Efficient, Energy Conserving Transaction Processing in Wireless Data Broadcast

Broadcasting in wireless mobile computing environments is an effective technique to disseminate information to a massive number of clients equipped with powerful, battery operated devices. To conserve the usage of energy, which is a scarce resource, the information to be broadcast must be organized so that the client can selectively tune in at the desired portion of the broadcast. In this paper, the efficient, energy conserving transaction processing in mobile broadcast environments is examined with widely accepted approaches to indexed data organizations suited for a single item retrieval. The basic idea is to share the index information on multiple data items based on the predeclaration technique. The analytical and simulation studies have been performed to evaluate the effectiveness of our methodology, showing that predeclaration-based transaction processing with selective tuning ability can provide a significant performance improvement of battery life, while retaining a low access time. Tolerance to access failures during transaction processing is also described.     

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.     

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 efficient nonuniform index in the wireless broadcast environments

Data broadcast is an efficient dissemination method to deliver information to mobile clients through the wireless channel. It allows a huge number of the mobile clients simultaneously access data in the wireless environments. In real-life applications, more popular data may be frequently accessed by clients than less popular ones. Under such scenarios, Acharya et al.’s Broadcast Disks algorithm (BD) allocates more popular data appeared more times in a broadcast period than less popular ones, i.e., the nonuniform broadcast, and provides a good performance on reducing client waiting time. However, mobile devices should constantly tune in to the wireless broadcast channel to examine data, consuming a lot of energy. Using index technologies on the broadcast file can reduce a lot of energy consumption of the mobile devices without significantly increasing client waiting time. In this paper, we propose an efficient nonuniform index called the skewed index, SI, over BD. The proposed algorithm builds an index tree according to skewed access patterns of clients, and allocates index nodes for the popular data more times than those for the less popular ones in a broadcast cycle. From our experimental study, we have shown that our proposed algorithm outperforms the flexible index and the flexible distributed index.     

多盘广播的偏斜索引算法

在移动环境中,多盘广播是被广泛使用的数据广播调度算法之一。为广播数据建立索引可以使移动客户机选择性地监听信道,以减少电源消耗,但过多地插入索引会增加数据访问时间。针对该问题,为多盘广播建立偏斜索引,设计索引树构造算法和广播数据的索引树算法。与可变扇出算法相比,多盘广播的偏斜索引算法需要的平均访问时间和平均调谐时间较短。     

Disseminating dependent data in wireless broadcast environments

In wireless mobile environments, data broadcasting is an effective approach to disseminate information to mobile clients. In some applications, the access pattern of all the data can be represented by a weighted DAG. In this paper, we explore how to efficiently generate the broadcast schedule in a wireless environment for the data set having a weighted DAG access pattern. Such a broadcast schedule not only minimizes the access latency but also is a topological ordering of the DAG. Minimized access latency ensures the quality of service (QoS). We prove that it is NP-hard to find an optimal broadcast schedule and provide some heuristics. After giving an analysis for these heuristics on the latency and complexity, we implement all the proposed heuristics to compare their performance. Recommended by: Sunil Prabhakar     

Power-aware data retrieval protocols for indexed broadcast parallel channels

In pervasive and mobile computing environments, “timely and reliable” access to public data requires methods that allow quick, efficient, and low-power access to information to overcome technological limitations of wireless communication and access devices. The literature suggests broadcasting (one-way communication) as an effective way to disseminate the public data to mobile devices. Within the scope of broadcasting, the response time and energy consumption of retrieval methods have been used as the performance metrics for measuring the effectiveness of different access methods. The hardware and architecture of the mobile units offer different operational modes that consume different energy levels. Along with these architectural and hardware enhancements, techniques such as indexing, broadcasting along parallel channels, and efficient allocation and retrieval protocols can be used to minimize power consumption and access latency.In general, the retrieval methods attempt to determine the optimal access pattern for retrieving the requested data objects on parallel broadcast channels. The employment of heuristics provides a methodology for such ideal path planning solutions. Using informative heuristics and intelligent searches of an access forest can provide a prioritized cost evaluation of access patterns for requested data objects and, hence, an optimal path for the access of requested data on broadcast air channels.This paper examines two scheduling methods that along with a set of heuristics generate and facilitate the access patterns for retrieving data objects in the presence of conflicts in an indexed parallel broadcast channel environment. A simulation of the proposed schemes is presented for analyzing the relationship between response time and power consumption.     

