false positives and a low rate of false negatives due to imperfect data format specifications and the sampling technique used in our probe generation. Overall, they are significantly more precise than the signatures generated by existing schemes. We have also conducted a detailed study of 25 vulnerabilities for which Microsoft has issued security bulletins between 2003 and 2006. We estimate that ShieldGen can produce high quality signatures for a large portion of those vulnerabilities and that the signatures are superior to the signatures generated by existing schemes.
14931170
Towards Automatic Identification Of Singing Language In Popular Music Recordings
The automatic analysis of singing from music is an important and challenging issue within the research target of content-based retrieval of music information. As part of this research target, this study presents a first attempt to automatically identify the language sung in a music recording. It is assumed that each language has its own set of constraints that specify which of the basic linguistic events present in a singing process are allowed to follow another. The acoustic structure of individual languages may, thus, be characterized by statistically modeling those constraints. To this end, the proposed method employs vector clustering to convert a singing signal from its spectrum-based feature representation into a sequence of smaller basic phonological units. The dynamic characteristics of the sequence are then analyzed by using bigram language models. Since the vector clustering is performed in an unsupervised manner, the resulting system does not use sophisticated linguistic knowledge and, thus, is easily portable to new language sets. In addition, to eliminate the interference of background music, we leverage the statistical estimation of a piece’s music background so that the vector clustering is relevant to the solo singing voices in the accompanied signals.
18351320
Spatial data query support in peer-to-peer systems
The distributed hash table (DHT) mechanisms have been proposed to manage data in very large, structured peer-to-peer (P2P) systems. DHT algorithms provide efficient exact-match object search capabilities without requiring global indexing and are hence extremely scalable. However, range queries - which are very common with spatial data - cannot be executed efficiently in these systems because the adoption of uniform hash functions to ensure excellent load balancing unfortunately destroys any existing data locality. In this report we propose a novel technique to preserve spatial locality information while also keeping some of the load balancing properties of DHT based systems. We describe our design as an extension of content-addressable networks (CAN) and illustrate the feasibility of supporting spatial range queries.
1367527
Space-Time Light Field Rendering
In this paper, we propose a novel framework called space-time light field rendering, which allows continuous exploration of a dynamic scene in both space and time. Compared to existing light field capture/rendering systems, it offers the capability of using unsynchronized video inputs and the added freedom of controlling the visualization in the temporal domain, such as smooth slow motion and temporal integration. In order to synthesize novel views from any viewpoint at any time instant, we develop a two-stage rendering algorithm. We first interpolate in the temporal domain to generate globally synchronized images using a robust spatial-temporal image registration algorithm followed by edge-preserving image morphing. We then interpolate these software-synchronized images in the spatial domain to synthesize the final view. In addition, we introduce a very accurate and robust algorithm to estimate subframe temporal offsets among input video sequences. Experimental results from unsynchronized videos with or without time stamps show that our approach is capable of maintaining photorealistic quality from a variety of real scenes.
14048105
GString: A Novel Approach for Efficient Search in Graph Databases
Graphs are widely used for modeling complicated data, including chemical compounds, protein interactions, XML documents, and multimedia. Information retrieval against such data can be formulated as a graph search problem, and finding an efficient solution to the problem is essential for many applications. A popular approach is to represent both graphs and queries on graphs by sequences, thus converting graph search to subsequence matching. State-of-the-art sequencing methods work at the finest granularity - each node (or edge) in the graph will appear as an element in the resulting sequence. Clearly, such methods are not semantic conscious, and the resulting sequences are not only bulky but also prone to complexities arising from graph isomorphism and other problems in searching. In this paper, we introduce a novel sequencing method to capture the semantics of the underlying graph data. We find meaningful components in graph structures and use them as the most basic units in sequencing. It not only reduces the size of resulting sequences, but also enables semantic-based searching. In this paper, we base our approach on chemical compound databases, although it can be applied to searching other complicated graphs, such as protein structures. Experiments demonstrate that our approach outperforms state-of-the-art graph search methods.
34944417
Logic of Many-Sorted Theories
Certain axiomatic systems involve more than one category of fundamental objects; for example, points, lines, and planes in geometry; individuals, classes of individuals, etc. in the theory of types or in predicate calculi of orders higher than one. It is natural to use variables of different kinds with their ranges respectively restricted to different categories of objects, and to assume as substructure the usual quantification theory (the restricted predicate calculus) for each of the various kinds of variables together with the usual theory of truth functions for the formulas of the system. An axiomatic theory set up in this manner will be called many-sorted. We shall refer to the theory of truth functions and quantifiers in it as its (many-sorted) elementary logic, and call the primitive symbols and axioms (including axiom schemata) the proper primitive symbols and proper axioms of the system. Our purpose in this paper is to investigate the many-sorted systems and their elementary logics. Among the proper primitive symbols of a many-sorted system T n ( n = 2, …, ω ) there may be included symbols of some or all of the following kinds: (1) predicates denoting the properties and relations treated in the system; (2) functors denoting the functions treated in the system; (3) constant names for certain objects of the system. We may either take as primitive or define a predicate denoting the identity relation in T n .