2039223
Processing Sliding Window Join Aggregate in Continuous Queries over Data Streams
Processing continuous queries over unbounded streams require unbounded memory. A common solution to this issue is to restrict the range of continuous queries into a sliding window that contains the most recent data of data streams. Sliding window join aggregates are often-used queries in data stream applications. The processing method to date is to construct steaming binary operator tree and pipeline execute. This method consumes a great deal of memory in storing the sliding window join results, therefore it isn’t suitable for stream query processing. To handle this issue, we present a set of novel sliding window join aggregate operators and corresponding realized algorithms, which achieve memory-saving and efficient performance. Because the performances of proposed algorithms vary with the states of data streams, a scheduling strategy is also investigated to maximize the processing efficiency. The algorithms in this paper not only can process the complex sliding window join aggregate, but also can process the multi-way sliding window join aggregate.
18804730
Processing Distributed Compoud-Data Streams
In the environment of distribute data stream systems, the available communication bandwidth is a bottleneck resource. It is significant to reduce the communication overhead as possible for improving the availability of communication bandwidth with the constraint of the precision of queries. In this paper, we propose a new method for transferring data streams in distributed data stream systems, named as compound-data streams. The idea is that raw data streams are grouped and merged into compound-data streams, and then compound-data streams, instead of raw data streams, are transferred to the central processor node. By this way, the communication overhead can be reduced greatly.
14692373
SlidingWindow based Multi-Join Algorithms over Distributed Data Streams
This paper focuses on multi-way sliding window join (SWJoin) processing over distributed data streams. A novel Join algorithm is proposed based on two distributed data stream transfer models. To reduce the communication cost and lighten the workload on the central processor node, the algorithm filters out tuples that can’t contribute to multiway SWJoin results by transforming the join conditions of SWJoin into filtering conditions during data stream transfer. Furthermore, the algorithm guarantees that all necessary data for generating exact multi-way SWJoin results can be transmitted to the central processor node.
3416923
Efficient Computation of the Skyline Cube
Skyline has been proposed as an important operator for multi-criteria decision making, data mining and visualization, and user-preference queries. In this paper. we consider the problem of efficiently computing a SKYCUBE, which consists of skylines of all possible non-empty subsets of a given set of dimensions. While existing skyline computation algorithms can be immediately extended to computing each skyline query independently, such "shared-nothing" algorithms are inefficient. We develop several computation sharing strategies based on effectively identifying the computation dependencies among multiple related skyline queries. Based on these sharing strategies, two novel algorithms, Bottom-Up and Top-Down algorithms, are proposed to compute SKYCUBE efficiently. Finally, our extensive performance evaluations confirm the effectiveness of the sharing strategies. It is shown that new algorithms significantly outperform the naive ones.
18683414
Extending Tree Automata to Obtain Consistent Query Answer from Inconsistent XML Document
Data may contain inconsistencies that violate integrity constraints, the consistent query answering problem attempts to find answers common for every possible repair. In this paper, we study how to handle the inconsistent XML document, which conforms to the DTD, while violates constraints. We consider three types of constraints, including functional dependencies, keys and foreign keys. We provide a repair framework for inconsistent XML document with three basic update operations: node insertion, node deletion and value modification. Following this approach, we introduce the concept of labelled XML document, which is an extension to the traditional tree model of XML with a function to indicate the unreliable nodes. We then give the definition of minimal labelled XML document, a representation of all possible repairs and can be used for consistent query answering. We provide a method for building an extended bottom-up tree automaton. The automaton can, in only one pass, not only check the validity of an XML document w.r.t DTD and integrity constraints, but also generate the corresponding minimal labelled XML document
32286255
Hardware Organization to Achieve High-Speed Elliptic Curve Cryptography for Mobile Devices
Elliptic curve cryptography (ECC) is recognized as a fast cryptography system and has many applications in security systems. In this paper, a novel sharing scheme is proposed to significantly reduce the number of field multiplications and the usage of lookup tables, providing high speed operations for both hardware and software realizations.
34121335
Data-Aware Clustering Hierarchy for Wireless Sensor Networks
In recent years, the wireless sensor network (WSN) is employed a wide range of applications. But existing communication protocols for WSN ignore the characteristics of collected data and set routes only according to the mutual distance and residual energy of sensors. In this paper we propose a Data-Aware Clustering Hierarchy (DACH), which organizes the sensors based on both distance information and data distribution in the network Furthermore, we also present a multi-granularity query processing method based on DACH, which can estimate the query result more efficiently. Our empirical study shows that DACH has higher energy efficiency than Low-Energy Adaptive Clustering Hierarchy (LEACH), and the multi-granularity query processing method based on DACH brings more accurate results than a random access system using same cost of energy.
9921122
Probabilistic Skyline Operator over Sliding Windows
Skyline computation has many applications including multi-criteria decision making. In this paper, we study the problem of efficient processing of continuous skyline queries over sliding windows on uncertain data elements regarding given probability thresholds. We first characterize what kind of elements we need to keep in our query computation. Then we show the size of dynamically maintained candidate set and the size of skyline. We develop novel, efficient techniques to process a continuous, probabilistic skyline query. Finally, we extend our techniques to the applications where multiple probability thresholds are given or we want to retrieve "top-k" skyline data objects. Our extensive experiments demonstrate that the proposed techniques are very efficient and handle a high-speed data stream in real time.