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.     

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.     

A General Framework of Time-Variant Bandwidth Allocation in the Data Broadcasting Environment

Data broadcast is an advanced technique to realize large scalability and bandwidth utilization in a mobile computing environment. In this environment, the channel bandwidth of each channel is variant with time in real cases. However, traditional schemes do not consider time-variant bandwidth of each channel to schedule data items. Therefore, the above drawback degrades the performance in generating broadcast programs. In this paper, we address the problem of generating a broadcast program to disseminate data via multiple channels of time-variant bandwidth. In view of the characteristics of time-variant bandwidth, we propose an algorithm using adaptive allocation on time-variant bandwidth to generate the broadcast program to avoid the above drawback to minimize average waiting time. Experimental results show that our approach is able to generate the broadcast programs with high quality and is very efficient in a data broadcasting environment with the time-variant bandwidth.     

An energy efficient re-access scheme for data caching in data broadcast of a mobile computing environment

Data caching is used to improve the response time and the power consumption of a mobile client in a mobile computing environment. To enhance the performance of data caching, one needs to improve the hit ratio and to reduce the cost in processing a cache miss. In a mobile computing environment, a cached data item of a mobile client needs to remain up-to-date with respect to its corresponding data item in the server. A cached data item which is out of date is called a cached invalidated data item. Accessing a cached invalidated data item can be regarded as processing a cache miss. To access a cached invalidated data item, a mobile client needs to download the new content of the data item from the broadcast channel. This operation is called a re-access operation in this paper. Re-accessing a cached invalidated data item incurs large tuning time overhead. In this paper, we propose a re-access scheme that reduces this overhead by allowing a mobile client to access a cached invalidated data item from the broadcast channel without accessing indices. We analyze the performance of the proposed scheme and validate the analysis through experiments. The experiments showed that the proposed scheme significantly reduces the tuning time of a mobile client. Furthermore, the proposed scheme is robust in the sense that it allows changes on the broadcast structure in data broadcasting.     

Maintaining mobile transactional consistency in hybrid broadcast environments

Recently there have been attempts in several research areas at efficiently utilizing the resources of mobile computers. Considering the properties in mobile computing environments, push-based data dissemination systems have lately attracted considerable attention. However, skewed access patterns among mobile clients makes response time worse, and they prefer to send data requests to the server explicitly through an uplink channel. A broadcast supporting an uplink channel is called a hybrid broadcast. In this paper, we devise new transaction processing algorithms for hybrid broadcasts. It is assumed that data objects that the server maintains are divided into Push_Data for periodic broadcasting and Pull_Data for on-demand service. That is, clients have to explicitly request data objects in Pull_Data. Maintaining transactional consistency in this environment without much additional cost is our main concern. Finally, we evaluate performance behavior through simulation study.Received: 15 November 2002, Published online: 5 August 2004This work was done as part of the Information & Communication Fundamental Technology Research Program, supported by the Ministry of Information & Communication in the Republic of Korea.     

Scheduling time‐critical requests for multiple data objects in on‐demand broadcast

On‐demand broadcast is an effective data dissemination approach in mobile computing environments. Most of the recent studies on on‐demand data broadcast assume that clients request only a single‐data‐object at a time. This assumption may not be practical for the increasingly sophisticated mobile applications. In this paper, we investigate the scheduling problem of time‐critical requests for multiple data objects in on‐demand broadcast environments and observe that existing scheduling algorithms designed for single‐data‐object requests perform unsatisfactorily in this new setting. Based on our analysis, we propose new algorithms to improve the system performance. Copyright © 2010 John Wiley & Sons, Ltd.     

Query optimization for broadcast database

In a mobile environment, the broadcast paradigm has been recognized as an effective way to disseminate frequently requested information to multiple ‘mobile clients’. In this paper, we show that to query the broadcast database efficiently, database items must be organized over the broadcast channel in a meaningful way, reflecting the semantics of the database being broadcast. We define, for the first time, a cost model called the Semantic Ordering Model for identifying the optimal organization of database items over the broadcast channel. Experimental results are also delineated to illustrate the feasibility of our cost model, using relational and object-oriented databases as examples.     

