A frequency‐aware data‐centric mechanism for wireless sensor networks

Wireless sensor networks (WSNs) are characterized by their low bandwidth, limited energy, and largely distributed deployment. To reduce the flooding overhead raised by transmitting query and data information, several data‐centric storage (DCS) mechanisms are proposed. However, the locations of these data‐centric nodes significantly impact the power consumption and efficiency for information queries and storage capabilities, especially in a multi‐sink environment. This paper proposes a novel dissemination approach, which is namely the dynamic data‐centric routing and storage mechanism (DDCRS), to dynamically determine locations of data‐centric nodes according to sink nodes' location and data collecting rate and automatically construct shared paths from data‐centric nodes to multiple sinks. To save the power consumption, the data‐centric node is changed when new sink nodes participate when the WSNs or some queries change their frequencies. The simulation results reveal that the proposed protocol outperforms existing protocols in terms of power conservation and power balancing. Copyright © 2009 John Wiley & Sons, Ltd.     

Energy-efficient skyline query optimization in wireless sensor networks

With the deployment of wireless sensor networks (WSNs) for environmental monitoring and event surveillance, WSNs can be treated as virtual databases to respond to user queries. It thus becomes more urgent that such databases are able to support complicated queries like skyline queries. Skyline query which is one of popular queries for multi-criteria decision making has received much attention in the past several years. In this paper we study skyline query optimization and maintenance in WSNs. Specifically, we first consider skyline query evaluation on a snapshot dataset, by devising two algorithms for finding skyline points progressively without examining the entire dataset. Two key strategies are adopted: One is to partition the dataset into several disjoint subsets and produce the skyline points in each subset progressively. Another is to employ a global filter that consists of some skyline points in the processed subsets to filter out unlikely skyline points from the rest of unexamined subsets. We then consider the query maintenance issue by proposing an algorithm for incremental maintenance of the skyline in a streaming dataset. A novel maintenance mechanism is proposed, which is able to identify which skyline points from past skylines to be the global filter and determine when the global filter is broadcast. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms on both synthetic and real sensing datasets, and the experimental results demonstrate that the proposed algorithms significantly outperform existing algorithms in terms of network lifetime prolongation.     

基于MapReduce的增广动态Skyline查询处理方法

Skyline查询能够计算大规模的数据集中满足多个标准的最优解,被广泛应用于多目标决策等领域.动态skyline查询作为skyline查询的一种重要变体,其结果随着查询点的不同而动态改变,为用户在指定查询要求方面提供了更大的灵活性.然而,随着数据量的不断增加,动态skyline查询会产生大量的查询结果,忽略了查询点的维度方向性和数据的全局整体性,给用户的选择带来极大困难.因此,需要进一步优化动态skyline查询的结果集,提高全局整体性,过滤冗余数据.针对上述问题,提出一种基于MapReduce的增广动态skyline查询处理方法.该方法将原始数据按照维度信息进行分区,在多个节点并行计算动态skyline,优化传统动态skyline结果集,同时提供全局更优的结果供用户选择.在此基础上,针对用户给出某些维度的容忍度的情况,提出一种引入用户容忍度的增广动态skyline查询处理方法.该方法可以根据用户容忍度缩减增广动态skyline查询的原始数据集,很大程度上减少中间结果的比较次数,并且提高了结果集的准确度.大量实验证明,基于MapReduce的增广动态skyline查询处理方法具有更好的有效性、准确性和可用性.     

移动P2P网络中能量有效连续查询研究

在移动P2P网络中一个基本应用问题是访问分布式空间数据库中的数据对象,同时节省电量.文中提出了在移动P2P网络中能量有效连续查询处理（Energy Efficient Continuous Query Processing,EECQP）算法,包括范围查询和k个最近邻居节点查询（k-nearest-neighbor queries, k-NN）.EECQP算法能够提供移动用户找到一个有质量保证的连续查询结果.EECQP算法主要的想法是允许用户与节点合作,持续保存查询结果,而不是总是从头开始处理查询,从而减少通信开销.实验结果表明所提出的EECQP算法对于范围查询和k个最近邻居节点查询在通信开销和QoS保证是能量有效和可扩展的.     

Dynamic network layer for data query in sensor network

Query processing systems in wireless sensor networks usually support tasks such as data acquisition, data aggregation, and event‐based query. The performances of query processing with these tasks are greatly varied according to different routing protocols. Most existing data query systems usually use one routing protocol to deal with all kinds of queries. This work demonstrates that proper selection of routing protocols can improve the performance of query processing. We propose a dynamic routing layer that makes protocol selection on the basis of query tasks and can automatically switch between different routing protocols. Simulation results show that dynamic routing scheme is more energy efficient than single routing protocol. Copyright © 2012 John Wiley & Sons, Ltd.     

