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 noncluster 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.

A Minimum-energy Path-preserving Topology Control Algorithm for Wireless Sensor Networks

The topology control strategies of wireless sensor networks are very important for reducing the energy consumption of sensor nodes and prolonging the life-span of networks. In this paper, we put forward a minimum-energy path-preserving topology control （MPTC） algorithm based on a concept of none k-redundant edges. MPTC not only resolves the problem of excessive energy consumption because of the unclosed region in small minimum-energy communication network （SMECN）, but also preserves at least one minimum-energy path between every pair of nodes in a wireless sensor network. We also propose an energy-efficient reconfiguration protocol that maintains the minimum-energy path property in the case where the network topology changes dynamically. Finally, we demonstrate the performance improvements of our algorithm through simulation.

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.

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.

Energy Efficient Direction-Based Topology Control Algorithm for WSN

A wireless sensor network consists of hundreds or thousands of small nodes which could either have a static or dynamic position. These nodes are deployed through normal or random distribution to report events of a particular area to the base station through sink nodes. Having limited onboard energy of sensor nodes, conservation of energy in wireless sensor network is necessary. For this purpose, a new algorithm is proposed titled Energy-Efficient-Direction-Based-Topology-Control-Algorithm (EEDBTC). In proposed algorithm, direction is the main concern whenever an event occurs the node will send data in the direction of base station so that less energy is consumed. The results of the same were compared with customary dense wireless sensor network, color based WSNs and it was observed that this algorithm is much better than previous topology control algorithms used.

Issues and Challenges in Node Connectivity in Mobile Ad Hoc Networks: A Holistic Review

One of the fundamental properties of an ad hoc network is its connectivity. Maintaining connectivity in wireless networks is extremely difficult due to dynamic changing topology of MANETs. There are several techniques to understand the connectivity level for a given network topology. In this paper, we examine the existing methods and discuss the issues and challenges that are still insurmountable in order to enhance the connectivity properties of wireless multi hop networks.

Stabilityanalysis of tactical missile autopilots based on vector margin

A novel stability computation approach for tactical missile autopilots is detailed. The limi- tations of traditional stability margins are exhibited. Then the vector margin is introduced and com- pared with sensitivity function to show their essential relationship. The longitudinal three-loop auto- pilot for tactical missiles is presented and used as the baseline for all the available linear autopilots. Ten linear autopilot topologies using all the measurable feedback components are given with the iden- tical closed-loop characteristic equation and time-domain step response. However, the stability of the ten autopilots differs when considering the actuator dynamics, which limits their application. Then vector margin method is adopted to compute and evaluate the stability of all available autopi- lots. The analysis and computation results show that the vector margin method could better evaluate autopilot stability.

AN ENERGY-EFFICIENT OPTIMIZATION DEPLOYMENT SCHEME FOR WIRELESS SENSOR NETWORKS

Most of the current deployment schemes for Wireless Sensor Networks (WSNs) do not take the network coverage and connectivity features into account, as well as the energy consumption. This paper introduces topology control into the optimization deployment scheme, establishes the mathe-matical model with the minimum sum of the sensing radius of each sensors, and uses the genetic al-gorithm to solve the model to get the optimal coverage solution. In the optimal coverage deployment, the communication and channel allocation are further studied. Then the energy consumption model of the coverage scheme is built to analyze the performance of the scheme. Finally, the scheme is simulated through the network simulator NS-2. The results show the scheme can not only save 36% energy av-eragely, but also achieve 99.8% coverage rate under the condition of 45 sensors being deployed after 80 iterations. Besides, the scheme can reduce the five times interference among channels.

Topology Control Algorithm Using Fault-Tolerant 1-Spanner for Wireless Ad Hoc Networks

A fault-tolerant 1-spanner is used to preserve all the minimum energy paths after node failures to cope with fault-tolerant topology control problems in wireless ad hoc networks. A fault-tolerant 1-spanner is a graph such that the remaining graph after node failures will not only remain connected, but also have a stretch factor of one. The fault-tolerant 1-spanner is used in a localized and distributed topology control algorithm, named the k-Fault-Tolerant 1-Spanner （k-FT1S）, where each node constructs a minimum energy path tree for every local failed node set. This paper proves that the topology constructed by k-FT1S is a k-fault-tolerant 1-spanner that can tolerate up to k node failures, such that the remaining network after node failures preserves all the minimum energy paths of the remaining network gained from the initial network by removing the same failed nodes. Simulations show that the remaining network after removal of any k nodes still has the optimal energy efficiency and is competitive in terms of average logical degree, average physical degree, and average transmission radius.

