2077132
Continuous query processing in data streams using duality of data and queries
Recent data stream systems such as TelegraphCQ have employed the well-known property of duality between data and queries. In these systems, query processing methods are classified into two dual categories -- data-initiative and query-initiative -- depending on whether query processing is initiated by selecting a data element or a query. Although the duality property has been widely recognized, previous data stream systems do not fully take advantages of this property since they use the two dual methods independently: data-initiative methods only for continuous queries and query-initiative methods only for ad-hoc queries. We contend that continuous query processing can be better optimized by adopting an approach that integrates the two dual methods. Our primary contribution is based on the observation that spatial join is a powerful tool for achieving this objective. In this paper, we first present a new viewpoint of transforming the continuous query processing problem to a multi-dimensional spatial join problem. We then present a continuous query processing algorithm based on spatial join, which we name Spatial Join CQ. This algorithm processes continuous queries by finding the pairs of overlapping regions from a set of data elements and a set of queries, both defined as regions in the multi-dimensional space. The algorithm achieves the advantages of the two dual methods simultaneously. Experimental results show that the proposed algorithm outperforms earlier algorithms by up to 36 times for simple selection continuous queries and by up to 7 times for sliding window join queries.
18004950
Trajectory clustering: a partition-and-group framework
Existing trajectory clustering algorithms group similar trajectories as a whole, thus discovering common trajectories. Our key observation is that clustering trajectories as a whole could miss common sub-trajectories. Discovering common sub-trajectories is very useful in many applications, especially if we have regions of special interest for analysis. In this paper, we propose a new partition-and-group framework for clustering trajectories, which partitions a trajectory into a set of line segments, and then, groups similar line segments together into a cluster. The primary advantage of this framework is to discover common sub-trajectories from a trajectory database. Based on this partition-and-group framework, we develop a trajectory clustering algorithm TRACLUS. Our algorithm consists of two phases: partitioning and grouping. For the first phase, we present a formal trajectory partitioning algorithm using the minimum description length(MDL) principle. For the second phase, we present a density-based line-segment clustering algorithm. Experimental results demonstrate that TRACLUS correctly discovers common sub-trajectories from real trajectory data.
13264531
An efficient scattered data approximation using multilevel B-splines based on quasi-interpolants
In this paper, we propose an efficient approximation algorithm using multilevel B-splines based on quasi-interpolants. Multilevel technique uses a coarse to fine hierarchy to generate a sequence of bicubic B-spline functions whose sum approaches the desired interpolation function. To compute a set of control points, quasi-interpolants gives a procedure for deriving local spline approximation methods where a B-spline coefficient only depends on data points taken from the neighborhood of the support corresponding the B-spline. Experimental results show that the smooth surface reconstruction with high accuracy can be obtained from a selected set of scattered or dense irregular samples.
11377777
Delayed locking technique for improving real-time performance of embedded Linux by prediction of timer interrupt
In this paper, we propose a new technique, called a delayed locking technique, to improve the real-time performance of embedded Linux. The proposed technique employs the rule that entering a critical section is allowed only if the operation does not disturb the future execution of the real-time application. To execute this rule, we introduce the concepts of timer interrupt prediction and lock hold time acquisition. In addition, we designed and implemented a new high-resolution timer that is simple, yet efficient. We implemented the prototype on Linux 2.4.18. Experimental results show that the worst-case OS latency of real-time process is reduced to 23% of the original one, at the expense of slowdown of the nonreal-time process by 20%. Though we focus only on embedded Linux, our technique is useful for all kinds of real-time operating systems in which the critical section is significantly long.
1586129
A network-aware distributed storage cache for data intensive environments
Modern scientific computing involves organizing, moving, visualizing, and analyzing massive amounts of data at multiple sites around the world. The technologies, the middleware services, and the architectures that are used to build useful high-speed, wide area distributed systems, constitute the field of data intensive computing. We describe an architecture for data intensive applications where we use a high-speed distributed data cache as a common element for all of the sources and sinks of data. This cache-based approach provides standard interfaces to a large, application-oriented, distributed, on-line, transient storage system. We describe our implementation of this cache, how we have made it "network aware ", and how we do dynamic load balancing based on the current network conditions. We also show large increases in application throughput by access to knowledge of the network conditions.
16343799
Synchronization with multiprocessor caches
Introducing private caches in bus-based shared memory multiprocessors leads to the cache consistency problem since there may be multiple copies of shared data. However, the ability to snoop on the bus coupled with the fast broadcast capability allows the design of special hardware support for synchronization. We present a new lock-based cache scheme which incorporates synchronization into the cache coherency mechanism. With this scheme high-level synchronization primitives as well as low-level ones can be implemented without excessive overhead. Cost functions for well-known synchronization methods are derived for invalidation schemes, write update schemes, and our lock-based scheme. To accurately predict the performance implications of the new scheme, a new simulation model is developed embodying a widely accepted paradigm of parallel programming. It is shown that our lock-based protocol outperforms existing cache protocols.
14229192
Ranking Documents in Thesaurus-Based Boolean Retrieval Systems
Abstract In this paper we investigate document ranking methods in thesaurus-based boolean retrieval systems, and propose a new thesaurus-based ranking algorithm called the Extended Relevance (E-Relevance) algorithm. The E-Relevance algorithm integrates the extended boolean model and the thesaurus-based relevance algorithm. Since the E-Relevance algorithm has all the desirable properties of the extended boolean model, it avoids the various problems of previous thesaurus-based ranking algorithms. The E-Relevance algorithm also ranks documents effectively by using term dependence information from the thesaurus. We have shown through performance comparison that the proposed algorithm achieves higher retrieval effectiveness than the others proposed earlier.