A decision support system for interactive decision making-Part I: model formulation

A comprehensive decision support system, GMCR II, is developed for the systematic study of real-world interactive decision problems. Model formulation is presented in Part I, and analysis and output interpretation in Part II. GMCR II is based upon existing and new research developments of the graph model for conflict resolution. In Part I, specially designed data structures and corresponding algorithms are implemented for generating and representing possible states, removing infeasible states, coalescing indistinguishable states, and specifying and storing allowable state transitions. Algorithms implementing different approaches to the elicitation of preferences over states enable GMCR II to construct and manage an efficient, flexible, and complete graph model of a strategic conflict.     

A decision support system for interactive decision making - Part II: analysis and output interpretation

For pt.I see ibid., p.42-55 (2003). The development of a comprehensive decision support system, GMCR II, for the systematic study of real-world interactive decision problems is presented. The companion paper (Part I), discusses how GMCR II elicits, stores, and manages conflict models; here (Part II), the focus is on GMCR IIs analysis and output interpretation subsystems. Specifically, this paper describes the powerful and efficient analysis engine contained in GMCR II, its informative output presentation and interpretation facilities, and a number of follow-up analyses. Furthermore, an illustrative case study is used to demonstrate how GMCR II can be conveniently applied in practice.     

CPSM:一种增强IP网络生存性的客户端主动服务漂移模型

 本文在注重提高IP网络服务可生存性的同时,也兼顾了服务可区分性的要求,提出了一种基于客户端的主动服务漂移模型,即CPSM,Client-side Proactive Service Migration model.该模型把服务漂移抽象为一个部分可观测马尔可夫决策过程,用以增强服务漂移对动态不确定性网络环境的自适应能力.在信息预报和信任机制的基础上,通过对网络状态的不断观测和分析,CPSM模型可以计算出使客户获益最高的服务漂移策略.     

The application of robustness analysis to the conflict withincomplete information

When players with different interests try to achieve a better state, conflicts among players arise. Conflicts may arise also among public players. For example, a local government may insist on the interest of the region while the national government represents the interests of the whole country. Conflict analysis is one of the methods to model such conflicts mathematically. Its stability analysis specifies stable states based on the ordinal information on players' preferences. However, if the preference of a player is private, stability of states is not known. In such a case, players or third parties have to collect additional information on other players' preference. It is necessary to specify the minimum information to collect. In this paper, graph model for conflict resolution (GMCR) is extended for the cases with incomplete information. Then, the generalized robustness analysis is proposed to specify the minimum conditions for stability of states. Finally, robustness analysis is applied to the conflict on water resources development     

Service function chain deployment algorithm based on optimal weighted graph matching

Service function chain can support flexible network service requirement by linking virtual network functions.Aiming at the problem of service function chain deployment in a resource-constrained network,an algorithm for service function chain deployment based on optimal weighted graph matching was proposed.The service function chains was composed into graphs of functional topography,and the optimal matching results between graphs of functional topology and physical topology was obtained using eigendecomposition approach,and furtherly the matching results by hill-climbing method was optimized.Simulation results show that,the proposed algorithm can reduce the required bandwidth to deploy service function chains,balance the load of nodes and bandwidth of links,and support more service requests.What is more,the algorithm has a lower computation complexity and higher time efficience.     

基于网络编码多维特征权重的无线Mesh网络接入时间分配机制

本文分析影响系统接入时间分配决策的多种因素,提出基于网络编码多维终端特征权重模型的系统接入时间分配机制FDMW.FDMW构建终端编码集合信道多维特征权重模型,自适应调整系统接入时间分配决策.理论和仿真证明,FDMW能够动态优化接入时间,有效提升系统整体传输效率.     

A decision support system for spare parts management in a waferfabrication facility

We present a decision support system for spare parts management in a wafer fabrication facility. The system is based on an analytical stochastic inventory model, which calculates the reorder level and quantity for each part to attain a specified service level. Results from our simulation study indicate that the policies suggested by the system either improve the service level or reduce the operating cost     

基于数据仓库的高校数据统计服务平台研究

为了适应新形势下高校对大数据统计、分析的需求,设计实现了一套基于数据仓库的高校数据统计服务平台的整体方案。对高校数据仓库的整体架构、数据仓库的建模进行了研究,并设计了一种基于数据仓库星型结构的统计数据模型;进一步探讨了统计服务平台在实现过程中ETL(extraction transformation loading)以及界面设计等方面的关键技术;为高校下一步搭建管理与决策支持平台提供了重要的实践基础和理论支撑。     

