A Clustering-tree Topology Control Based on the Energy Forecast for Heterogeneous Wireless Sensor Networks

How to design an energy-efficient algorithm to maximize the network lifetime in complicated scenarios is a critical problem for heterogeneous wireless sensor networks (HWSN). In this paper, a clustering-tree topology control algorithm based on the energy forecast (CTEF) is proposed for saving energy and ensuring network load balancing, while considering the link quality, packet loss rate, etc. In CTEF, the average energy of the network is accurately predicted per round (the lifetime of the network is denoted by rounds) in terms of the difference between the ideal and actual average residual energy using central limit theorem and normal distribution mechanism, simultaneously. On this basis, cluster heads are selected by cost function (including the energy, link quality and packet loss rate) and their distance. The non-cluster heads are determined to join the cluster through the energy, distance and link quality. Furthermore, several non-cluster heads in each cluster are chosen as the relay nodes for transmitting data through multi-hop communication to decrease the load of each cluster-head and prolong the lifetime of the network. The simulation results show the efficiency of CTEF. Compared with low-energy adaptive clustering hierarchy (LEACH), energy dissipation forecast and clustering management (EDFCM) and efficient and dynamic clustering scheme (EDCS) protocols, CTEF has longer network lifetime and receives more data packets at base station. © 2014 Chinese Association of Automation.

Consensus of high-order dynamic multi-agent systems with switching topology and time-varying delays

This paper studies the consensus problems for a group of agents with switching topology and time-varying communication delays, where the dynamics of agents is modeled as a high-order integrator. A linear distributed consensus protocol is proposed, which only depends on the agent＇s own information and its neighbors＇ partial information. By introducing a decomposition of the state vector and performing a state space transformation, the closed-loop dynamics of the multi-agent system is converted into two decoupled subsystems. Based on the decoupled subsystems, some sufficient conditions for the convergence to consensus are established, which provide the upper bounds on the admissible communication delays. Also, the explicit expression of the consensus state is derived. Moreover, the results on the consensus seeking of the group of high-order agents have been extended to a network of agents with dynamics modeled as a completely controllable linear time-invariant system. It is proved that the convergence to consensus of this network is equivalent to that of the group of high-order agents. Finally, some numerical examples are given to demonstrate the effectiveness of the main results.

MST-BASED CLUSTERING TOPOLOGY CONTROL ALGORITHM FOR WIRELESS SENSOR NETWORKS

In this paper, we propose a novel clustering topology control algorithm named Minimum Spanning Tree (MST)-based Clustering Topology Control (MCTC) for Wireless Sensor Networks (WSNs), which uses a hybrid approach to adjust sensor nodes' transmission power in two-tiered hi- erarchical WSNs. MCTC algorithm employs a one-hop Maximum Energy & Minimum Distance (MEMD) clustering algorithm to decide clustering status. Each cluster exchanges information between its own Cluster Members (CMs) locally and then deliveries information to the Cluster Head (CH). Moreover, CHs exchange information between CH and CH and afterwards transmits aggregated in- formation to the base station finally. The intra-cluster topology control scheme uses MST to decide CMs' transmission radius, similarly, the inter-cluster topology control scheme applies MST to decide CHs' transmission radius. Since the intra-cluster topology control is a full distributed approach and the inter-cluster topology control is a pure centralized approach performed by the base station, therefore, MCTC algorithm belongs to one kind of hybrid clustering topology control algorithms and can obtain scalability topology and strong connectivity guarantees simultaneously. As a result, the network topology will be reduced by MCTC algorithm so that network energy efficiency will be improved. The simulation results verify that MCTC outperforms traditional topology control schemes such as LMST, DRNG and MEMD at the aspects of average node's degree, average node's power radius and network lifetime, respectively.

Inter-satellite Link Topology Design and Relative Navigation for Satellite Clusters

A distributed relative navigation approach via inter-satellite sensing and communication for satellite clusters is proposed. The inter-satellite link(ISL)is used for ranging and exchanging data for the relative navigation,which can improve the autonomy of the satellite cluster. The ISL topology design problem is formulated as a multi-objective optimization problem where the energy consumption and the navigation performance are considered. Further,the relative navigation is performed in a distributed fashion,where each satellite in the cluster makes observations and communicates with its neighbors via the ISL locally such that the transmission consumption and the computational complexity for the navigation are reduced. The ISL topology optimization problem is solved via the NSGA-Ⅱ algorithm,and the consensus Kalman filter is used for the distributed relative navigation. The proposed approach is flexible to varying tasks,with satellites joining or leaving the cluster anytime,and is robust to the failure of an individual satellite. Numerical simulations are presented to verify the feasibility of the proposed approach.