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.     

移动环境下支持实时事务处理的数据预取

随着移动通信技术的迅速发展,人们提出了新的应用要求:在移动环境下处理实时事务.而移动通信带宽有限性引起较大的数据访问延迟,有时甚至由于网络传输的断接使得事务得不到所需要的数据,数据预取能够很好地解决这个问题.已有的移动环境下数据预取没有考虑到数据的流行性和事务的时间特性.该文分析影响实时事务数据预取的因素,首先考虑数据易变性、活跃性等因素,获得高价值预取数据集合;然后考虑访问预取数据的事务优先级、数据流行性等因素,构造预取数据的选择函数,通过该函数在前面选取的集合中筛选出对满足实时事务截止期更有价值的数据对象进行预取.实验表明,该数据预取策略能降低移动实时事务满足截止期的比率,更好地支持移动实时事务处理.     

在移动计算环境中基于移动代理的缓存失效方案

1 引言缓存技术是分布式计算环境中的重要技术,它可以改善系统的整体性能(如查询响应时间、吞吐量等),而移动计算的网络环境是一种特殊的分布式环境,与传统的分布式系统相比,它具有鲜明的特点:移动性、断接性、带宽多样性、可伸缩性、弱可靠性、网络通信的非对称性、电源能力局限性等等。这些特点使得缓存技术在移动计算环境中尤为重要。因为缓存能有效减少带宽需求,并能节省移动计算机的能耗。     

Efficient Distributed Skyline Queries for Mobile Applications

In this paper, we consider skyline queries in a mobile and distributed environment, where data objects are distributed in some sites (database servers) which are interconnected through a high-speed wired network, and queries are issued by mobile units (laptop, cell phone, etc.) which access the data objects of database servers by wireless channels. The inherent properties of mobile computing environment such as mobility, limited wireless bandwidth, frequent disconnection, make skyline queries more complicated. We show how to efficiently perform distributed skyline queries in a mobile environment and propose a skyline query processing approach, called efficient distributed skyline based on mobile computing (EDS-MC). In EDS-MC, a distributed skyline query is decomposed into five processing phases and each phase is elaborately designed in order to reduce the network communication, network delay and query response time. We conduct extensive experiments in a simulated mobile database system, and the experimental results demonstrate the superiority of EDS-MC over other skyline query processing techniques on mobile computing.     

Adaptive caching and refreshing in mobile databases

The mobile computing environment is receiving increasing attention recently. We consider a mobile environment in which a collection of mobile clients accesses a stationary database server via a wireless channel. Due to the limited bandwidth of a wireless channel and the instability of the wireless network, caching of frequently accessed data items in a client's local storage becomes especially important for improving the performance and data availability of data access queries. In this paper, we discuss the limitations of existing caching mechanisms in a mobile environment and investigate issues that need to be addressed. We propose an adaptive caching model that could cope with the nature of a mobile environment and the low-bandwidth wireless media, supporting fast data access. We describe the adaptive cache replacement and refresh mechanisms; explain the implementation in the context of object-oriented databases; and illustrate the results of some exploratory experiments to demonstrate the feasibility of the mechanisms.     

多用户动态节能资源竞争计算卸载策略

针对移动边缘计算环境下,移动设备的计算、续航、存储能力的不足,导致其响应延迟、电池寿命降低等问题,设计了一种动态节能资源竞争计算卸载（DERCO）策略。该策略综合考虑了信道容量以及设备间的相互干扰等情况,以一种贪婪算法的思想,让所有边缘设备通过迭代竞争信道资源,节能效果最好的设备将获得卸载机会,再利用一次性卸载方法,根据实时的信道状况和卸载速率进行动态的细粒度子任务卸载决策。实验结果表明,该策略优于一种近似协同计算卸载方案,有效降低了设备的能耗与时延。     

Broadcast-based group invalidation: An energy-efficient cache invalidation strategy

