Less conservative stability criteria for linear systems with interval time‐varying delays

The problem of the stability of a linear system with an interval time‐varying delay is investigated. A new Lyapunov–Krasovskii functional that fully uses information about the lower bound of the time‐varying delay is constructed to derive new stability criteria. It is proved that the proposed Lyapunov–Krasovskii functional can lead to less conservative results than some existing ones. Based on the proposed Lyapunov–Krasovskii functional, two stability conditions are developed using two different methods to estimate Lyapunov–Krasovskii functional's derivative. Two numerical examples are given to illustrate that the two stability conditions are complementary and yield a larger maximum upper bound of the time‐varying delay than some existing results. Copyright © 2013 John Wiley & Sons, Ltd.     

Recover Fault Services via Complex Service-to-Node Mappings in Wireless Sensor Networks

With the motivation of seamlessly extending wireless sensor networks to the external environment, service-oriented architecture comes up as a promising solution. However, as sensor nodes are failure prone, this consequently renders the whole wireless sensor network to seriously faulty. When a particular node is faulty, the service on it should be migrated into those substitute sensor nodes that are in a normal status. Currently, two kinds of approaches exist to identify the substitute sensor nodes: the most common approach is to prepare redundancy nodes, though the involved tasks such as maintaining redundancy nodes, i.e., relocating the new node, lead to an extra burden on the wireless sensor networks. More recently, other approaches without using redundancy nodes are emerging, and they merely select the substitute nodes in a sensor node’s perspective i.e., migrating the service of faulty node to it’s nearest sensor node, though usually neglecting the requirements of the application level. Even a few work consider the need of the application level, they perform at packets granularity and don’t fit well at service granularity. In this paper, we aim to remove these limitations in the wireless sensor network with the service-oriented architecture. Instead of deploying redundancy nodes, the proposed mechanism replaces the faulty sensor node with consideration of the similarity on the application level, as well as on the sensor level. On the application level, we apply the Bloom Filter for its high efficiency and low space costs. While on the sensor level, we design an objective solution via the coefficient of a variation as an evaluation for choosing the substitute on the sensor level.     

Novel neural network modeling method and applications

Neural networks play an important role for designing the parametric model of electromagnetic structures. The current neural network methods are unfit for a circuit model with many input variables because it is costly to extract a large number of the training data and test data to complete the highly nonlinear mapping approximation. This article proposes a new neural network modeling method—the multidimensional neural network model, which can be used to solve the issue of multivariable radiofrequency and microwave passive device modeling. The entire multidimensional neural network modeling problem is simplified into a set of neural network submodels through decomposition method. Then the submodels are combined into an equivalent model, and the final entire model is produced through the neural‐network mapping model developed with the submodels and equivalent model. A microstrip hairpin filter model is developed using the proposed method. The simulation results show the correctness and the effectivity of the proposed method. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:769–779, 2015.     

Tree-based data retrieval algorithm for multi-item request with deadline in wireless networks

The data retrieval problem in wireless communication has attracted increasing attentions in many applications such as electronic information sharing and e-business. However, most existing studies do not consider how to retrieve the requested data items in their deadlines. In this paper, we discuss the so-called deadline-based multi-item data retrieval problem, which aims at finding an access pattern for retrieving requested data items in certain deadlines such that the access latency and data miss rate are minimized. We propose two algorithms, named EDFS and UR, to deal with the above problem. The EDFS algorithm gives priority to retrieve the requested data item with the least deadline, while the UR algorithm introduces the urgent rate that is computed by the broadcast time and deadline of requested data item for further reducing the access latency and data miss ratio. Moreover, we design a tree-based data retrieval algorithm that finds the longest downloading sequence of data items in one broadcast cycle and is applied to EDFS and UR for finding data retrieval sequence of requested data items. The efficiency of our proposed schemes has been validated by the extensive experiments.     

