基于WCDMA的矿用M2M终端系统的设计

为了将井下人员信息、设备信息以及环境信息通过井下现有的通信网络传送至煤矿信息中心,提出了一种基于WCDMA的矿用M2M终端系统的设计方案,详细介绍了该系统硬件和软件的设计。该系统实现了对井下目标信息的采集、人机交互操作及数据通信功能,通过WCDMA网络将采集的数据互传,实现了物与物相联、物与人相联以及物与网络相联的物联网。     

实时光纤网络中突发数据传输的物理层设计

使用Altera CycloneⅢ FPGA设计了百兆实时光纤网络物理层,解决了百兆光纤网络突发数据通信中的数据突发发送、数据时钟的恢复及接收的关键技术。利用空间过采样技术避开了光通信中用于相位锁定、时钟恢复所需的等待时间,直接从码流中提取数据,从而减少了网络突发数据包的同步码开销,提高了光网络的带宽利用率。     

基于WAP的移动学习设计与实现

阐述移动学习的定义,说明移动学习的特点及优势;对移动学习平台的体系结构和功能模块进行设计,探讨了系统实现的关键技术。     

结合粗糙集与集成学习的中文文本分类方法研究

介绍中文文本分类的流程及相关技术。在分析传统的文本特征选择不足的基础上,提出了基于粗糙集与集成学习结合的文本分类方法,通过粗糙集进行文本的特征选择,采用一种集成学习算法AdaBoost.M1来提高弱分类器的分类性能,对中文文本进行分类。实验证明,这种算法分类结果的F1值比C4.5、kNN分类器都高,具有更加优良的分类性能。     

Grid resource management policies for load-balancing and energy-saving by vacation queuing theory

The resource management is the central component of grid system. The analysis of the workload log file of LCG including the job arrival and the resource utilization daily cycle shows that the idle sites in the Grid are the source of load imbalance and energy waste. Here we focus on these two issues: balancing the workload by transferring jobs to idle sites at prime time to minimize the response time and maximize the resource utilization; power management by switch the idle sites to sleeping mode at non-prime time to minimize the energy consume. We form the M/G/1 queue model with server vacations, startup and closedown to analysis the performance metrics to instruct the design of load-balancing and energy-saving policies. We provide our Adaptive Receiver Initiated (ARI) load-balancing strategy and power-management policy for energy-saving. The simulation experiments prove the accuracy of our analysis and the comparisons results indicate our policies are largely suitable for large-scale heterogeneous grid environment.     

A divide and conquer matheuristic algorithm for the Prize-collecting Steiner Tree Problem

The Prize-collecting Steiner Tree Problem (PCSTP) is a well-known problem in graph theory and combinatorial optimization. It has been successfully applied to solve real problems such as fiber-optic and gas distribution networks design. In this work, we concentrate on its application in biology to perform a functional analysis of genes. It is common to analyze large networks in genomics to infer a hidden knowledge. Due to the NP-hard characteristics of the PCSTP, it is computationally costly, if possible, to achieve exact solutions for such huge instances. Therefore, there is a need for fast and efficient matheuristic algorithms to explore and understand the concealed information in huge biological graphs. In this study, we propose a matheuristic method based on clustering algorithm. The main target of the method is to scale up the applicability of the currently available exact methods to large graph instances, without loosing too much on solution quality. The proposed matheuristic method is composed of a preprocessing procedures, a heuristic clustering algorithm and an exact solver for the PCSTP, applied on sub-graphs. We examine the performance of the proposed method on real-world benchmark instances from biology, and compare its results with those of the exact solver alone, without the heuristic clustering. We obtain solutions in shorter execution time and with negligible optimality gaps. This enables analyzing very large biological networks with the currently available exact solvers.     

物联网技术的研究综述

物联网打破了将物理基础设施和IT基础设施分开的传统思维,是信息领域一次重大的发展和变革机遇。物联网涉及众多领域,当前国内外的研究和开发都还处于起步阶段。对物联网研究的现实基础以及关键问题展开了讨论,介绍了物联网的四种具有代表性的定义和三种关键性的基本特征;分析了基于RFID的物联网应用架构、基于泛在传感网的物联网应用架构和基于M2M的物联网应用架构;给出了大致被公认为的四个层次的物联网关键技术框架;最后描述了物联网的典型应用领域。     

Analysis of the M/G/1 queue with discriminatory random order service policy

We consider an M/G/1 queue with different classes of customers and discriminatory random order service (DROS) discipline. The DROS discipline generalizes the random order service (ROS) discipline: when the server selects a customer to serve, all customers waiting in the system have the same selection probability under ROS discipline, whereas customers belonging to different classes may have different selection probabilities under DROS discipline. For the M/G/1 queue with DROS discipline, we derive equations for the joint queue length distributions and for the waiting time distributions of each class. We also obtain the moments of the queue lengths and the waiting time of each class. Numerical results are given to illustrate our results.