Resource Partitioning and Routing Optimization in Relay Enhanced Cellular Network

A joint routing and resource partitioning scheme were proposed to improve cell capacity and user throughput of cellular network enhanced with two-hop fixed relay nodes (FRNs). Radio resources are partitioned under a reuse partitioning based framework, which guarantees effective and efficient inter-cell interference management. At the same time, each mobile terminal was assigned a channel-dependent route by the routing controller, which tries to maximize the cell capacity under the constraint imposed by reuse partitioning. Intensive computer simulations demonstrate the performance superiority of the FRN enhanced cellular network employing this scheme in comparison with conventional network, as well as the validity of the channel-dependent routing mechanism.

Clustering in Wireless Multimedia Sensor Networks Using Spectral Graph Partitioning

Wireless multimedia sensor network (WMSN) consists of sensors that can monitor multimedia data from its surrounding, such as capturing image, video and audio. To transmit multimedia information, large energy is required which decreases the lifetime of the network. In this paper we present a clustering approach based on spectral graph partitioning (SGP) for WMSN that increases the lifetime of the network. The efficient strategies for cluster head selection and rotation are also proposed.

Reuse Partitioning-Based Frequency Assignment in Fixed Two-Hop Relay Cellular Network

In relay cellular network, relay links will consume extra frequency resources, which makes radio resource allocation become more complex and important. A new frequency allocation scheme is proposed to increase cell capacity and improve signal-to-interference ratio (SIR) of users located at cell edges. By dividing cell into different parts and configuring each of these parts with a unique reuse factor, this scheme improves spectral utilization efficiency and avoids inter-cell interference effectively. Optimal combinations of reuse factors and locations of relay nodes are also addressed and investigated. Computer simulation results show that, by employing the proposed scheme, maximum cell capacity gains of about 50%, 35% and 30% can be achieved in comparison with conventional cellular network scheme, traditional reuse partitioning scheme and reuse-adjacent-cell-frequencies scheme, respectively. Moreover, since in the proposed scheme resources are dynamically allocated among relay nodes, more benefits can be obtained in comparison with fixed resource allocation schemes under non-uniform traffic distribution.

Impact of joint resource partitioning and routing on performance of relay enhanced cellular networks

Radio resource assignment schemes and routing strategies in relay enhanced cellular networks are proposed in this paper. Under the reuse partitioning-based frequency planning framework, the intra-cell resource partitioning between the base station and relay nodes was addressed firstly by introducing a metric of effective reuse factor. Then, coverage-oriented and capacity-oriented rantings, as well as two link bandwidth assignment schemes＂ equal-bandwidth per link＂ and ＂equal-bandwidth per mobile station＂ were developed. These key issues and their impacts on the system performance were analyzed comprehensively and supported by simulations. Results show that the cell capacity and edge user throughput of the proposed network are superior to the traditional non-relay network when an appropriate effective reuse factor is adopted.

Alloy gene Gibbs energy partition function and equilibrium holographic network phase diagrams of AuCu_3-type sublattice system

Taking AuCu3-type sublattice system as an example, three discoveries have been presented: First, the third barrier hindering the progress in metal materials science is that researchers have got used to recognizing experimental phenomena of alloy phase transitions during extremely slow variation in temperature by equilibrium thinking mode and then taking erroneous knowledge of experimental phenomena as selected information for establishing Gibbs energy function and so-called equilibrium phase diagram. Second, the equilibrium holographic network phase diagrams of AuCu3-type sublattice system may be used to describe systematic correlativity of the composition?temperature-dependent alloy gene arranging structures and complete thermodynamic properties, and to be a standard for studying experimental subequilibrium order-disorder transition. Third, the equilibrium transition of each alloy is a homogeneous single-phase rather than a heterogeneous two-phase, and there exists a single-phase boundary curve without two-phase region of the ordered and disordered phases; the composition and temperature of the top point on the phase-boundary curve are far away from the ones of the critical point of the AuCu3 compound.

