PS+Pre/Post: A novel structure and access mechanism for wireless XML stream supporting twig pattern queries

XML data broadcast is an efficient way to disseminate XML data to a large number of mobile clients in mobile wireless networks. Recently, several indexing methods have been proposed to improve the performance of XML query processing in terms of access time and tuning time over XML streams. However, existing indexing methods cannot process twig pattern XML queries. In this paper, we propose a novel structure for streaming XML data called PS+Pre/Post by integrating the path summary technique and the pre/post labeling scheme. Our proposed XML stream structure exploits the benefits of the path summary technique and the pre/post labeling scheme to efficiently process different types of XML queries over the broadcast stream. Experimental results show that our proposed XML stream structure improves the performance of access time and tuning time in processing different types of XML queries.     

Query processing optimization in broadcasting XML data in mobile communications

Todays, XML as a de facto standard is used to broadcast data over mobile wireless networks. In these networks, mobile clients send their XML queries over a wireless broadcast channel and recieve their desired XML data from the channel. However, downloading the whole XML data by a mobile device is a challenge since the mobile devices used by clients are small battery powered devices with limited resources. To meet this challenge, the XML data should be indexed in such a way that the desired XML data can be found easily and only such data can be downloaded instead of the whole XML data by the mobile clients. Several indexing methods are proposed to selectively access the XML data over an XML stream. However, the existing indexing methods cause an increase in the size of XML stream by including some extra information over the XML stream. In this paper, a new XML stream structure is proposed to disseminate the XML data over a broadcast channel by grouping and summarizing the structural information of XML nodes. By summarizing such information, the size of XML stream can be reduced and therefore, the latency of retrieving the desired XML data over a wirless broadcast channel can be reduced. The proposed XML stream structure also contains indexes in order to skip from the irrelevant parts over the XML stream. It therefore can reduce the energy consumption of mobile devices in downloading the results of XML queries. In addition, our proposed XML stream structure can process different types of XML queries and experimental results showed that it improves the performace of XML query processing over the XML data stream compared to the existing research works in terms of access and tuning times.

     

Broadcasting and querying multi-dimensional index trees in a multi-channel environment

The continuous broadcast of data together with an index structure is an effective way of disseminating data in a wireless, mobile environment. The availability of an index allows a reduction in the tuning time and thus leads to lower power consumption for a mobile client. This paper considers scheduling index trees in multiple channel environments in which a mobile client can tune into a specified channel at one time instance. Let T be an n-node index tree of height h representing multi-dimensional index structure to be broadcast in a c  -channel environment. We describe two algorithms generating broadcast schedules that differ in the worst-case performance experienced by a client executing a general query. A general query is a query which results in an arbitrary traversal of the index tree, compared to a simple query in which a single path is traversed. Our first algorithm schedules any tree using minimum cycle length and it executes a simple query within one cycle. However, a general query may require O(hc)$O(\mathit{hc})$ cycles and thus result in a high latency. The second algorithm generates a schedule of minimum cycle length on which a general query takes at most O(c)$O(c)$ cycles. For some queries this is the best possible latency.     

Mobile service oriented architectures for NN-queries

The ever-increasing number of mobile device users has also raised the users’ expectation of mobile services accordingly. This phenomenon has given pressures to the mobile service providers to improve their services in order to stay competitive in the market. The service oriented approach is seen to be a promising scheme for mobile services. This paper presents mobile service oriented architectures for Nearest-Neighbor (NN) queries that are classified into five categories, namely (i) intermittent query mobile services, (ii) continuous query mobile services, (iii) context-aware mobile services, (iv) continuous moving object query mobile services, and (v) data broadcast mobile services. These services incorporate query, location and context-aware services, ontological context model, and broadcast. The proposed architectures are concerned with mobile services for clients on the move requesting services based on their current location, which is arguably the most important feature in a wireless environment. Furthermore, we also discuss the Quality-of-Service (QoS) requirement for mobile services in which request latency time is one of the most important parameters to consider. Some analytical models for query latency measurement are presented and the results are compared with the simulation experiments.     

Broadcast-Based Spatial Queries

Indexing techniques have been developed for wireless data broadcast environments, in order to conserve the scarce power resources of the mobile clients. However, the use of interleaved index segments in a broadcast cycle increases the average access latency for the clients. In this paper, the broadcast-based spatial query processing methods (BBS) are presented for the location-based services. In the BBS, broadcasted data objects are sorted sequentially based on their locations, and the server broadcasts the location dependent data along with an index segment. Then, a sequential prefetching and caching scheme is designed to reduce the query response time. The performance of this scheme is investigated in relation to various environmental variables, such as the distributions of the data objects, the average speed of the clients and the size of the service area.     

