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.
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.
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 .
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.
2945748
Time Series Compressibility and Privacy
In this paper we study the trade-offs between time series compressibility and partial information hiding and their fundamental implications on how we should introduce uncertainty about individual values by perturbing them. More specifically, if the perturbation does not have the same compressibility properties as the original data, then it can be detected and filtered out, reducing uncertainty. Thus, by making the perturbation "similar" to the original data, we can both preserve the structure of the data better, while simultaneously making breaches harder. However, as data become more compressible, a fraction of the uncertainty can be removed if true values are leaked, revealing how they were perturbed. We formalize these notions, study the above trade-offs on real data and develop practical schemes which strike a good balance and can also be extended for on-the-fly data hiding in a streaming environment.
16010739
Compiler-directed proactive power management for networks
Increasing use of parallel computation platforms (both off-chip and on-chip) makes communication analysis and optimization an important target. While there have been numerous studies that target network performance of parallel architectures, the efforts that target network power consumption (in terms of both modeling and optimization) are relatively new. One of the common characteristics of most of the prior approaches to network power management is that they are hardware-based and reactive in the sense that they manage power consumption of the network as a response to observed message traffic. Consequently, they can miss important opportunities for saving power and can incur performance penalties due to inaccuracies in predicting future idle and active times of communication links. Motivated by this observation, this paper proposes a compiler-directed proactive approach to network power management for the class of loop-intensive applications running on small-sized networks used exclusively by a single embedded application at a time.As compared to hardware-based approaches, the proposed compiler-directed approach has two potential benefits. First, based on high-level communication analysis, it determines the points at which a given communication link is idle and can be turned off (i.e., powered down) to save power. Therefore, an idle link can be put in the low-power state without waiting for a certain period of time to make sure that the link has really become idle (as in the case of hardware schemes). Second, since the compiler can also determine the point at which a turned-off link will be needed in the future, it can pre-activate it (i.e., before it is actually needed) to eliminate the turn on (reactivation) performance penalty. Our simulations with seven array-intensive applications and an embedded on-chip network clearly show that the proposed compiler-directed approach is better than a hardware-based scheme from both power and performance perspectives.
9337355
Weather forecasting: predicting performance for streaming video over wireless LANs
The growth of wireless LANs has brought the expectation for high-bitrate streaming video to wireless PCs. However, it remains unclear how wireless channel characteristics impact the quality of streaming video sent over wireless LANs. This paper presents results from experiments that stream commercial video over a wireless campus network. By analyzing the streaming video quality and capturing wireless LAN characteristics across network and wireless link layers, "weather forecasts" are created such that selected wireless LAN performance indicators might be used to predict the streaming video quality. Furthermore, a quantified measurement of accuracy is presented to evaluate the effectiveness of individual weather forecasts. The paper evaluates six distinct weather forecasts four different streaming configurations including TCP and UDP streaming, and single and multiple-level encoded videos. The results show that the wireless Received Signal Strength Indicator (RSSI) and average wireless link capacity are the most accurate indicators to predict the performance of streaming video over wireless LANs. The weather forecast philosophy can be beneficial for adapting video streaming in wireless LAN environments.
6134766
Compiler-directed instruction duplication for soft error detection
We experiment with compiler-directed instruction duplication to detect soft errors in VLIW datapaths. In the proposed approach, the compiler determines the instruction schedule by balancing the permissible performance degradation with the required degree of duplication. Our experimental results show that our algorithms allow the designer to perform tradeoff analysis between performance and reliability.
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
8583268
Proportional degradation services in wireless/mobile adaptive multimedia networks
Adaptive multimedia services are very attractive since resources in wireless/mobile networks are relatively scarce and widely variable, and more importantly the resource fluctuation caused by mobility and channel fading can be mitigated using adaptive services. Therefore, there are extensive research activities on Quality of Service (QoS), call admission control, as well as bandwidth degradation and adaptation for adaptive multimedia services in wireless/mobile networks in recent years. However, fairness of bandwidth degradation has largely been ignored in previous work and remains an important issue in adaptive multimedia service provisioning. In this paper, we propose and study proportional degradation service provisioning in wireless/mobile networks that offer multiple classes of adaptive multimedia services. The proposed proportional degradation fairness model guarantees the proportional bandwidth degradation among different classes of services. Two proportional degradation scenarios are studied in this paper. In the first scenario, we study the proportional degradation provisioning with two QoS parameters for adaptive multimedia: the degradation ratio (DR) and the degradation degree (DD). In the second scenario, we study the proportional degradation provisioning with a new QoS parameter for adaptive multimedia: the degradation area (DA). For each scenario, based on the QoS parameters, proportional degradation adaptation algorithms are proposed to approximate the proportional degradation model, to fairly adapt calls' degradations, to utilize the system resource efficiently, as well as to optimize QoS parameters. Performance studies show that in the first scenario, proportional DR has been achieved very well, whereas proportional DD has not been well achieved. In other words, DR outperforms DD in terms of proportional degradation. In the second scenario, proportional DA has been well achieved. Furthermore, bandwidth resources have been efficiently utilized and DA has been minimized. Copyright © 2004 John Wiley & Sons, Ltd.