Alloy gene Gibbs energy partition function and equilibrium holographic network phase diagrams of Au_3Cu-type sublattice system

Taking Au3Cu-type sublattice system as an example, three discoveries have been presented. First, the fourth barrier to hinder the progress of metal materials science is that today’s researchers do not understand that the Gibbs energy function of an alloy phase should be derived from Gibbs energy partition function constructed of alloy gene sequence and their Gibbs energy sequence. Second, the six rules for establishing alloy gene Gibbs energy partition function have been discovered, and it has been specially proved that the probabilities of structure units occupied at the Gibbs energy levels in the degeneracy factor for calculating configuration entropy should be degenerated as ones of component atoms occupied at the lattice points. Third, the main characteristics unexpected by today’s researchers are as follows. There exists a single-phase boundary curve without two-phase region coexisting by the ordered and disordered phases. The composition and temperature of the top point on the phase-boundary curve are far away from those of the critical point of the Au3Cu compound; At 0 K, the composition of the lowest point on the composition-dependent Gibbs energy curve is notably deviated from that of the Au3Cu compounds. The theoretical limit composition range of long range ordered Au3Cu-type alloys is determined by the first jumping order degree.

Research on reliability index of a large communication network with domain partition and interconnection

In order to indicate the performances of a large-scale communication network with domain partition and interconnection today, a kind of reliability index weighed by normalized capacity is defined. Based on the route rules of network with domain partition and interconnection, the interconnection indexes among the nodes within the domain and among the domains are given from several aspects. It is expatiated on that the index can thoroughly represent the effect on the reliability index of the objective factor and the subjective measures of the designer, which obeys the route rules of a network with domain partition and interconnection. It is discussed that the defined index is rational and compatible with the traditional index.

Partition coefficient prediction of Baker's yeast invertase in aqueous two phase systems using hybrid group method data handling neural network

A hybrid GMDH neural network model has been developed in order to predict the partition coefficients of invertase from Baker's yeast. ATPS experiments were carried out changing the molar average mass of PEG(1500–6000 Da), p H(4.0–7.0), percentage of PEG(10.0–20.0 w/w), percentage of MgSO_4(8.0–16.0 w/w), percentage of the cell homogenate(10.0–20.0 w/w) and the percentage of MnSO_4(0–5.0 w/w) added as cosolute. The network evaluation was carried out comparing the partition coefficients obtained from the hybrid GMDH neural network with the experimental data using different statistical metrics. The hybrid GMDH neural network model showed better fitting(AARD = 32.752%) as well as good generalization capacity of the partition coefficients of the ATPS than the original GMDH network approach and a BPANN model. Therefore hybrid GMDH neural network model appears as a powerful tool for predicting partition coefficients during downstream processing of biomolecules.

Dynamic Nodes Partition Algorithm for Ad HOC Network

A dynamic nodes partition algorithm for the Ad Hoc network is proposed. Firstly, Roam cluster method is used to cluster 926 random nodes in a square region. Subsequently, the central moving model based on the simulated annealing algorithm and the least circle overlay model is constructed to remove the network redundancy of the circle number and circle radius respectively. Simulation results show that the algorithm can effectively maintain the stability of network structure and increase balancing capabilities of Ad Hoc network load. The future work is to study how to improve the adaptability for the application in the complicated areas.

System Vulnerability Analysis Using Graph Pathfinding Strategies in Partitioned Networks

In this paper, a new method has been introduced to find the most vulnerable lines in the system dynamically in an interconnected power system to help with the security and load flow analysis in these networks. Using the localization of power networks, the power grid can be divided into several divisions of sub-networks in which, the connection of the elements is stronger than the elements outside of that division. By using our proposed method, the probable important lines in the network can be identified to do the placement of the protection apparatus and planning for the extra extensions in the system. In this paper, we have studied the pathfinding strategies in most vulnerable line detection in a partitioned network. The method has been tested on IEEE39-bus system which is partitioned using hierarchical spectral clustering to show the feasibility of the proposed method.