A scalable low-latency cache invalidation strategy for mobile environments

Caching frequently accessed data items on the client side is an effective technique for improving performance in a mobile environment. Classical cache invalidation strategies are not suitable for mobile environments due to frequent disconnections and mobility of the clients. One attractive cache invalidation technique is based on invalidation reports (IRs). However, the IR-based cache invalidation solution has two major drawbacks, which have not been addressed in previous research. First, there is a long query latency associated with this solution since a client cannot answer the query until the next IR interval. Second, when the server updates a hot data item, all clients have to query the server and get the data from the server separately, which wastes a large amount of bandwidth. In this paper, we propose an IR-based cache invalidation algorithm, which can significantly reduce the query latency and efficiently utilize the broadcast bandwidth. Detailed analytical analysis and simulation experiments are carried out to evaluate the proposed methodology. Compared to previous IR-based schemes, our scheme can significantly improve the throughput and reduce the query latency, the number of uplink request, and the broadcast bandwidth requirements.     

An energy-efficient and access latency optimized indexing scheme for wireless data broadcast

Data broadcast is an attractive data dissemination method in mobile environments. To improve energy efficiency, existing air indexing schemes for data broadcast have focused on reducing tuning time only, i.e., the duration that a mobile client stays active in data accesses. On the other hand, existing broadcast scheduling schemes have aimed at reducing access latency through nonflat data broadcast to improve responsiveness only. Not much work has addressed the energy efficiency and responsiveness issues concurrently. This paper proposes an energy-efficient indexing scheme called MHash that optimizes tuning time and access latency in an integrated fashion. MHash reduces tuning time by means of hash-based indexing and enables nonflat data broadcast to reduce access latency. The design of hash function and the optimization of bandwidth allocation are investigated in depth to refine MHash. Experimental results show that, under skewed access distribution, MHash outperforms state-of-the-art air indexing schemes and achieves access latency close to optimal broadcast scheduling.     

Effective Data Placement for Wireless Broadcast

This paper investigates how to place data objects on air for wireless broadcast such that mobile clients can access the data in short latency. We first define and analyze the problem of wireless data placement, and also propose a measure, named Query Distance (QD), which represents the coherence degree of data set accessed by a query. We show that the problem is NP-complete, and then propose an effective data placement method that constructs the broadcast schedule by appending each query's data set in greedy way. We show through performance experiments that the proposed method reduces the access time of mobile query.     

Effective protocols for kNN search on broadcast multi-dimensional index trees

In a wireless mobile environment, data broadcasting provides an efficient way to disseminate data. Via data broadcasting, a server can provide location-based services to a large client population in a wireless environment. Among different location-based services, the k nearest neighbors (kNN) search is important and is used to find the k closest objects to a given point. However, the kNN search in a broadcast environment is particularly challenging due to the sequential access to the data on a broadcast channel. We propose efficient protocols for the kNN search on a broadcast R-tree, which is a popular multi-dimensional index tree, in a wireless broadcast environment in terms of latency and tuning time as well as memory usage. We investigate how a server schedules the broadcast and provide the corresponding kNN search algorithms at the mobile clients. One of our kNN search protocols further allows a kNN search to start at an arbitrary time instance and it can skip the waiting time for the beginning of a broadcast cycle, thereby reducing the latency. The experimental results validate that our mechanisms achieve the objectives.     

An error-resilient and tunable distributed indexing scheme for wireless data broadcast

Access efficiency and energy conservation are two critical performance concerns in a wireless data broadcast system. We propose in this paper a novel parameterized index called the exponential index that has a linear yet distributed structure for wireless data broadcast. Based on two tuning knobs, index base and chunk size, the exponential index can be tuned to optimize the access latency with the tuning time bounded by a given limit, and vice versa. The client access algorithm for the exponential index under unreliable broadcast is described. A performance analysis of the exponential index is provided. Extensive ns-2-based simulation experiments are conducted to evaluate the performance under various link error probabilities. Simulation results show that the exponential index substantially outperforms the state-of-the-art indexes. In particular, it is more resilient to link errors and achieves more performance advantages from index caching. The results also demonstrate its great flexibility in trading access latency with tuning time.     