In a wireless environment, mobile clients may cache frequently accessed data to reduce the contention on the narrow bandwidth of the wireless channel. However, to minimize energy consumption, mobile clients may also often operate in a disconnected mode. As a result, the clients may miss some cache invalidation reports broadcast by a server. Thus, upon reconnection, a cache invalidation scheme must be employed to ensure the validity of the cached data. Existing techniques either require the clients to discard the cached data entirely, or require the clients to transmit uplink messages to a server. While the former eliminates the benefits of caching, the latter may lead to high energy consumption, poor channel utilization, and costs. In this paper, we present a new cache invalidation scheme, called Broadcast-Based Group Invalidation (BGI), that retains the benefits of caching while avoiding unnecessary transmissions (which translates to energy saving, better channel utilization, and lower costs). Under BGI, a pair of invalidation reports is broadcast periodically. While the object invalidation report enables the clients to salvage as many recently cached objects as possible, the group invalidation report cuts down on false invalidation. We conduct extensive studies based on a simulation model. The simulation results show that BGI consumes less energy and is superior over existing techniques.     

移动实时事务预留广播空间的验证协议

在无线数据广播环境中,从移动客户机到服务器的上行带宽非常有限,传统的并发控制协议不适合这种不对称通信环境.本文提出一种可变乐观并发控制协议,服务器周期性向移动客户机广播数据对象,同时把一个广播周期分成若干个子周期,在两个连续的子周期间,一个保留空间被预留来存放服务器更新事务在第一个子周期开始后修改的所有数据对象,移动只读事务通过比较服务器更新事务提交的写集合和自己读集合来自主进行一致性验证,如果只读事务不能通过部分验证,它不会被草率地夭折并重新启动,相反,应用一个改进的向前验证策略,帮助移动只读事务争取更多提交机会.最后,本文进行充分的实验对提出的算法性能进行了评价.     

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     

基于进化理论的层信任模型研究与实现

通过对可信计算进行深入的分析,并进行严格的逻辑推理证明,提出了基于进化理论的层信任模型。该模型在逻辑结构上定义了可信计算环境基本的信任链和可信层,并通过3个主要属性来描述可信度,物理结构上通过广电网的基于法定权利义务关系的可信根广播和在可信终端建立基于可信存储的可信根,来实现可信计算环境。该模型使得现有通用计算平台也适用于可信计算环境,提出了解决可信计算环境的外部性和公正性问题的方法,减少了可信终端主动防御带来的验证开销,用较小的代价实现了可信计算环境下可信计算实体可信度收敛。     

Effcient Distributed Skyline Queries for Mobile Applications

In this paper, we consider skyline queries in a mobile and distributed environment, where data objects are distributed in some sites (database servers) which are interconnected through a high-speed wired network, and queries are issued by mobile units (laptop, cell phone, etc.) which access the data objects of database servers by wireless channels. The inherent properties of mobile computing environment such as mobility, limited wireless bandwidth, frequent disconnection, make skyline queries more complicat...     

Energy- and Latency-Efficient Processing of Full-Text Searches on a Wireless Broadcast Stream

In wireless mobile computing environments, broadcasting is an effective and scalable technique to disseminate information to a massive number of clients, wherein the energy usage and latency are considered major concerns. This paper presents an indexing scheme for the energy- and latency-efficient processing of full-text searches over the wireless broadcast data stream. Although a lot of access methods and index structures have been proposed in the past for full-text searches, all of them are targeted for data in disk storage, not wireless broadcast channels. For full-text searches on a wireless broadcast stream, we firstly introduce a naive, inverted list-style indexing method, where inverted lists are placed in front of the data on the wireless channel. In order to reduce the latency overhead, we propose a two-level indexing method which adds another level of index structure to the basic inverted list-style index. In addition, we propose a replication strategy of the index list and index tree to further improve the latency performance. We analyze the performance of the proposed indexing scheme with respect to the latency and energy usage measures, and show the optimality of index replication. The correctness of the analysis is demonstrated through simulation experiments, and the effectiveness of the proposed scheme is shown by implementing a real wireless information delivery system.