Fast CU Partition for VVC Using Texture Complexity Classification Convolutional Neural Network

Versatile video coding(H.266/VVC),which was newly released by the Joint Video Exploration Team(JVET),introduces quad-tree plus multitype tree(QTMT)partition structure on the basis of quad-tree(QT)partition structure in High Efficiency Video Coding(H.265/HEVC).More complicated coding unit(CU)partitioning processes in H.266/VVC significantly improve video compression efficiency,but greatly increase the computational complexity compared.The ultra-high encoding complexity has obstructed its real-time applications.In order to solve this problem,a CU partition algorithm using convolutional neural network(CNN)is proposed in this paper to speed up the H.266/VVC CU partition process.Firstly,64×64 CU is divided into smooth texture CU,mildly complex texture CU and complex texture CU according to the CU texture characteristics.Second,CU texture complexity classification convolutional neural network(CUTCC-CNN)is proposed to classify CUs.Finally,according to the classification results,the encoder is guided to skip different RDO search process.And optimal CU partition results will be determined.Experimental results show that the proposed method reduces the average coding time by 32.2%with only 0.55%BD-BR loss compared with VTM 10.2.

基于重叠社区划分和非回溯矩阵的社交网络多源点检测

在线社交网络的发展为信息传播提供了极大的便利,但同时在一定程度上也成为谣言等信息的重要传播渠道。社交网络的信息源检测对于控制信息的传播起着重要作用。为了解决现有社交网络多源点检测方法准确度不够高的问题,提出了一种新颖的多源点同步检测方法SVT-BiasMSI。该方法将多源检测问题转化为若干单源检测问题,采用局部度中心节点及相邻节点的Jaccard系数选取种子节点,使用Voronoi方法对社交网络进行初步社区划分,通过tolerance neighborhood方法寻找分区之间重叠部分的节点并实现重叠社区划分,为了兼顾网络全局和局部信息,基于传染邻域偏差改进非回溯矩阵多源点检测方法,提高单源点检测精度。在多个社交网络数据集中的实验表明,所提的方法能够有效提高在线社交网络多源点检测和定位准确度。

分区监测诊断方法在城镇排水管网排查中的应用研究

为揭示城镇排水管网系统存在的问题,提高排水管网的管理水平,基于划分监测诊断单元,以某城市污水处理厂为例,采用在线监测技术,运用水量平衡关系核算、水质拓扑关系分析、旱天基本入渗分析等方法开展应用研究,定量评估排水管网的运行状况,对排水管网运行情况进行系统性诊断,评估排水管网的健康状态。结果表明:针对入流、入渗非常严重的片区,对片区的入流、入渗情况复核结果与前期评估结果一致,说明城镇排水管网分区诊断技术在管网排查工作中具有较好的借鉴作用。该研究成果可为开展管网修复和设施改造工作奠定基础。

基于改进K-means聚类算法的分布式储能集群划分方法

随着规模化分布式电源及储能的接入,配电网的功率返送、节点过电压等问题愈加显著,对电网规划、运行监视和调度控制等造成一定影响,也不利于储能大范围发展。为此提出一种适用于规模化分布式储能的集群划分方法,基于功率节点电压灵敏度的电气距离模块度指标,对经典K-means算法进行改进,设计节点指数法、肘部法则优化初始聚类中心选择和集群数确定。以IEEE33系统算例进行验证,结果表明所提集群划分方法具有较强的电气耦合性、准确性和运算效率。

Reactor Network Synthesis Based on Instantaneous Objective Function Characteristic Curves

It is believed that whether the instantaneous objective function curves of plug-flow-reactor (PFR) and continuous-stirred-tank-reactor (CSTR) overlap or not, they have a consistent changing trend for complex reactions (steady state, isothermal and constant volume). As a result of the relation of the objective functions (selectivity or yield) to the instantaneous objective functions (instantaneous selectivity or instantaneous reaction rate), the optimal reactor network configuration can be determined according to the changing trend of the instantaneous objective function curves. Further, a recent partition strategy for the reactor network synthesis based on the instantaneous objective function characteristic curves is proposed by extending the attainable region partition strategy from the concentration space to the instantaneous objective function-unreacted fraction of key reactant space. In this paper, the instantaneous objective function is closed to be the instantaneous selectivity and several samples are examined to illustrate the proposed method. The comparison with the previous work indicates it is a very convenient and practical systematic tool of the reactor network synthesis and seems also promising for overcoming the dimension limit of the attainable region partition strategy in the concentration space.