Optimizing index allocation for sequential data broadcasting in wireless mobile computing

Energy saving is one of the most important issues in wireless mobile computing. Among others, one viable approach to achieving energy saving is to use an indexed data organization to broadcast data over wireless channels to mobile units. Using indexed broadcasting, mobile units can be guided to the data of interest efficiently and only need to be actively listening to the broadcasting channel when the relevant information is present. We explore the issue of indexing data with skewed access for sequential broadcasting in wireless mobile computing. We first propose methods to build index trees based on access frequencies of data records. To minimize the average cost of index probes, we consider two cases: one for fixed index fanouts and the other for variant index fanouts, and devise algorithms to construct index trees for both cases. We show that the cost of index probes can be minimized not only by employing an imbalanced index tree that is designed in accordance with data access skew, but also by exploiting variant fanouts for index nodes. Note that, even for the same index tree, different broadcasting orders of data records will lead to different average data access times. To address this issue, we develop an algorithm to determine the optimal order for sequential data broadcasting to minimize the average data access time. Performance evaluation on the algorithms proposed is conducted. Examples and remarks are given to illustrate our results.     

A concurrency control scheme for mobile transactions in broadcast disk environments

Broadcast disk technique has been often used to disseminate frequently requested data efficiently to a large volume of mobile clients over wireless channels. In broadcast disk environments, a server often broadcasts different data items with differing frequencies to reflect the skewed data access patterns of mobile clients. Previously proposed concurrency control methods for mobile transactions in wireless broadcast environments are focused on the mobile transactions with uniform data access patterns. These protocols perform poorly in broadcast disk environments where the data access patterns of mobile transactions are skewed. In broadcast disk environments, the time length of a broadcast cycle usually becomes large to reflect the skewed data access patterns. This will often cause read-only transactions to access old data items rather than the latest data items. Furthermore, updating mobile transactions will be frequently aborted and restarted in the final validation stage due to the update conflict of the same data items with high access frequencies. This problem will increase the average response time of the update mobile transactions and waste the uplink communication bandwidth. In this paper, we extend the existing FBOCC concurrency control method to efficiently handle mobile transactions with skewed data access patterns in broadcast disk environments. Our method allows read-only transactions to access the more updated data, and reduces the average response time of updating transactions through early aborts and restarts. Our method also reduces the amount of uplink communication bandwidth for the final validation of the update transactions. We present an in-depth experimental analysis of our method by comparing with existing concurrency control protocols. Our performance analysis shows that it significantly decreases the average response time and the amount of uplink bandwidths over existing methods.     

数据广播调度自适应信道划分与分配方法

随着移动网络的不断发展,移动终端设备的计算能力与日俱增,越来越多的用户倾向于通过移动网络获取信息资源,这使得实时按需数据广播面临新的挑战：（1）数据内容和规模的多样化;（2）用户请求的实时性与需求多样性使得热点数据增加,直接导致广播数据总量的剧增;（3）用户对服务质量和水平的要求越来越高.当前的研究成果主要集中在固定信道模型和算法上,一定程度上忽略了当前数据广播调度环境的变化.固定信道存在如下问题：（1）局限于特定的网络,缺乏通用性;（2）信道大小、个数不能随着网络环境的变化而自动调整,降低了广播效率.基于以上考虑,对实时按需数据广播调度的自适应信道划分和分配进行研究,提出一种自适应信道划分与分配方法OCSM （optimized channel split method）,其根据数据请求特征的不同,实时自适应地调整信道个数和大小,从而提高系统敏感性、鲁棒性以及广播效率.该方法包括：（1）广播数据均衡聚类算法WASC （weight average and size clusteralgorithm）,其挖掘数据特征,为信道划分提供依据;（2）数据项广播优先级评定算法R×W/SL,其实时评定数据项调度优先级;（3）信道划分与分配算法CSA （channel split algorithm）.实验包括两个方面：（1）确定不同数据项大小和请求截止期分布下的信道划分策略,并分析聚类算法中聚类距离K在不同情况下的最佳取值以及最佳信道划分;（2）验证自适应信道划分与分配策略的有效性,并通过对比实验验证在不同情况下OCSM的有效性.实验结果表明：OCSM优于其他调度算法,并具有较强的自适应.     