Modeling search in group decision support systems

Groups using group decision support systems (GDSS) to address particular tasks can be viewed as performing a search. Such tasks involve arriving at a solution or decision within the context of a complex search space, warranting the use of computerized decision support tools. The type of search undertaken by the groups appears to be a form of adaptive, rather than enumerative, search. Recently, efforts have been made to incorporate this adaptation into an analytical model of GDSS usage. One possible method for incorporating adaptation into an analytical model is to use an evolutionary algorithm, such as a genetic algorithm (GA), as an analogy for the group problem-solving process. In this paper, a test is made to determine whether GDSS behaves similarly to a GA process utilizing rank selection, uniform crossover, and uniform mutation operators. A Markov model for GAs is used to make this determination. Using GDSS experimental data, the best-fit transition probabilities are estimated and various hypotheses regarding the relation of GA parameters to GDSS functionality are proposed and tested. Implications for researchers in both GAs and group decision support systems are discussed.     

电力企业客户服务辅助决策支持系统的设计与实现

针对目前电力系统营销域中客户服务的数据进行分析,设计开发了一套辅助决策支持系统,从数据存储、应用支持、数据分析等方面进行设计与实现,业务涵盖了服务渠道使用情况分析和应用、95598坐席人员分析、IVR服务路径分析、客户细分深化应用。论文简要分析了目前电网企业在营销域决策支持系统的现状,阐述了营销域决策支持系统的总体架构,并对系统关键功能和技术进行了详细介绍,最后给出该系统在企业的实际应用情况。     

一种混合式协作过滤服务推荐算法

随着电子商务的飞速发展,服务推荐系统的重要性越来越得到体现。服务推荐技术作为电子商务的重要应用技术之一,为用户正确的决策提供有力的支持和保证。传统的基于协作过滤的服务推荐算法存在无法进行双向推荐的弊端,同时推荐质量有待提高。针对这些不足,提出了一种基于混合式协作过滤的服务推荐算法,考虑用户和服务之间的相似度,实现了双向推荐。实验结果表明,该算法能有效提高推荐质量。     

基于互补谓词的编译优化

许多通用和嵌入式高性能处理器都支持谓词执行,利用谓词执行可以简化程序的控制结构,而且指令调度、寄存器分配也可以利用谓词提高效率.基于二进制决策图(BDD)的谓词分析系统,提出了一种利用互补谓词机制对控制结构进行优化的方法;对传统着色图寄存器分配算法进行改进,给出了一种利用互补谓词机制建立统一简化干涉图的新算法,减少了代码溢出;利用互补谓词的特性指导指令调度,使之更加有效利用资源,并对目标体系结构进行了改进以支持指令调度.最后在YHFT-DSP/700芯片的编译器上对所提优化方法的有效性进行了验证.     

Home Health Gateway Based Healthcare Services Through U-Health Platform

The Ubiquitous Health, or u-Health, service is an IT health care service using the ubiquitous computing environment. U-Health provides customized medical services. As it is a service that has developed from the current hospital visiting medical system, the u-Health service provides a patient with healthcare anywhere and anytime. In this paper, we propose a home health gateway based healthcare services through the u-Health platform. Using home health gateway, u-Health can provide health monitoring, diet, and exercise services using the healthcare decision support module in the ubiquitous environment. This approach would offer specialized services using an external content provider of DB. In addition, a doctor can provide advice to patients using the monitoring service. The proposed u-Health platform provides effective services using home health gateway in ubiquitous environments to customers, which will improve the health of chronic patients.     

Symmetric routing in DHT overlays

In this paper, we propose to extend the DHT topology to a bidirectional graph to provide a super-peer based lookup algorithm and a scalable search support. We consider routing algorithms for a bidirectional variant of the DHT network and show how the resulting structure extends the search region and provides an efficient resource lookup service at a very little additional cost.     