SQLS: A Storm-Based Query Language System for Real-Time Stream Data Analysis

In this work,a Storm-based query language System (SQLS) is proposed for real-time data stream analysis.The system is compatible with Continuous query language (CQL) specification.It supports both continuous queries and one-time queries over streaming data,and meets the requirements of user experience (traditional SQL queries) and QoS (such as real-time and throughput).In order to better meet the requirement of throughput and enhance the processing efficiency,the load shedding algorithm and cache optimization are employed during the implementation of SQL-like operators.Finally,performance testing of the proposed SQLS has been conducted on standalone Storm platform and Storm clusters.Experimental resuits show that our system can not only meet the needs of users,but also extend the function of real-time streaming queries processing.     

查询驱动模式下两层传感器网络Top-k查询汇聚算法研究

在两层传感器网络中,查询驱动模式是将查询请求在下层传感器网络层进行分布式处理的一种查询处理模式.在传感器节点产生数据的频率较高而用户发出查询请求的频率较低的情况下,查询驱动模式能够大大减少数据传输量,降低节点的能量消耗.在这种模式下,如何有效支持局部区域性Top-k查询是一个很有挑战性的问题.针对这一问题,本文首先构造了一种新的数据汇聚树(DAT),接着在DAT的基础上提出了一种支持区域性Top-k查询的数据汇聚方案.理论分析和仿真实验表明,与已有算法相比,本文提出的方案更加高效.     

超对等网络中的轮廓查询优化

轮廓查询是近年来信息服务领域的一个研究重点和热点.现有的三阶段算法TPAOSS (Three-Phase Algorithm for Optimizing Skyline Scalar)至少存在如下两个缺陷:(1)在TPAOSS算法的第3阶段中,当网络节点上的对象个数较多时,Bloom filter的长度将呈指数级增长,从而严重影响获取子空间重复值的效率以及占用内存空间的大小;(2)TPAOSS算法只考虑预处理阶段的时间代价,而没有考虑各网络节点进行局部或全局子空间轮廓查询计算的效率.为此,提出一种适合超对等网络(Super-Peer Architecture,SPA)的子空间轮廓查询方法EPSSQDN (Efficient Processing of Subspace Skyline Queries in Distributed Networks).EPSSQDN算法有效解决了TPAOSS算法的的两个主要性能问题,并且显著提高了SPA网络中的子空间轮廓查询处理的效率.此外,为了能够进一步降低子空间上轮廓查询的时间开销以及网络节点间的数据传输量,我们给出新颖且有效的优化策略.实验结果表明,EPSSQDN算法比TPAOSS算法更能够缩短SPA网络中子空间轮廓查询的时间开销.     

用于智能电表数据分析的大数据平台

智能电网所产生的海量计量数据对数据存储和数据处理的系统架构提出了苛刻的性能要求,为此,文中提出了一种以内核、代理和客户端为主的模块化的大数据平台架构。所提议的大数据平台是基于Hadoop平台扩展,针对TB级别的静态智能电表数据集的存储和查询。实验结果表明,提议的大数据平台能够为电力行业提供一个具有竞争力且易于操作的大型能源数据管理和可视化知识平台,具有支持数据密集型决策的潜力。     

SKYLINE查询解析

现有的研究工作只考虑如何对单个底层关系表进行skyline计算,即它们假定用户所提交的skyline查询不涉及任何传统的关系操作,并且所有skyline维度均落入同一个关系表中.显然,在实际应用中,由于这种假设的不成立,使得在多数情况下用户查询的效率极其低下.基于此,将skyline计算作为一个特殊的关系操作符,研究它与传统关系操作符间执行顺序变换的等价规则.从而,利用这些等价变换规则,通过改变skyline操作符与传统关系操作符之间的执行顺序来有效提高查询的效率.同时,给出充分的理论证明来论证所给等价变换规则的正确性,并通过实验验证其有效性.     

An Efficient PAB‐Based Query Indexing for Processing Continuous Queries on Moving Objects

Existing methods to process continuous range queries are not scalable. In particular, as the number of continuous range queries on a large number of moving objects becomes larger, their performance degrades significantly. We propose a novel query indexing method called the projected attribute bit (PAB)‐based query index. We project a two‐dimensional continuous range query on each axis to get two one‐dimensional bit lists. Since the queries are transformed to bit lists and query evaluation is performed by bit operations, the storage cost of indexing and query evaluation time are reduced significantly. Through various experiments, we show that our method outperforms the containment‐encoded squares‐based indexing method, which is one of the most recently proposed methods.     

An Adaptive Smart Grid Management Scheme Based on the Coopetition Game Model

Recently, the idea of the smart grid has been gaining significant attention and has become a hot research topic. The purpose of this paper is to present a novel smart grid management scheme that uses game theory principles. In our proposed scheme, power appliances in the smart grid adaptively form groups according to the non‐cooperative hedonic game model. By exploiting multi‐appliance diversity, appliances in each group are dynamically scheduled in a cooperative manner. For efficient smart grid management, the proposed coopetition game approach is dynamic and flexible to adaptively respond to current system conditions. The main feature is to maximize the overall system performance while satisfying the requirements of individual appliances. Simulation results indicate that our proposed scheme achieves higher energy efficiency and better system performance than other existing schemes.     