Clustering Network Topology Control Method Based on Responsibility Transmission

The topology control is an effective approach which can improve the quality of wireless sensor network at all sides. Through studying the mechanism of sensor network data transmission, the nature of data transmission in wireless sensor network is concluded as a kind of responsibility transmission. By redefining the responsibility and availability of nodes, the strategy for cluster head selection is studied, the responsibility and availability is determined by the combination of the residual energy, location and current flow of nodes. Based on the above, new clustering network topology control algorithm based on responsibility transmission CNTCABRT and hierarchical multi-hop CNTCABRT is presented in this paper, whose algorithm structure is along the famous LEACH algorithm. Experimental result demonstrates its promising performance over the famous LEACH algorithm in the cluster head selection, the size of cluster, the deployment of nodes and the lifetime of nodes, and several innovative conclusions are proposed finally.

Unicast Network Topology Inference Algorithm Based on Hierarchical Clustering

Network topology inference is one of the important applications of network tomography.Traditional network topology inference may impact network normal operation due to its generation of huge data traffic.A unicast network topology inference is proposed to use time to live(TTL)for layering and classify nodes layer by layer based on the similarity of node pairs.Finally,the method infers logical network topology effectively with self-adaptive combination of previous results.Simulation results show that the proposed method holds a high accuracy of topology inference while decreasing network measuring flow,thus improves measurement efficiency.

Tracking problem under a time-varying topology

This paper studies the multi-agent tracking problem of a third-order maneuvering target under uncertain communication environments. Each tracking agent is assumed to be a third-order system and can only use its own and neighbors＇ position, velocity, and acceleration information to design its control input. In this work, the uncertain communication environments are modelled by a finite number of constant Laplacian matrices together with their corresponding scheduling functions. Sufficient conditions for the existence of a tracking strategy have been expressed in terms of the solvability of linear matrix inequalities. Finally, a numerical example is employed to demonstrate the effectiveness of the proposed tracking strategy.

Two-Tier Hierarchical Cluster Based Topology in Wireless Sensor Networks for Contention Based Protocol Suite

The 802.15.4 Wireless Sensor Networks (WSN) becomes more economical, feasible and sustainable for new generation communication environment, however their limited resource constraints such as limited power capacity make them difficult to detect and defend themselves against variety of attacks. The radio interference attacks that generate for WSN at the Physical Layer cannot be defeated through conventional security mechanisms proposed for 802.15.4 standards. The first section introduces the deployment model of two-tier hierarchical cluster topology architecture and investigates different jamming techniques proposed for WSN by creating specific classification of different types of jamming attacks. The following sections expose the mitigation techniques and possible built-in mechanisms to mitigate the link layer jamming attacks on proposed two-tier hierarchical clustered WSN topology. The two-tier hierarchical cluster based topology is investigated based on contention based protocol suite through OPNET simulation scenarios.

A Location-Based Clustering Topology Control Algorithm in WSN

Aiming at the existing problems in Leach algorithm,which has short network survival time and high energy consumption,a new location-based clustering topology control algorithm is proposed.Based on Leach algorithm,improvements have been done.Firstly,when selecting cluster head,node degree,remaining energy,and the number of being cluster head,these three elements are taken into consideration.Secondly,by running the minimum spanning tree algorithm,the tree routing is constructed.Finally,selecting the next hop between clusters is done by MTE algorithm.Simulation results show that the presented control algorithm has not only a better adaptability in the large-scale networks,but also a bigger improvement in terms of some indicators of performance such as network lifetime and network energy consumption.

Multi-agent consensus with time-varying delays and switching topologies

The consensus problems of multi-agents with time-varying delays and switching topologies are studied. First, assume that an agent receives state information from its neighbors with fixed communication delays and processes its own state information with time-varying self-delay respectively. The state time-delay feedback is introduced into the existing consensus protocol to begenerate an improved protocol. Then a sufficient condition is derived which can make the system with time-varying self-delays achieve the consensus. On this basis, a specific form of consensus equilibrium influenced by the initial states of agents, time-delays and state feedback intensity is figured out. In addition, the multi-agent consensus is considered with time-varying topologies. Finally, simulations are presented to il ustrate the validity of theoretical results.

Cluster exponential synchronization of a class of complex networks with hybrid coupling and time-varying delay

This paper deals with the cluster exponential synchronization of a class ot complex networks wlm nyorm coupm^g and time-varying delay. Through constructing an appropriate Lyapunov-Krasovskii functional and applying the theory of the Kronecker product of matrices and the linear matrix inequality （LMI） technique, several novel sufficient conditions for cluster exponential synchronization are obtained. These cluster exponential synchronization conditions adopt the bounds of both time delay and its derivative, which are less conservative. Finally, the numerical simulations are performed to show the effectiveness of the theoretical results.

REMUDA: A Practical Topology Control and Data Forwarding Mechanism for Wireless Sensor Networks

In wireless sensor networks, topology control plays an important role for data forwarding efficiency in the data gathering applications. In this paper, we present a novel topology control and data forwarding mechanism called REMUDA, which is designed for a practical indoor parking lot management system. REMUDA forms a tree-based hierarchical network topology which brings as many nodes as possible to be leaf nodes and constructs a virtual cluster structure. Meanwhile, it takes the reliability, stability and path length into account in the tree construction process. Through an experiment in a network of 30 real sensor nodes, we evaluate the performance of REMUDA and compare it with LEPS which is also a practical routing protocol in TinyOS. Experiment results show that REMUDA can achieve better performance than LEPS.