基于广播空间数据安全查询方法

索引提供了选择性调优,为了节约电池,客户需等待并调优到最佳索引段。在位置感知移动服务里(LAMSs),由于晚查询响应可能包含过时的信息,重要的是要减少查询响应时间。因此提出一个基于广播空间查询方案,处理方案旨在支持最邻近查询处理。分配方案中,广播数据项按顺序进行排序,基于其位置和客户可以选择性地调整到所需的数据项,而不需要一个索引段。由此产生的延迟和调优时间已经接近最优值,作为分析和仿真结果显示。     

移动环境中基于Huffman索引树的广播数据组织

移动计算环境中无线网络通信的非对称性和伸缩性要求 ,使得数据广播成为移动环境中数据发布和获取的重要手段 .为使移动客户有效地从广播中获取数据 ,该文提出了一种基于 Huffm an树的索引模型 ,给出 Huffman索引树的构造方法和基于 Huffman索引树的广播数据组织方式 .同时 ,该文还对比 B 树 ,对基于 Huffman索引树的数据组织方式从空间开销、调谐时间、存取时间等方面进行了性能分析与比较 ,表明该广播组织方式能提高移动数据广播的性能     

A Hierarchical Grid Index (HGI), spatial queries in wireless data broadcasting

The main requirements for spatial query processing via mobile terminals include rapid and accurate searching and low energy consumption. Most location-based services (LBSs) are provided using an on-demand method, which is suitable for light-loaded systems where contention for wireless channels and server processing is not severe. However, as the number of users of LBSs increases, performance deteriorates rapidly since the servers’ capability to process queries is limited. Furthermore, the response time of a query may significantly increase with the concentration of users’ queries in a server at the same time. That is because the server has to check the locations of users and potential objects for the final result and then individually send answers to clients via a point-to-point channel. At this time, an inefficient structure of spatial index and searching algorithm may incur an extremely large access latency. To address this problem, we propose the Hierarchical Grid Index (HGI), which provides a light-weight sequential location-based index structure for efficient LBSs. We minimize the index size through the use of hierarchical location-based identifications. And we support efficient query processing in broadcasting environments through sequential data transfer and search based on the object locations. We also propose Top-Down Search and Reduction-Counter Search algorithms for efficient searching and query processing. HGI has a simple structure through elimination of replication pointers and is therefore suitable for broadcasting environments with one-dimensional characteristics, thus enabling rapid and accurate spatial search by reducing redundant data. Our performance evaluation shows that our proposed index and algorithms are accurate and fast and support efficient spatial query processing.     

Grid-partition index: a hybrid method for nearest-neighbor queries in wireless location-based services

Traditional nearest-neighbor (NN) search is based on two basic indexing approaches: object-based indexing and solution-based indexing. The former is constructed based on the locations of data objects: using some distance heuristics on object locations. The latter is built on a precomputed solution space. Thus, NN queries can be reduced to and processed as simple point queries in this solution space. Both approaches exhibit some disadvantages, especially when employed for wireless data broadcast in mobile computing environments. In this paper, we introduce a new index method, called the grid-partition index, to support NN search in both on-demand access and periodic broadcast modes of mobile computing. The grid-partition index is constructed based on the Voronoi diagram, i.e., the solution space of NN queries. However, it has two distinctive characteristics. First, it divides the solution space into grid cells such that a query point can be efficiently mapped into a grid cell around which the nearest object is located. This significantly reduces the search space. Second, the grid-partition index stores the objects that are potential NNs of any query falling within the cell. The storage of objects, instead of the Voronoi cells, makes the grid-partition index a hybrid of the solution-based and object-based approaches. As a result, it achieves a much more compact representation than the pure solution-based approach and avoids backtracked traversals required in the typical object-based approach, thus realizing the advantages of both approaches. We develop an incremental construction algorithm to address the issue of object update. In addition, we present a cost model to approximate the search cost of different grid partitioning schemes. The performances of the grid-partition index and existing indexes are evaluated using both synthetic and real data. The results show that, overall, the grid-partition index significantly outperforms object-based indexes and solution-based indexes. Furthermore, we extend the grid-partition index to support continuous-nearest-neighbor search. Both algorithms and experimental results are presented. Edited by R. Guting     

A distributed spatial index for error-prone wireless data broadcast

Information is valuable to users when it is available not only at the right time but also at the right place. To support efficient location-based data access in wireless data broadcast systems, a distributed spatial index (called DSI) is presented in this paper. DSI is highly efficient because it has a linear yet fully distributed structure that naturally shares links in different search paths. DSI is very resilient to the error-prone wireless communication environment because interrupted search operations based on DSI can be resumed easily. It supports search algorithms for classical location-based queries such as window queries and kNN queries in both of the snapshot and continuous query modes. In-depth analysis and simulation-based evaluation have been conducted. The results show that DSI significantly out-performs a variant of R-trees tailored for wireless data broadcast environments.     