A virtual service placement approach based on improved quantum genetic algorithm

Despite the critical role that middleboxes play in introducing new network functionality, management and innovation of them are still severe challenges for network operators, since traditional middleboxes based on hardware lack service flexibility and scalability. Recently, though new networking technologies, such as network function virtualization (NFV) and software-defined networking (SDN), are considered as very promising drivers to design cost-efficient middlebox service architectures, how to guarantee transmission efficiency has drawn little attention under the condition of adding virtual service process for traffic. Therefore, we focus on the service deployment problem to reduce the transport delay in the network with a combination of NFV and SDN. First, a framework is designed for service placement decision, and an integer linear programming model is proposed to resolve the service placement and minimize the network transport delay. Then a heuristic solution is designed based on the improved quantum genetic algorithm. Experimental results show that our proposed method can calculate automatically the optimal placement schemes. Our scheme can achieve lower overall transport delay for a network compared with other schemes and reduce 30% of the average traffic transport delay compared with the random placement scheme.     

天津市水功能区划要求下海河干流排涝问题研究

按新的海河干流水功能区划要求,海河干流将不再承担上游来水的行洪任务。因而有必要分析探讨新形势下海河干流的排涝问题。在充分考虑海河干流水功能区划要求的基础上,通过推求设计暴雨、进行产汇流计算,建立海河干流汇水区一维水动力模型,模拟了海河干流在经历不同重现期(3年、5年及10年一遇)设计暴雨下的排涝水位。在此基础上,对多种排涝方案进行比选,给出了适当的排涝方案,以缓解水功能区划要求下天津市海河干流的排涝矛盾。     

灌溉结合发电水库调度图编制的改进算法研究

在使用《水利工程水利计算规范》(SL 104—95)编制灌溉结合发电水库综合调度图的过程中,对初步计算结果进行反复检验和修改后仍难以准确符合设计要求。为解决这一问题,提出了改进限制灌溉线、灌溉防破坏线的计算方法,协调了限制灌溉区、保证灌溉区、灌溉发电共同保证区之间的关系,统一了年调节与多年调节水库调度图的计算方法,并用系列年代替了典型年。结果表明:采用改进方法计算和编制的综合调度图可以一次性通过检验,无需进行修改;按改进方法编制的调度图进行长系列径流调节计算,可以准确地符合灌溉和发电的各种设计要求,提高时历法编制综合调度图的理论合理性和实用价值。     

非一致性条件下城市设计洪水的计算方法

在分析城市化后产流变化的基础上,可采用平均洪量模数增量修正设计洪峰频率曲线的均值,进而推算城市化后的设计洪峰流量,以宝象河流域为实例进行了验证。结果表明:该算法具有合理性,以实测洪水资料为基础进行的非一致性条件下的设计洪水计算结果比基于设计暴雨推求设计洪水的误差更小。     

宽尾墩对跌坎底流消力池影响的试验研究

针对低水头、大单宽流量、下游水位变幅大的水电站中的泄洪消能问题,本文结合官地水电站工程进行了水工模型试验研究,从消力池的水流流态、临底流速以及底板时均动水压强对比几方面,分析了宽尾墩对跌坎底流消力池的影响。结果表明,宽尾墩改善了消力池内的水流流态,降低了消力池内的临底流速和时均压强,充分利用了宽尾墩技术优势,提高了泄洪设施的总消能率,有效解决了下游水位变幅较大的水电工程类泄洪消能问题。     

珠江口咸潮影响因素分析

对珠江口平岗泵站和联石湾水闸两个代表站咸潮与流量、潮差、潮水位、海平面、气象等影响因素的响应规律采用集对分析和非参相关分析方法进行了研究,结果表明:1珠江口咸潮的主要影响因素为流量、最低潮位和海平面,潮差、风级为次要影响因素;2平岗泵站和联石湾水闸咸潮对各影响因素的敏感性具有差异性,平岗泵站咸湖对流量更敏感,联石湾水闸咸潮对海平面、最低潮位、潮差和最高潮位的敏感性大于平岗泵站;3未来全球气候还将持续变暖,珠江流域枯水径流变化复杂,珠江口海平面上升速度在加快,应加强珠江口咸潮变化机理的研究。