Time-varying formation for general linear multi-agent systems via distributed event-triggered control under switching topologies

This paper investigates the time-varying formation problem for general linear multi-agent systems using distributed event-triggered control strategy.Different from the previous works,to achieve the desired time-varying formation,a distributed control scheme is designed in an event-triggered way,in which for each agent the controller is triggered only at its own event times.The interaction topology among agents is assumed to be switching.The common Lyapunov function as well as Riccati inequality is applied to solve the time-varying formation problem.Moreover,the Zeno behavior of triggering time sequences can be excluded for each agent.Finally,a simulation example is presented to illustrate the effectiveness of the theoretical results.

The Uniform Convergence Topology On Multi-valued Mapping Space

Some convergences of topology are discussed. The definitions of almost uniform convergence topology and compatible topology are given. It is shown that the quasiuniform convergence and generalized uniform convergence have no compatible topology,but the almost uniform convergence has compatible topology. Moreover, the description of all uniform convergence limits and their mutual relation are investigated[1].

Efficient Clustering Using Memetic Adaptive Hill Climbing Algorithm in WSN

Wireless Sensor Networks are composed of autonomous sensing devices which are interconnected to form a closed network.This closed network is intended to share sensitive location-centric information from a source node to the base station through efficient routing mechanisms.The efficiency of the sensor node is energy bounded,acts as a concentrated area for most researchers to offer a solution for the early draining power of sensors.Network management plays a significant role in wireless sensor networks,which was obsessed with the factors like the reliability of the network,resource management,energy-efficient routing,and scalability of services.The topology of the wireless sensor networks acts dri-ven factor for network efficiency which can be effectively maintained by perform-ing the clustering process effectively.More solutions and clustering algorithms have been offered by various researchers,but the concern of reduced efficiency in the routing process and network management still exists.This research paper offers a hybrid algorithm composed of a memetic algorithm which is an enhanced version of a genetic algorithm integrated with the adaptive hill-climbing algorithm for performing energy-efficient clustering process in the wireless sensor networks.The memetic algorithm employs a local searching methodology to mitigate the premature convergence,while the adaptive hill-climbing algorithm is a local search algorithm that persistently migrates towards the increased elevation to determine the peak of the mountain(i.e.,)best cluster head in the wireless sensor networks.The proposed hybrid algorithm is compared with the state of art clus-tering algorithm to prove that the proposed algorithm outperforms in terms of a network life-time,energy consumption,throughput,etc.

面向任务的无人飞行器自组网OLSR协议

无人飞行器(unmanned aerial vehicle,UAV)自组网的路由研究多以性能指标出发、忽略无人飞行器网络的任务驱动性,与实际需求动态耦合弱、适用性不强。针对该问题基于无人飞行器多任务网络提出了面向任务的无人飞行器联盟组网架构,提出了无人飞行器联盟的任务自适应优化链路状态路由协议(task adaptive optimized link state routing,TA-OLSR)。基于模糊逻辑设计拓扑稳定度计算方法,利用拓扑稳定度实现TA-OLSR控制消息的自适应广播,同时结合稳定度设计新的多点中继选择策略。仿真结果表明,TA-OLSR算法能从宏观面向任务的角度出发,实现不同任务下的良好自适应性,提升数据包投递率,减少冗余信息传播,降低网络开销,有效提高整体网络性能。

基于多特征符号聚合近似和层次聚类的户变关系识别方法

针对低压配电台区拓扑档案中可能存在的户变关系异常问题,文中提出了一种基于多特征符号聚合近似(MF-SAX)和层次聚类的户变关系识别方法。首先,运用符号聚合近似表达方法将用户电压时间序列转化为字符串序列,并引入电压波动系数和电压变化趋势两个附加参数对其特征表达进行强化。然后,基于编辑距离生成用户电压曲线相似性矩阵,并结合层次聚类算法实现户变关系的识别。最后,实际算例结果表明,提出的方法相比于现有方法准确率更高,误报更少,能直接应对数据缺失的情况,且具有更高的效率。

基于自适应网络拓扑和日志聚类的故障定界方法研究

传统的异常检测方法采用不定时巡检和用户反馈等被动方式发现问题,存在效率低、无法主动发现故障的问题。本文提出了一种基于自适应网络拓扑和日志聚类的故障定界方法。首先利用交换机ARP表和主机流量关系构建网络拓扑,再对系统日志进行结构化和聚类处理,最后结合网络拓扑和聚类结果快速定位异常范围,保证异常检测高效及全面。经生产实践表明,本文提出的故障定界方法能快速定位问题主机。