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1.
Automatic network clustering is an important technique for mining the meaningful communities (or clusters) of a network. Communities in a network are clusters of nodes where the intra-cluster connection density is high and the inter-cluster connection density is low. The most popular scheme of automatic network clustering aims at maximizing a criterion function known as modularity in partitioning all the nodes into clusters. But it is found that the modularity suffers from the resolution limit problem, which remains an open challenge. In this paper, the automatic network clustering is formulated as a constrained optimization problem: maximizing a criterion function with a density constraint. With this scheme, the established algorithm can be free from the resolution limit problem. Furthermore, it is found that the density constraint can improve the detection accuracy of the modularity optimization. The efficiency of the proposed scheme is verified by comparative experiments on large scale benchmark networks.  相似文献   

2.
Ad hoc networks consist of wireless hosts that communicate with each other in the absence of a fixed infrastructure. Such networks cannot rely on centralized and organized network management. The clustering problem consists of partitioning network nodes into non-overlapping groups called clusters. Clusters give a hierarchical organization to the network that facilitates network management and that increases its scalability.In a weight-based clustering algorithm, the clusterheads are selected according to their weight (a node’s parameter). The higher the weight of a node, the more suitable this node is for the role of clusterhead. In ad hoc networks, the amount of bandwidth, memory space or battery power of a node could be used to determine weight values.A self-stabilizing algorithm, regardless of the initial system configuration, converges to legitimate configurations without external intervention. Due to this property, self-stabilizing algorithms tolerate transient faults and they are adaptive to any topology change.In this paper, we present a robust self-stabilizing weight-based clustering algorithm for ad hoc networks. The robustness property guarantees that, starting from an arbitrary configuration, after one asynchronous round, the network is partitioned into clusters. After that, the network stays partitioned during the convergence phase toward a legitimate configuration where the clusters verify the “ad hoc clustering properties”.  相似文献   

3.
In mobile networks, the assignment of base stations to controllers when planning the network has a strong impact on network performance. In a previous paper, the authors formulated the assignment of base stations to packet controllers in GSM-EDGE Radio Access Network (GERAN) as a graph partitioning problem, which was solved by a heuristic method. In this paper, an exact method is presented to find optimal solutions that can be used as a benchmark. The proposed method is based on an effective re-formulation of the classical integer linear programming model of the graph partitioning problem, which is solved by the branch-and-cut algorithm in a commercial optimization package. Performance assessment is based on an extensive set of problem instances built from data of a live network. Preliminary analysis shows some properties of the graphs in this problem justifying the limitations of heuristic approaches and the need for more sophisticated methods. Results show that the proposed method outperforms classical heuristic algorithms used for benchmarking, even under runtime constraints. Likewise, it improves the efficiency of exact methods previously applied to similar problems in the cellular field.  相似文献   

4.
In this paper, a new robust distributed model predictive control (RDMPC) is proposed for large-scale systems with polytopic uncertainties. The time-varying system is first decomposed into several interconnected subsystems. Interactions between subsystems are obtained by a distributed Kalman filter, in which unknown parameters of the system are estimated using local measurements and measurements of neighboring subsystems that are available via a network. Quadratic boundedness is used to guarantee the stability of the closed-loop system. In the MPC algorithm, an output feedback-interaction feedforward control input is computed by an LMI-based optimization problem that minimizes an upper bound on the worst case value of an infinite-horizon objective function. Then, an iterative Nash-based algorithm is presented to achieve the overall optimal solution of the whole system in partially distributed fashion. Finally, the proposed distributed MPC approach is applied to a load frequency control (LFC) problem of a multi-area power network to study the efficiency and applicability of the algorithm in comparison with the centralized, distributed and decentralized MPC schemes.  相似文献   

5.
Subdomain generation using emergent ant colony optimization   总被引:1,自引:0,他引:1  
Finite elements mesh decomposition is a well known optimization problem and is used to split a computationally expensive finite elements mesh into smaller subdomains for parallel finite elements analysis.The ant colony optimization is a type of algorithm that seeks to model the emergent behaviour observed in ant colonies and utilize this behaviour to solve combinatorial problems. This technique has been applied to several problems, most of which are graph related because the ant colony metaphor can be most easily applied to such types of problems. This paper examines the application of ant colony optimization algorithm to the partitioning of unstructured adaptive meshes for parallel explicit time-stepping finite elements analysis.The concept of ant colony optimization technique in addition to the notion of swarm intelligence for finding approximate solutions to combinatorial optimization problems is described. This algorithm combines the features of the classical ant colony optimization technique with swarm intelligence to form a model which is an artificial system designed to perform a certain task.The application of the ant colony optimization for partitioning finite elements meshes based on triangular elements using the swarm intelligence concept is described. A recursive greedy algorithm optimization method is also presented as a local optimization technique to improve the quality of the solutions given by the ant colony optimization algorithm. The partitioning is based on the recursive bisection approach.The mesh partitioning is carried out using normal and predictive modes for which the predictive mode uses a trained multi-layered feedforward neural network that estimates the number of triangular elements that will be generated after finite elements mesh generation is carried out.The performance of the proposed hybrid approach for the recursive bisection of finite elements meshes is examined by decomposing two mesh examples and comparing them with a well known finite elements domain decomposer.  相似文献   

