1718945
Dynamic authenticated index structures for outsourced databases
In outsourced database (ODB)systems the database owner publishes its data through a number of remote servers, with the goal of enabling clients at the edge of the network to access and query the data more efficiently. As servers might be untrusted or can be compromised, query authentication becomes an essential component of ODB systems. Existing solutions for this problem concentrate mostly on static scenarios and are based on idealistic properties for certain cryptographic primitives. In this work, first we define a variety of essential and practical cost metrics associated with ODB systems. Then, we analytically evaluate a number of different approaches, in search for a solution that best leverages all metrics. Most importantly, we look at solutions that can handle dynamic scenarios, where owners periodically update the data residing at the servers. Finally, we discuss query freshness, a new dimension in data authentication that has not been explored before. A comprehensive experimental evaluation of the proposed and existing approaches is used to validate the analytical models and verify our claims. Our findings exhibit that the proposed solutions improve performance substantially over existing approaches, both for static and dynamic environments.
8773045
Characterizing and Exploiting Reference Locality in Data Stream Applications
In this paper, we investigate a new approach to process queries in data stream applications. We show that reference locality characteristics of data streams could be exploited in the design of superior and flexible data stream query processing techniques. We identify two different causes of reference locality: popularity over long time scales and temporal correlations over shorter time scales. An elegant mathematical model is shown to precisely quantify the degree of those sources of locality. Furthermore, we analyze the impact of locality-awareness on achievable performance gains over traditional algorithms on applications such asMAX-subset approximate sliding window join and approximate count estimation. In a comprehensive experimental study, we compare several existing algorithms against our locality-aware algorithms over a number of real datasets. The results validate the usefulness and efficiency of our approach.
3002704
Approximate aggregation techniques for sensor databases
In the emerging area of sensor-based systems, a significant challenge is to develop scalable, fault-tolerant methods to extract useful information from the data the sensors collect. An approach to this data management problem is the use of sensor database systems, exemplified by TinyDB and Cougar, which allow users to perform aggregation queries such as MIN, COUNT and AVG on a sensor network. Due to power and range constraints, centralized approaches are generally impractical, so most systems use in-network aggregation to reduce network traffic. However, these aggregation strategies become bandwidth-intensive when combined with the fault-tolerant, multipath routing methods often used in these environments. For example, duplicate-sensitive aggregates such as SUM cannot be computed exactly using substantially less bandwidth than explicit enumeration. To avoid this expense, we investigate the use of approximate in-network aggregation using small sketches. Our contributions are as follows: 1) we generalize well known duplicate-insensitive sketches for approximating COUNT to handle SUM, 2) we present and analyze methods for using sketches to produce accurate results with low communication and computation overhead, and 3) we present an extensive experimental validation of our methods.
6484880
Spatio-temporal aggregation using sketches
Several spatio-temporal applications require the retrieval of summarized information about moving objects that lie in a query region during a query interval (e.g., the number of mobile users covered by a cell, traffic volume in a district, etc.). Existing solutions have the distinct counting problem: if an object remains in the query region for several timestamps during the query interval, it will be counted multiple times in the result. We solve this problem by integrating spatio-temporal indexes with sketches, traditionally used for approximate query processing. The proposed techniques can also be applied to reduce the space requirements of conventional spatio-temporal data and to mine spatio-temporal association rules.
11230966
Robust Aggregation in Sensor Networks
In the emerging area of sensor-based systems, a significant challenge is to develop scalable, fault-tolerant methods to extract useful information from the data the sensors collect. An approach to this data management problem is the use of sensor “database” systems, which allow users to perform aggregation queries on the readings of a sensor network. Due to power and range constraints, centralized approaches are generally impractical, so most systems use in-network aggregation to reduce network traffic. However, these aggregation strategies become bandwidthintensive when combined with the fault-tolerant, multi-path routing methods often used in these environments. In order to avoid this expense, we investigate the use of approximate in-network aggregation using small sketches and we survey robust and scalable methods for computing duplicate-sensitive aggregates.
