Effective Location Based Services with Dynamic Data Management in Mobile Environments

With the proliferation of mobile computing technologies, location based services have been identified as one of the most promising target application. We classify mobile information service domains based on feature characteristics of the information sources and different patterns of mobile information access. By carefully examining the service requirements, we identify the dynamic data management problem that must be addressed for effective location based services in mobile environments. We then devise a general architecture and cost model for servicing both location independent and location dependent data. Based on the architecture and cost model, we propose a set of dynamic data management strategies that employs judicious caching, proactive server pushing and neighborhood replication to reduce service cost and improve response time under changing user mobility and access patterns. Detail behavior analysis helps us in precisely capturing when and how to apply these strategies. Simulation results suggest that different strategies are effective for different types of data in response to different patterns of movement and information access. Shiow-yang Wu is an associate professor of the Department of Computer Science and Information Engineering at National Dong Hwa University, Hualien, Taiwan, R.O.C. He received the BS and MS degrees in computer engineering from National Chiao Tung University, Hsinchu, Taiwan, ROC, and the PhD degree in computer science from the University of Texas at Austin in 1984, 1986, and 1995, respectively. His research interests include data/knowledge bases, mobile computing, distributed processing, intelligence information systems, and electronic commerce. Kun-Ta Wu was born in Taipei, Taiwan, R.O.C., in 1976. He received the B.S. degree in computer science from Soochow University, Taipei, Taiwan, R.O.C., in 1999 and the M.S. degree in computer science and information engineering from National Dong Hwa University, Hualien, Taiwan, R.O.C., in 2001. Currently, he is an Assistant Researcher in the Domestic Division at Science and Technology Information Center, National Science Council, R.O.C., as a member of Information Gathering and Analysis Group of National Information and Communication Security Taskforce. His research interests include mobile computing, wireless network and information security.     

Adsp-21060的主机接口在实时图像处理中的应用

简要介绍了数字信号处理器Adsp 2 10 6 0和大规模可编程逻辑器件EP1K5 0。详细讨论了Adsp 2 10 6 0的主机接口工作模式以及一个实时图像跟踪处理器的硬件组成原理 ,在这个系统中EP1K5 0充当了主机。调试结果表明 ,所提出的硬件结构设计思想工作效率高 ,完全能够胜任实时图像处理的实际需要。     

能源实时监控与信息管理系统出现的问题及解决的方法

中国石化北京燕化石油化工股份有限公司动力事业部二供水车间电气改造完成后，能源实时监控与信息管理系统出现线路名称不统一、电流互感系数变比不起作用、数据查询功能及统计报表数据的准确性等问题，严重地影响系统的使用。通过对比分析，找到了出现问题的实质，对源代码进行修改，问题得到了解决。同时也成功地解决了其他部门遇到相类似的问题。     

东营凹陷王庄-宁海地区流体包裹体分析与流体充注研究

利用流体包裹体分析技术，系统地分析了东营凹陷王庄-宁海地区覆盖所有含油层位的流体包裹体样品。包裹体荧光观察和均一温度特征分析揭示了包裹体发育期次为5期，说明该区油藏存在5次流体充注过程；据此确定了备期烃类的成藏期次。东营组沉积时期和明化镇组沉积末期的油气运聚均在成藏后遭受大气淡水淋滤和降解作用。沙三段原油可能经历至少2期稠油化作用。荧光观察进一步证实该区主要发生2期充注、2期成藏。     

低勘探程度区域油气资源评价方法

目前中国油气资源勘探和开发面临后备可采储量不足，低勘探程度区域受到重视。为了提高低勘探程度区域的资源评价精度，在前人评价的基础上，通过研究并利用勘探程度较高区域的资源评价结果，求准低勘探程度区域的油气聚集量，进而模拟求出其烃排聚系数、储量密度系数、单储系数和单生系数等关键参数，提出了利用练台地质推断法对低勘探程度区域进行评价，并对该方法评价的风险进行了分析。综合地质推断法的成果更能准确反映一个盆地、坳（凹）陷或区带的油气潜力及其分布特征。     

涡轮搅拌桨反应器混合过程的数值计算

利用CFD方法计算单层涡轮反应器搅拌槽内流体混合过程的速度场和浓度场,研究物料在搅拌槽内的混合过程,以及不同监测点对混合时间的影响。结果表明,搅拌槽内物料的混合主要受槽内流体的流动形式所影响;混合时间的长短与监测点位置有关;在搅拌桨的桨叶附近进行监测所得到的混合时间较短,在液面附近进行监测所得的混合时间较长。在实际生产和试验中,应注意对监测点位置的选取。     

石化企业实时数据管理引擎设计与实现

实时数据管理系统是流程企业控制信息网络与管理信息网络平滑集成的基础，为两者的数据通讯提供桥梁。介绍了笔者在炼油化工C企业IMS建设中的实时数据管理引擎设计与开发，具有其先进性与实用性。     

一种高精度的非平稳随机信号实时建模算法研究

针对传统的非平稳随机信号时变参数筹分模型算法的不足,论文把非平稳随机信号时变参数差分模型与一种带自适应遗忘因子的RLS算法结合起来,形成一种有效的非平稳随机信号实时建模算法,仿真分析表明该算法不仅能获得快的收敛速度而且能获得高的建模精度。     

Analysis of Distributed DDQ for QoS Router

In a packet switching network, congestion is unavoidable and affects the quality of real‐time traffic with such problems as delay and packet loss. Packet fair queuing (PFQ) algorithms are well‐known solutions for quality‐of‐service (QoS) guarantee by packet scheduling. Our approach is different from previous algorithms in that it uses hardware time achieved by sampling a counter triggered by a periodic clock signal. This clock signal can be provided to all the modules of a routing system to get synchronization. In this architecture, a variant of the PFQ algorithm, called digitized delay queuing (DDQ), can be distributed on many line interface modules. We derive the delay bounds in a single processor system and in a distributed architecture. The definition of traffic contribution improves the simplicity of the mathematical models. The effect of different time between modules in a distributed architecture is the key idea for understanding the delay behavior of a routing system. The number of bins required for the DDQ algorithm is also derived to make the system configuration clear. The analytical models developed in this paper form the basis of improvement and application to a combined input and output queuing (CIOQ) router architecture for a higher speed QoS network.     

Modeling and analysis of hierarchical cellular networks with bidirectional overflow and take-back strategies under generally distributed cell residence times

The rapid growth of wireless services and mobile users drives a great interest in cellular networks with a hierarchical structure. Hierarchical cellular networks (HCNs) can provide high system capacity, efficient channel utilization and inherent load-balancing capability. In this paper, we develop an analytical model and a performance analysis method for a two-layer HCN with bidirectional overflow and take-back strategies. Mobile users are divided into two classes. The call requests (including new and handoff calls) of fast and slow users are preferably assigned to the macrolayer and microlayer, respectively. A call from a fast user or slow user can overflow to its non-preferable layer if there is no channel available. The successful overflow call can be taken back to its preferable layer if a channel becomes available. Since the commonly used exponentially distributed assumption for cell residence time and then the channel occupancy time does not hold for emerging mobile networks, we model various cell residence times by general distributions to adapt to more flexible mobility environments. The channel occupancy times are derived in terms of the Laplace transforms of various cell residence times. The handoff rates, overflow rates and take-back rates of each layer are also derived in terms of the new call arrival rates and related probabilities. The stationary probabilities (and then the performance measures) are determined on the basis of the theory of multi-dimensional loss systems.