PerfMon: Measuring Application-Level Performance in a Large-Scale Campus Wireless Network

WiFi has become one of the most popular ways to access the Internet.However,in large-scale campus wireless networks,it is challenging for network administrators to provide optimized access quality without knowledge on fine-grained traffic characteristics and real network performance.In this paper,we implement PerfMon,a network performance measurement and diagnosis system,which integrates collected multi-source datasets and analysis methods.Based on PerfMon,we first conduct a comprehensive measurement on application-level traffic patterns and behaviors from multiple dimensions in the wireless network of T university(TWLAN),which is one of the largest campus wireless networks.Then we systematically study the application-level network performance.We observe that the application-level traffic behaviors and performance vary greatly across different locations and device types.The performance is far from satisfactory in some cases.To diagnose these problems,we distinguish locations and device types,and further locate the most crucial factors that affect the performance.The results of case studies show that the influential factors can effectively characterize performance changes and explain for performance degradation.

Research on strategic risk identification method of equipment system development based on system dynamics

Strategic management of equipment system develop-ment must attach importance to effective strategic risk manage-ment.Aiming at the identification of strategic risk of equipment system development,firstly,the source of strategic risk of equip-ment system development is analyzed and classified.Based on this,a causal loop diagram of strategic risk of equipment sys-tem development based on system dynamics is established.The system dynamics analysis software Vensim PLE is used to carry out the risk influencing factors analysis,risk consequences ana-lysis,risk feedback loop identification and corresponding pre-control measures,and achieves a good risk identification effect.

A Privacy-Based SLA Violation Detection Model for the Security of Cloud Computing

A Service Level Agreement(SLA) is a legal contract between any two parties to ensure an adequate Quality of Service(Qo S). Most research on SLAs has concentrated on protecting the user data through encryption. However, these methods can not supervise a cloud service provider(CSP) directly. In order to address this problem, we propose a privacy-based SLA violation detection model for cloud computing based on Markov decision process theory. This model can recognize and regulate CSP's actions based on specific requirements of various users. Additionally, the model could make effective evaluation to the credibility of CSP, and can monitor events that user privacy is violated. Experiments and analysis indicate that the violation detection model can achieve good results in both the algorithm's convergence and prediction effect.

THE SPILLOVER MANAGEMENT IN THE DYNAMIC OUTPUT FEEDBACK CONTROL OF FLEXIBLE SPACECRAFT

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Renewable and Storage Energy Integration for Smart Grid Housing

This paper presents the design, implementation and testing of an embedded system that integrates solar and storage energy resources to smart homes within the smart mierogrid. The proposed system provides the required home energy by installing renewable energy and storage devices. It also manages and schedules the power flow during peak and off-peak periods. In addition, a two-way communication protocol is developed to enable the home owners and the utility service provider to improve the energy flow and the consumption efficiency. The system can be an integral part for homes in a smart grid or smart microgrid power networks. A prototype for the proposed system was designed, implemented and tested by using a controlled load bank to simulate a scaled random real house consumption behavior. Three different scenarios were tested and the results and findings are reported. Moreover, data flow security among the home, home owners and utility server is developed to minimize cyber-attaeks.

Research on Supplier Relationship Management of the Main Manufacturer of Large Aircraft Project:A Psychological Contract Perspective

The main manufacturer and its suppliers＇ relationship management is very important for success of the large aircraft project. The study concentrates on analysis of the relationship management on a psychological con- tract perspective, shows that constructing good psychological contract is useful to promote mutual trust, reduce the transaction cost caused by incompleteness of formal contract, avoid the risk of supplier management between the main manufacturer and suppliers of the large aircraft project. And with further understanding of the dynamic contracting process as well as formation framework of psychological contract between the main manufacturer and suppliers, we can better understand the relationship black-box and provide a new perspective for the study of the relationship management, then given some constructive suggestions to supplier relationship management.

Configuration Reusing in On-Line Task Scheduling for Reconfigurable Computing Systems

Reconfigurable computing systems can be reconfigured at runtime and support partial reconfigurability which makes us able to execute tasks in a true multitasking manner. To manage such systems at runtime, a reconfigurable operating system is needed. The main part of this operating system is resource management unit which performs on-line scheduling and placement of hardware tasks at runtime. Reconfiguration overhead is an important obstacle that limits the performance of on-line scheduling algorithms in reconfigurable computing systems and increases the overall execution time. Configuration reusing （task reusing） can decrease reconfiguration overhead considerably, particularly in periodic applications or the applications in which the probability of tasks recurrence is high. In this paper, we present a technique called reusing-based scheduling （RBS）, for on-line scheduling and placement in which configuration reusing is considered as a main characteristic in order to reduce reconfiguration overhead and decrease total execution time of the tasks. Several experiments have been conducted on the proposed algorithm. Obtained results show considerable improvement in overall execution time of the tasks.