Betweenness-based algorithm for a partition scale-free graph

Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom-up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top-down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches.

New Network Immunization Strategy ~tter than the EGP Strategy

This paper aims at designing a better net-work i,,imozatopm strategy to fight against the Sus- ceptible-Infected-Susceptible （SIS） type epidemic spreading in networks. Previous work used the nurrber of drops in the spectral radius of the net-work for evaluation and guiding the design of im-munization strategies. Instead, we propose using the infected node number in the steady state of SIS spreading as the appropriate metric. We use the metric to point out the limitations of the Equal Graph Partitioning （EGP） strategy and the ＂max-△λ＂ strategy, which are two representative network inmmnization strategies, and then identify the criti-cal role of epidemic spreading parameters in the e-valuation and design of network immuzization strat- egies. Based on all of these, we design a new immuzization strategy. Simulation results show that our strategy performs consistently better than the EGP strategy. In many cases, it uses only 50% less re-sources to achieve the same immuzization effect.

Clustering in Wireless Multimedia Sensor Networks

Wireless Multimedia Sensor Networks (WMSNs) are comprised of small embedded audio/video motes capable of extracting the surrounding environmental information, locally processing it and then wirelessly transmitting it to sink/base station. Multimedia data such as image, audio and video is larger in volume than scalar data such as temperature, pressure and humidity. Thus to transmit multimedia information, more energy is required which reduces the lifetime of the network. Limitation of battery energy is a crucial problem in WMSN that needs to be addressed to prolong the lifetime of the network. In this paper we present a clustering approach based on Spectral Graph Partitioning (SGP) for WMSN that increases the lifetime of the network. The efficient strategies for cluster head selection and rotation are also proposed as part of clustering approach. Simulation results show that our strategy is better than existing strategies.

基于CatBoost算法的配电网分区拓扑辨识

含多分布式电源配电网的拓扑结构具有多样性与多变性,影响拓扑辨识的实时性和准确性。提出一种基于CatBoost算法的配电网分区拓扑辨识方法。构建结合拓扑分区的配电网拓扑辨识框架,采用区域开关状态矩阵描述拓扑结构,以进行物理上的辨识降维;提出基于CatBoost算法的特征选择与拓扑辨识方法,通过分区并行离线训练得到历史拓扑和未知拓扑的区域拓扑辨识CatBoost模型,通过在线应用得到实时的区域开关状态矩阵标签,形成配电网开关状态矩阵,实现系统拓扑辨识。配电网算例系统测试结果验证了所提方法的有效性。

面向区域自治的配电网动态区域划分方法

具有间隙性及波动性特征的大量分布式光伏接入配电网,为配电网的源荷功率平衡及节点电压调节等带来了新的技术挑战。为充分利用配电网中多类型调节资源的调节能力,提高新能源高比例接入下配电网的自治能力,提出了一种面向区域自治的配电网动态区域划分方法。首先,结合分布式光伏和负荷预测数据,衡量配电网中多类型可调资源的调节能力,建立考虑模块度、电压调节能力和功率持续调节能力的综合指标体系。其次,采用遗传算法求解各区域最优综合指标,结合运行状态及调控需求设计分区结构更新触发机制,更新分区结果。最后,结合实际配电网典型日运行数据的仿真算例及对比分析验证了所提区域动态划分方法在提高区域电压调节能力和功率持续调节能力方面的优势,并分析了不同指标权重,不同触发阈值以及不同时间尺度对分区结果的影响。