一种基于OLAP的相关分析算法

数据挖掘算法Apriori在处理关联规则分析时,当项目集很多、数据立方体很稠密时回溯的次数急剧增加。本文结合一个黑龙江企业信息网的数据仓库给出了一个改进算法,该算法对数据分布稠密的数据立方体具有很好的效果。证实该方法可以提供给高层决策者完整、及时、准确、立体多方位的决策信息,达到了提供全面决策支持服务的目的。     

Optimal Resource Allocation for Maximizing Performance and Reliability in Tree-Structured Grid Services

The paper considers a grid computing systems in which the resource management systems (RMS) can divide service tasks into execution blocks (EB), and send these blocks to different resources. To provide a desired level of service reliability, the RMS can assign the same EB to several independent resources for parallel (redundant) execution. According to the optimal schedule for service task partition, and distribution among resources, one can achieve the greatest possible expected service performance (i.e. least execution time), or reliability. For solving this optimization problem, the paper suggests an algorithm that is based on graph theory, Bayesian approach, and the evolutionary optimization approach. A virtual tree-structure model is constructed in which failure correlation in common communication channels is taken into account. Illustrative examples are presented.     

Towards an event-aware approach for ubiquitous computing based on automatic service composition and selection

Service composition in ubiquitous and pervasive environments is becoming an active research domain which has received widespread attention in recent years. It aims to offer seamless access to a variety of high level and complex functionalities by combining existing services. Several frameworks have been designed to support service composition in ubiquitous and pervasive environments. Although some ubiquitous requirements and challenges are relatively well addressed by the proposed frameworks, others are still at a preliminary stage and should be well explored such as, automatic service composition with little human intervention, context and quality of service management, and service selection under uncertainty and changes. For this end, we propose in this paper a layered design approach for flexible and failure tolerant service composition using two main phases: off-line phase and on-line phase. In the off-line phase, a global graph that links all the available abstract services is generated automatically using rule-based technique. The defined rules aim at optimizing both the number of services and parameters that appear in the global graph. In the on-line phase, a subgraph is extracted spontaneously from the global graph according to the occurred and detected event in the environment at real time. Thereafter, the extracted subgraph is performed using service selection strategies. A prototype implementation including real services for event detection in smart home shows clearly the feasibility of the proposed approach in real environment. Also, the set of performed evaluation tests reveals the interest and the performance of the proposed algorithms.     

基于DT-KSVM的业务感知算法

提出一种新的基于DT-KSVM（decision tree kernel support vector machine,决策树支持向量机）的业务感知算法,利用ReliefF特征选择算法提取特征,提出样本间类别可分度计算方法排序不同业务感知难度,优先感知易分业务。在实际网络业务数据集上与传统一对一（one-versus-one）SVM感知方法进行对比,结果表明该方法具有较高的业务识别准确率和更好的时间性能。     

面向服务可靠性的云资源调度方法

随着云计算成为重要的信息基础设施,越来越多的应用迁移到云上,云服务的可靠性日益重要,尤其是边缘计算新模式的引入,对云服务可靠性提出了更高的要求.如何通过资源调度保障服务可靠性成为了当前研究的热点.为此,针对云-边协同的应用场景,开展面向服务可靠性的云资源调度方法研究,提出基于马尔科夫预测模型的云资源调度算法,实现节点负载判断、待迁移任务和节点选择、迁移路由的决策,以解决云服务节点失效情况下的任务调度和负载均衡问题,实现快速的云服务故障恢复,提高云服务的可靠性.实验结果表明,本文所提方法能够有效保证节点失效情况下的服务可靠性.     

Remote patient monitoring service using heterogeneous wireless access networks: architecture and optimization

Remote patient monitoring is an eHealth service, which is used to collect and transfer biosignal data from the patients to the eHealth service provider (e.g., healthcare center). A heterogeneous wireless access-based remote patient monitoring system is presented in which multiple wireless technologies are integrated to support continuous biosignal monitoring in presence of patient mobility. A patient-attached monitoring device with a heterogeneous wireless transceiver collects biosignal data from the sensors and transmits the data through the radio access network (RAN) to the eHeath service provider. In this system, the eHealth service provider reserves wireless bandwidth (or connections) from a network service provider in a proactive manner as well as in an on-demand basis. To determine the optimal number of connections to be reserved pro-actively so that the network access cost is minimized, a stochastic programming problem is formulated considering the randomness of service demand due to the mobility of the patients. Since different biosignal data can have different quality-of-service (QoS) requirements, traffic scheduling is used in the patient-attached device which determines whether to transmit and what to transmit over an available wireless connection. To make the optimal scheduling decision, an optimization problem is formulated as a constrained Markov decision process (CMDP). The objective of this formulation is to minimize the connection cost. The proposed system architecture and the optimization formulations will be useful for the eHealth service provider to provide flexible and cost-effective monitoring service to remote/mobile patients.