Cross-Layer,Energy-Efficient Design for Supporting Continuous Queries in Wireless Sensor Networks: A Quorum-Based Approach

Power saving and query processing are two major concerns in a wireless sensor network. Each of these two issues has been intensively studied separately in the literature. In this work, we are interested in linking the asynchronous power-saving protocol and the continuous query-processing problem together. A cross-layer solution is proposed. On the MAC layer, we propose to use the grid-quorum system (Tseng et al., Computer Networks, 43(3):317–337, 2003) to serve as the underlying power-saving framework. On the network layer, we propose to find query paths based on the power cost incurred by grid quorums used by nodes along a path. We show how these two layers interwork with each other to support continuous queries in an energy-efficient way.     

基于空间数据与流数据集成管理的交通实时监控系统设计与实现

实时交通数据以流的形式持续快速到达,智能交通系统在地理空间数据的基础上处理实时交通数据。从数据存储、数据查询等角度来看,传统关系数据库技术在同时处理空间数据和流数据方面具有不足。基于GIS的实时交通监控原型系统集成现有的空间数据和流数据管理技术,支持静态查询、连续查询和混合查询,为交通用户提供高质量的服务。     

连续服务请求下基于假位置的用户隐私增强方法

基于假位置的隐私保护方案在为用户提供准确位置服务查询结果的同时,还无需第三方和共享密钥。然而,当用户连续请求位置服务时,由于现有保护单次查询的假位置方案未考虑相邻位置集合间的时空关系,使攻击者能推断出假位置,降低用户的位置隐私保护等级。针对上述问题,采用现有假位置方案生成候选假位置,并通过连续合理性检查和单次隐私增强对其进行筛选,提出一个适用于连续请求的假位置隐私保护增强方法。安全性分析表明,所提方法能保证连续请求中形成的移动路径在时空上不可区分,有效保护连续请求中的用户位置隐私。大量实验表明,所提方法在不增加用户计算开销的同时,与采用的候选假位置生成方案相比,还能提高用户单次查询的隐私保护等级。     

An Efficient Content‐Based High‐Dimensional Index Structure for Image Data

The existing multi‐dimensional index structures are not adequate for indexing higher‐dimensional data sets. Although conceptually they can be extended to higher dimensionalities, they usually require time and space that grow exponentially with the dimensionality. In this paper, we analyze the existing index structures and derive some requirements of an index structure for content‐based image retrieval. We also propose a new structure, for indexing large amount of point data in a high‐dimensional space that satisfies the requirements. In order to justify the performance of the proposed structure, we compare the proposed structure with the existing index structures in various environments. We show, through experiments, that our proposed structure outperforms the existing structures in terms of retrieval time and storage overhead.     

Continuous Monitoring of Spatial Queries in Wireless Broadcast Environments

Wireless data broadcast is a promising technique for information dissemination that leverages the computational capabilities of the mobile devices in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may then tune in the broadcast channel and process their queries locally without contacting the server. Previous work on spatial query processing for wireless broadcast systems has only considered snapshot queries over static data. In this paper, we propose an air indexing framework that 1) outperforms the existing (i.e., snapshot) techniques in terms of energy consumption while achieving low access latency and 2) constitutes the first method supporting efficient processing of continuous spatial queries over moving objects.     

概率数据流上Skyline查询处理算法

 概率数据流管理与分析逐步引起了研究者们的关注.Skyline查询技术是近年来数据库领域的研究热点.此前相关工作仅限于静态数据集或传统确定性数据流上的Skyline查询处理,尚无人考虑概率数据流上的Skyline计算问题,本文提出的SOPDS算法则较好地解决了该问题.在采用适应性更强的网格索引的基础上,提出了概率定界、逐步求精、提前淘汰与选择补偿等启发式规则对算法从时间和空间两方面进行了系统地优化.实验表明,算法在时间与空间上具有较高的整体性能.     

动态网络空间中的k-NN查询

随着无线通讯应用的持续增长和定位技术的发展,如何有效率的应答大量移动对象的查询请求以及基于位置的服务(1location-based services LBS)变得越来越重要,k-NN查询是其中的重要服务功能.本文提出了一种解决动态网络中静态对象k-NN查询算法,该算法先将网络以目标对象为中心进行网络划分,通过定位原始...     

Trajectory privacy protection method based on location obfuscation

In the process of continuous queries,a method of trajectory privacy protection based on location obfuscation was proposed to solve the problem that K-anonymity was difficult to guarantee user privacy in third party architectrue.Firstly,the (G-1) query obfuscation locations through the location prediction was obtained and the dummy location selection mechanism,and then sent them together with the user’s real query location to different anonymizers to form cloaking regions and sent them to the LBS server for queries,and the query results were returned to the user by different anonymizers.In this method,the user’s real query location was confused by the location obfuscation,and the attacker couldn’t deduce the user’s trajectory from a single anonymizer or the LBS server.The method can enhance the privacy of the user’s trajectory and can effectively solve the performance bottleneck in the single anonymizer structure.Security analysis shows the security of the proposed approach,and experiments show this method can reduce the number of interactions between the user and the LBS server and the overhead of the single anonymizer.