An approach to calculating allowable watershed pollutant loads

To improve the management of discharge pollutants loads in the reservoirs＇ watershed, an approach of the allowable pollutants loads calculation and its allocation, based on the water environment model, was proposed. Establishment of the approach framework was described at first. Under the guidance of this framework, two major steps were as follows： modeling and scenario analysis were involved and should be applied to support the decision of discharge loads management; Environ- mental Fluid Dynamic Code （EFDC） model was selected as the kernel model in this framework. In modeling step, spatial discretization for establishing cell map in model, data preprocessing, parameter calibration and uncertainty analysis （which is considered as the significantly relevant factor of the margin of safety （MOS））, were conducted. As a result of the research, the model-based approach presented as a combination of estimation and precise calculation, which contributed to scenario analysis step. Some integrated modules, such as scenario simulation, result analysis and plan optimization were implemented as cycles in the scenario analysis. Finally, allowable pollutant loads under various conditions were calculated. The Chaihe Reservoir in Liaoning Province, China was used as a case study for an application of the approach described above. Results of the Chaihe reservoir water quality simulation, show good agreement with field data and demonstrated that the approach used in the present study provide an efficient and appropriate methodology for pollutant load allocation.

An inexact risk management model for agricultural land-use planning under water shortage

Water resources availability has a significant impact on agricultural land-use planning, especially in a water shortage area such as North China. The random nature of available water resources and other uncertainties in an agricultural system present risk for land-use planning and may lead to undesirable decisions or potential economic loss. In this study, an inexact risk management model （IRM） was developed for supporting agricultural land-use planning and risk analysis under water shortage. The IRM model was formulated through incorporating a conditional value-at-risk （CVaR） constraint into an inexact two-stage stochastic programming （ITSP） framework, and could be used to control uncertainties expressed as not only probability distributions but also as discrete intervals. The measure of risk about the second-stage penalty cost was incorporated into the model so that the trade-off between system benefit and extreme expected loss could be analyzed. The developed model was applied to a case study in the Zhangweinan River Basin, a typical agricultural region facing serious water shortage in North China. Solutions of the IRM model showed that the obtained first-stage land-use target values could be used to reflect decision-makers＇ opinions on the long-term devel- opment plan. The confidence level a and maximum acceptable risk loss fl could be used to reflect decision- makers＇ preference towards system benefit and risk control. The results indicated that the IRM model was useful for reflecting the decision-makers＇ attitudes toward risk aversion and could help seek cost-effective agricul- tural land-use planning strategies under complex uncer- tainties.

An interval joint-probabilistic programming method for solid waste management： a case study for the city of Tianjin, China

Currently, environmental protection and resources conservation continue to be challenges faced by solid-waste managers in China. These challenges are being further compounded by rapid socioeconomic devel- opment and population growth associated with increased waste generation rates and decreased waste disposal capacities. In response to these challenges, an interval joint-probabilistic mixed-integer programming （IJMP） method is developed for supporting long-term planning of waste management activities in the city of Tianjin, which is one of the largest municipalities in the northern part of China. In the IJMP, joint probabilistic constraints are introduced into an interval-parameter mixed-integer programming framework, such that uncertainties presented in terms of interval values and random variables can be reflected. Moreover, a number of violation levels for the waste-management-capacity constraints are examined, which can facilitate in-depth analyses of tradeoffs among economic objective and system-failure risk. The results indicate that reasonable solutions have been generated. They are valuable for supporting the adjustment of the city＇s existing waste-management practices and the long- term planning of the city＇s waste-management facilities.

Research on low carbon management using a scientific classification method

This research is aimed at the rapid development of a low-carbon economy, in which we propose the classification and application of relevant management measures to affect the development of environmental management ideas and measures of the low-carbon economy, which we called as low carbon management measures. According to scientific analysis of the lowcarbon economy, we can divide low-carbon management measures into three parts： measures for reduction of carbon sources, carbon flow planning, and increase of carbon sinks. Furthermore, we list the advantages that China can utilize to develop its own low-carbon management measures. In the end, necessary adjustments to environmental management measures in China can be made according to this scientific classification.

Joint admission control algorithm in access network

To deal with long probing delay and inaccurate probing results in the endpoint admission control method,a joint local and end-to-end admission control algorithm is proposed,which introduces local probing of access net-work besides end-to-end probing.Through local probing,the algorithm accurately estimated the resource status of the access network.Simulation shows that this algorithm can improve admission control performance and reduce users’average waiting time when the access network is heavily loaded.