3112017
Distribution chain security
Digital content distribution systems will enable business models in the near future that cannot be predicted today. In this paper, we identify a new security problem that can be crucial to this enablement. The problem arises from the con icting privacy and integrity goals of middlemen in digital distribution chains. Our solution is a novel system design that incorporates obfuscated digital contracts, semi-trusted contract certi ers, and zero-knowledge proofs of arithmetic relations. Our implementation and timing experiments demonstrate that our solution is practical and eÆcient.
2563843
An algebraic approach to IP traceback
We present a new solution to the problem of determining the path a packet traversed over the Internet (called the traceback problem) during a denial-of-service attack. This article reframes the traceback problem as a polynomial reconstruction problem and uses algebraic techniques from coding theory and learning theory to provide robust methods of transmission and reconstruction.
5309390
Uniform Object Management
Most real-world applications require a capability for both general-purpose programming and database transactions on persistent data. Unfortunately, the implementation techniques for these capabilities are notoriously incompatible. Programming languages stress memory-resident transient data with a rich collection of data types, while database systems stress disk-resident persistent data with a limited collection of data types. Even in object-oriented database systems, combining these capabilities is traditionally done using a two-level storage model in which storage formats are quite different. This approach suffers from the performance overhead required to translate data between these two levels.
270075
Adaptive execution of variable-accuracy functions
Many analysis applications require the ability to repeatedly execute sophisticated modeling functions, which can each take minutes or even hours to produce a single answer. Because of this expense, such applications have largely been unable to directly use such models in queries, with either on-demand or continuous query processing technology. Query processors are hindered in their ability to optimize expensive modeling functions due to the "black box" nature of existing user-defined function (UDF) interfaces. In this paper, we address the problem of querying over sophisticated models with the development of VAOs (Variable-Accuracy Operators). VAOs use a new function interface that exposes the trade-off between compute time and accuracy that exists in many modeling functions. Using this interface, VAOs adaptively run each function call in a query only to an accuracy needed to answer the query, thus eliminating unneeded work. In this paper, we present the design of VAOs for a set of common query operations. We show the effectiveness of VAOs using a prototype implementation running financial queries over real bond market data.
4909660
Declarative Support for Sensor Data Cleaning
Pervasive applications rely on data captured from the physical world through sensor devices. Data provided by these devices, however, tend to be unreliable. The data must, therefore, be cleaned before an application can make use of them, leading to additional complexity for application development and deployment. Here we present Extensible Sensor stream Processing (ESP), a framework for building sensor data cleaning infrastructures for use in pervasive applications. ESP is designed as a pipeline using declarative cleaning mechanisms based on spatial and temporal characteristics of sensor data. We demonstrate ESP's effectiveness and ease of use through three real-world scenarios.
21834624
Events on the edge
The emergence of large-scale receptor-based systems has enabled applications to execute complex business logic over data generated from monitoring the physical world. An important functionality required by these applications is the detection and response to complex events, often in real-time. Bridging the gap between low-level receptor technology and such high-level needs of applications remains a significant challenge.We demonstrate our solution to this problem in the context of HiFi, a system we are building to solve the data management problems of large-scale receptor-based systems. Specifically, we show how HiFi generates simple events out of receptor data at its edges and provides high-functionality complex event processing mechanisms for sophisticated event detection using a real-world library scenario.
236978
Streaming Queries over Streaming Data
Recent work on querying data streams has focused on systems where newly arriving data is processed and continuously streamed to the user in real-time. In many emerging applications, however, ad hoc queries and/or intermittent connectivity also require the processing of data that arrives prior to query submission or during a period of disconnection. For such applications, we have developed PSoup, a system that combines the processing of ad-hoc and continuous queries by treating data and queries symmetrically, allowing new queries to be applied to old data and new data to be applied to old queries. PSoup also supports intermittent connectivity by separating the computation of query results from the delivery of those results. PSoup builds on adaptive query processing techniques developed in the Telegraph project at UC Berkeley. In this paper, we describe PSoup and present experiments that demonstrate the effectiveness of our approach.