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     

Efficient query execution on broadcasted index tree structures

The continuous broadcast of data together with an index structure is an effective way of disseminating data in a wireless mobile environment. The index allows a mobile client to tune in only when relevant data is available on the channel and leads to reduced power consumption for the clients. This paper investigates the execution of queries on broadcasted index trees when query execution corresponds to a partial traversal of the tree. Queries exhibiting this behavior include range queries and nearest neighbor queries. We present two broadcast schedules for index trees and two query algorithms executed by mobile clients. Our solutions simultaneously minimize tuning time and latency and adapt to the client’s available memory. Experimental results using real and synthetic data compare results for a broadcast with node repetition to one without node repetition and they show how a priority-based data management can help reduce tuning time and latency.     

移动环境中自适应的XML广播索引

针对如何减少移动计算环境中XML数据广播的调谐时间和访问时间的问题,提出一种基于自适应索引的XML广播调度算法XAISA。它能根据系统负荷动态调整数据块的度,从而达到性能最优化。性能分析和实验比较表明,该算法能以极小的平均访问时间的代价大大减少平均调谐时间及接收XML广播数据的时间。     

移动计算环境中缓存失效策略的归类研究法

缓存失效报告法是在移动计算环境中普遍采用的缓存方案，即服务器定期广播缓存失效报告，该报告中包含了最近被更新的对象，根据报告内容，客户可使缓存中被更新对象失效，以保证缓存的有效性。缓存失效报告技术可采用多种策略，本文在研究多种缓存策略的基础上，提出了一种针对缓存失效方案的归类研究法，可对具体策略加以分析和评估，在此基础上对其性能进行改良，以形成更适应特定移动计算环境要求的缓存方案。     

移动数据库的并行数据分发控制技术研究

移动计算环境中上下行通信链路资源有限,通信链路频繁断连。数据移动终端用户如何能在移动计算环境中高效的访问数据,保证数据的实时性是文章的研究重点。通过提出一种基于并发控制的数据广播技术,来保证移动数据终端对数据的访问效率、时效性等性能的要求。实验结果表明数据访问的效率、时效性得到了提高。     

移动实时环境下一种改进的广播调度算法

在网络带宽不对称的移动实时环境中,数据广播是一种有效的数据访问方式。针对这种网络特性,分析了现今已经存在的某些广播调度算法。针对UFO算法,分别提出了SBS算法和CRS算法,它们从服务器、移动客户端两个方面进行了改进。两种算法可以根据给定的数据项访问概率分布,自动生成广播调度。通过理论分析和实验结果表明,该算法不会产生事务重启,并且可以有效减少数据的访问时间,使用户访问数据广播的平均等待时间最小。     

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     

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.

     

Dependent data broadcasting for unordered queries in a multiple channel mobile environment

Data broadcast is a promising technique to improve the bandwidth utilization and conserve the power consumption in a mobile computing environment. In many applications, the data items broadcast are dependent upon one another. However, most prior studies on broadcasting dependent data are restricted to a single broadcast channel environment, and as a consequence, the results are of limited applicability to the upcoming mobile environments. In view of this, we relax this restriction and explore the problem of broadcasting dependent data in multiple broadcast channels. By analyzing the model of dependent data broadcasting, we derive several theoretical properties for the average access time in a multiple channel environment. In light of the theoretical results, we develop a genetic algorithm to generate broadcast programs. Our experimental results show that the theoretical results derived are able to guide the search of the genetic algorithm very effectively, thus leading to broadcast programs of very high quality.