A tree-structured index allocation method with replication over multiple broadcast channels in wireless environments

Broadcast has often been used to disseminate frequently requested data efficiently to a large volume of mobile units over single or multiple channels. Since mobile units have limited battery power, the minimization of the access and tuning times for the broadcast data is an important problem. There have been many research efforts that focus on minimizing access and tuning times by providing indexes on the broadcast data. We have studied an efficient index allocation method for broadcast data with skewed access frequencies over multiple physical channels which cannot be coalesced into a single high bandwidth channel. Previously proposed index allocation techniques have one of two problems. The first problem is that they require equal size for both index and data. The second problem is that their performance degrades when the number of given physical channels is not enough. These two problems result in an increased average access time for the broadcast data. To cope with these problems, we propose a tree-structured index allocation method. Our method minimizes the average access time by broadcasting the hot data and their indices more frequently than the less hot data and their indexes over the dedicated index and data channels. We present an in-depth experimental and theoretical analysis of our method by comparing it with other similar techniques. Our performance analysis shows that it significantly decreases the average access and tuning times for the broadcast data over existing methods.     

基于数据访问概率的广播索引技术

在移动计算中,如何节约移动设备的电源是一个重要的研究方向。采用索引广播的方式可以使移动设备选择性地监听信道,从而减少了电源的消耗。该文提出了为广播数据建立基于访问概率的索引技术,并分固定扇出的非平衡索引树和可变扇出的索引树两种情况讨论如何降低平均访问代价。针对这两种情况,分别设计了构造索引树的算法。     

Mobile broadcast services with MIMO antennae in 4G wireless networks

The deployment of wireless data broadcast to empower mobile information services as a resource-conserving means offers significant benefits due to the scalability feature offered by the technology. In this paper, we present a novel and holistic data broadcast management approach in 4 G wireless networks with multiple-input multiple-output (MIMO) antennae. The proposed scheme consists of three elements, namely: (i) broadcast ordering; (ii) Global indexing; and (iii) merging data structure. With the integration of these elements, we expect to obtain substantial efficiency for mobile computing clients when retrieving data on-air. We have experimentally evaluated the performance of the proposed model including comparison with the relevant schemes. The results from the experiments affirm the effectiveness of our proposed approach in respect to minimizing query access time and conserving energy utilization of the clients.     

一种面向分布式数据库的多并发OLAP型查询性能预测方法

数据库查询性能预测即预测查询的执行延迟时间。数据库查询延迟预测技术能够用于查询调度和查询进度显示等。当前的查询性能预测技术都具有一定的局限性,不能准确预测分布式数据库中多并发查询导致CPU、I/O资源争用情形下的查询延迟。针对这一问题,该论文提出了一种在分布式数据库中预测并发OLAP型查询延迟的技术,该技术通过建立查询干扰度和查询敏感度模型来衡量资源（I/O,网络）竞争的激烈程度,并据此来预测不同执行环境下的查询性能。TPC-DS的实验结果表明,分析型查询预测的误差率在25%以下,说明该技术能够较准确地预测查询执行时间。     

Energy-efficient air-indices for shortest path and distance queries on road networks

Although various air-indices, e.g., Next Region (NR), have been proposed to support shortest path and distance queries at mobile clients on a road network, how to minimize the energy cost, which is dominated by the cost for obtaining traffic data from data broadcast, is still one of the most important performance objectives. Inspired by various preprocessing schemes in traditional computation models for shortest path queries that make use of special properties of road networks, we design in this paper a new air-index called the CH Index with the purpose of minimizing the energy cost for obtaining broadcasting data to perform shortest path and distance queries at mobile clients. Experimental evaluation shows that our CH Index is more energy efficient than the state-of-the-art index NR by an order of magnitude. We also extend the CH Index to the CHBN Index which provides a tradeoff between energy efficiency and response time for obtaining traffic data via a user-tunable parameter. We show that CHBN gives shorter response time than CH while still being energy efficient.