3455572
On Trip Planning Queries in Spatial Databases
In this paper we discuss a new type of query in Spatial Databas es, called the Trip Planning Query (TPQ). Given a set of points of interestP in space, where each point belongs to a specific category, a star ting pointS and a destinationE, TPQ retrieves thebesttrip that starts at S, passes through at least one point from each category, and ends at E. For example, a driver traveling from Boston to Providence might want to stop to a gas station, a ban k and a post office on his way, and the goal is to provide him with the best possibl e route (in terms of distance, traffic, road conditions, etc.). The difficulty of this query lies in the existence of multiple choices per category. In this paper, w study fast approximation algorithms for TPQ in a metric space. We provide a numb er of approximation algorithms with approximation ratios that depend o either the number of categories, the maximum number of points per category or b oth. Therefore, for different instances of the problem, we can choose the alg orithm with the best approximation ratio, since they all run in polynomial time. Furthermore, we use some of the proposed algorithms to derive efficient heuristi cs for large datasets stored in external memory. Finally, we give an experimental ev luation of the proposed algorithms using both synthetic and real datasets .
16360248
Exploiting software pipelining for network-on-chip architectures
Recent developments in process technology have made it possible to produce chips consisting of a large number of processing elements. For factors such as scalability, performance, power-efficiency, the interconnection structure supporting such a chip needs to be an on-chip network architecture rather than a conventional bus-based system. Recent research has studied such network-on-chip (NoC) based systems from the performance and throughput, power/energy, reliability, predictability, synchronization, and concurrency perspectives. However, most of these studies are hardware based and it is not clear what type of compiler support would be best suited for these NoC based systems. Focusing on a mesh based NoC architecture that connects multiple processor cores, this paper explores the effectiveness of voltage/frequency scaling for processors and communication links with and without software pipelining, a compiler optimization for increasing parallelism. To our knowledge, this is the first paper that explores the influence of software pipelining in the context of the embedded NoC architectures
2691860
Design and Management of 3D Chip Multiprocessors Using Network-in-Memory
Long interconnects are becoming an increasingly important problem from both power and performance perspectives. This motivates designers to adopt on-chip network-based communication infrastructures and three-dimensional (3D) designs where multiple device layers are stacked together. Considering the trends towards increasing use of chip multiprocessing, it is timely to consider 3D chip multiprocessor design and memory networking issues, especially in the context of data management in large L2 caches. The overall goal of this paper is to study the challenges for L2 design and management in 3D chip multiprocessors. Our first contribution is to propose a router architecture and a topology design that makes use of a network architecture embedded into the L2 cache memory. Our second contribution is to demonstrate, through extensive experiments, that a 3D L2 memory architecture generates much better results than the conventional two-dimensional (2D) designs under different number of layers and vertical (inter-wafer) connections. In particular, our experiments show that a 3D architecture with no dynamic data migration generates better performance than a 2D architecture that employs data migration. This also helps reduce power consumption in L2 due to a reduced number of data movements
2155969
Improving performance of Java applications using a coprocessor
Summary form only given. Java technology is becoming a significant force stimulating the evolution of embedded systems. One of the problems in front of it is its poor performance. An important component of this performance problem is the overhead time spent during dynamic compilation. We demonstrate that a dual-processor heterogeneous architecture that employs both a conventional CPU and a Java coprocessor dedicated to compilation can be very effective in hiding the time spent in dynamic compilation. We propose two different profile-driven algorithms that make use of such a coprocessor based system, and evaluate them using a set of Java benchmarks. Our results clearly indicate that it is possible to improve overall performance by intelligently scheduling dynamic compilations on the coprocessor.
32161993
Emerging Web Graphics Standards and Technologies
Migrating computer graphics to the Web poses several problems, but with new standards and technology advances, graphics applications can balance latency and bandwidth constraints with image quality. The paper discusses Web graphics standards, distributed virtual environments and virtual humans.
17981801
Studying storage-recomputation tradeoffs in memory-constrained embedded processing
Fueled by an unprecedented desire for convenience and self-service, consumers are embracing embedded technology solutions that enhance their mobile lifestyles. Consequently, we witness an unprecedented proliferation of embedded/mobile applications. Most of the environments that execute these applications have severe power, performance, and memory space constraints that need to be accounted for. In particular, memory limitations can present serious challenges to embedded software designers. The current solutions to this problem include sophisticated packaging techniques and code optimizations for effective memory utilization. While the first solution is not scalable, the second one is restricted by intrinsic data dependences in the code that prevent code restructuring. In this paper, we explore an alternate approach for reducing memory space requirements of embedded applications. The idea is to re-compute the result of a code block (potentially multiple times) instead of storing it in memory and performing a memory operation whenever needed. The main benefit of this approach is that it reduces memory space requirements, that is, no memory space is reserved for storing the result of the code block in question.