6.
This paper examines a method of clustering within a fully decentralized multi-agent system. Our goal is to group agents with similar objectives or data, as is done in traditional clustering. However, we add the additional constraint that agents must remain in place on a network, instead of first being collected into a centralized database. To do this, we connect agents in a random overlay network and have them search in a peer-to-peer fashion for other similar agents. We thus aim to tackle the basic clustering problem on an Internet scale, and create a method by which agents themselves can be grouped, forming coalitions. In order to investigate the feasibility of this decentralized approach, this paper presents simulation experiments that look into the quality of the clusters discovered. First, the clusters found by the agent method are compared to those created by k-means clustering for two-dimensional spatial data points. Results show that the decentralized agent method produces a better clustering than the centralized k-means algorithm, placing 95% to 99% of points correctly. A further experiment explores how agents can be used to cluster a straightforward text document set, demonstrating that agents can discover clusters and keywords that are reasonable estimates of those identified by the central word vector space approach.  相似文献   

7.
In Large Scale Systems the concept of centrality fails due to the lack of centralized computing capability. The control of such systems has to be performed using multiple control agents. In this case, the matter of interactions among neighboring subsystems needs to be considered. In this paper, a water control system in the Netherlands is studied as a real large scale system. A multi‐agent scheme is applied to control the flow through the system which is decomposed into two interconnected subsystems. Each agent employs a model‐based predictive control (MPC) technique. The model of this large scale system is nonlinear and nonconvex. Therefore, an augmented Lagrangian pattern search optimization algorithm is used to implement multi‐agent MPC for this system. This proposed algorithm is applied by each control agent to solve its own interconnected optimization problem, at each subsystem of whole the water system. Simulation results show the effectiveness of the proposed approach.  相似文献   

8.
轧制批量计划问题的模型及算法研究   总被引:5,自引:0,他引:5  
陈雄  郭令忠 《信息与控制》1997,26(5):382-387
网络建模在系统分析中是最有效的方法之一,广泛地应用于工业工程和生产调度中,应用组合优化中著名的车辆调度问题分析、研究钢生产中传统的轧制批量计划问题,提出一种新的具有优化分割功能的遗传算法,并进行了计算机仿真、仿真结果证实该方法的有效性。  相似文献   

9.
章治  曾夏玲 《计算机仿真》2012,29(5):130-132,238
研究网络控制系统的优化问题,提高系统的实时性。针对传统的网络控制系统是闭环系统,网络带宽有限,网络传输中的时间延迟、数据包丢失等问题不可避免。当发生以上情况时,反馈信号不能及时传回,造成控制信号发出延迟,影响了系统的实时性。为了解决上述问题,提出了一种非规律时滞补偿算法,把时滞信号引入自由权矩阵,能够得到延迟信号相关稳定性条件,并充分运用线性信号特征矩阵保证网络控制系统的性能,保证系统在线控制的实时性。证明改进方法能够避免控制信号延迟造成的滞后问题,提高了网络控制系统的实时性。  相似文献   

10.
针对现有换热站并联水泵优化算法在集中式架构下控制适应性不足的问题, 本文提出了一种改进的分布式并联水泵优化算法. 首先, 建立了并联水泵的分布式控制系统, 并对该优化问题的数学模型进行描述, 在目标函数中引入自适应非线性因子; 然后, 设计了改进的分布式果蝇优化算法, 在该算法中每台水泵的控制器仅通过与邻居控制器交互信息即可完成并联水泵的优化; 并且, 在嗅觉搜索阶段, 使用正弦余弦策略替代赋予个体距离与方向的随机策略; 最后, 以两个实际换热站中不同并联水泵系统为例对算法进行仿真验证, 并基于仿真结果进行性能分析. 结果表明, 相较于传统算法, 改进的分布式果蝇优化算法能得到更优的控制策略, 有着收敛速度快、稳定性好和鲁棒性强的特点; 并且该算法适用于不同系统的并联水泵优化问题, 具有可扩展性. 在实际工程验证中相较于集中式算法, 该算法在总功率和计算时间上分别平均降低了5.47%和29.90%, 因此, 能够满足实际换热站中对并联水泵热负荷优化分配的需求.  相似文献   

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