Sliding mode control of reaction flywheel-based brushless DC motor with buck converter

Reaction flywheel is a significant actuator for satellites＇ attitude control. To improve output torque and rotational speed accuracy for reaction flywheel, this paper reviews the modeling and control approaches of DC-DC converters and presents an application of the variable structure system theory with associated sliding regimes. Firstly, the topology of reaction flywheel is constructed. The small signal linearization process for a buck converter is illustrated. Then, based on the state averaging models and reaching qualification expressed by the Lee derivative, the general results of the sliding mode control （SMC） are analyzed. The analytical equivalent control laws for reaction flywheel are deduced detailedly by selecting various sliding surfaces at electromotion, energy consumption braking, reverse connection braking stages. Finally, numerical and experimental examples are presented for illustrative purposes. The results demonstrate that favorable agreement is established between the simulations and experiments. The proposed control strategy achieves preferable rotational speed regulation, strong rejection of modest disturbances, and high-precision output torque and rotational speed tracking abilities.

Topology control based on quantum genetic algorithm in sensor networks

Nowadays,two trends appear in the application of sensor networks in which both multi-service and quality of service(QoS)are supported.In terms of the goal of low energy consumption and high connectivity,the control on topology is crucial.The algorithm of topology control based on quantum genetic algorithm in sensor networks is proposed.An advantage of the quantum genetic algorithm over the conventional genetic algorithm is demonstrated in simulation experiments.The goals of high connectivity and low consumption of energy are reached.

A hierarchical autonomous system based space information network architecture and topology control

SIN(Space Information Network)has recently emerged as a promising approach to solving the collaboration difficulty among current space programs.However,because of the SIN’s large scale,high component complexity,and dynamic characteristics,designing a proper SIN architecture is challenging.Firstly,we propose a novel SIN architecture,which is composed of GEO(Geostationary Earth Orbit)satellites as backbone network nodes,LEO(Low Earth Orbit)or other types of satellites as enhanced coverage nodes,and high-altitude platforms to meet the service requirements of emergency or hot-spot applications.Unlike most existing studies,the proposed architecture is AS(Autonomous-System)based.We decouple the complex SIN into simpler sub-networks using a hierarchical AS model.Then,we propose a topology control algorithm to minimize the time delay among sub-AS networks.We prove that the proposed algorithm achieves logical k-connectivity provided that the original physical topology has k-connectivity.Simulation results validate the theoretic analysis and effectiveness of the algorithm.

Topology control of three-dimensional covalent organic frameworks by adjusting steric hindrance effect

Since the intrinsic topological network determines their pore characteristics and functional applications, it is important to construct 3D COFs with target topology from predesigned functional building blocks. However, when starting from precursors with same connectivity but different bulky groups, the structure and topology of 3D COFs may change, which will greatly increase the complexity of the crystal structure determination. Therefore, it is essential to understand how to control the steric hindrance effects and synthesize 3D COFs with target topology. Herein, we report the topology control of 3D COFs by adjusting steric hindrance effects of functional building blocks. Starting from a quadrilateral building block with sterically hindered phenyl groups, we have been able to achieve the target pts topology instead of the unprecedented ljh network that we reported recently by elongating the tetrahedral building block. This result clearly shows that it is promising to precisely control the topology of 3D COFs by judiciously selecting building blocks with steric hindrance and suitable dimensions.

Real-time,decentralized and bio-inspired topology control for holonomic autonomous vehicles

Purpose–This paper aims to present an approach for a bio-inspired decentralization topology control mechanism,called force-based genetic algorithm(FGA),where a genetic algorithm(GA)is run by each holonomic autonomous vehicle(HAV)in a mobile ad hoc network(MANET)as software agent to achieve a uniform spread of HAVs and to provide a fully connected network over an unknown geographical terrain.An HAV runs its own FGA to decide its next movement direction and speed based on local neighborhood information,such as obstacles and the number of neighbors,without a centralized control unit or global knowledge.Design/methodology/approach-The objective function used in FGA is inspired by the equilibrium of the molecules in physics where each molecule tries to be in the balanced position to spend minimum energy to maintain its position.In this approach,a virtual force is assumed to be applied by the neighboring HAVs to a given HAV.At equilibrium,the aggregate virtual force applied to an HAV by its neighbors should sum up to zero.If the aggregate virtual force is not zero,it is used as a fitness value for the HAV.The value of this virtual force depends on the number of neighbors within the communication range of Rcom and the distance among them.Each chromosome in our GA-based framework is composed of speed and movement direction.The FGA is independently run by each HAV as a topology control mechanism and only utilizes information from neighbors and local terrain to make movement and speed decisions to converge towards a uniform distribution of HAVs.The authors developed an analytical model,simulation software and several testbeds to study the convergence properties of the FGA.Findings-The paper finds that coverage-centric,bio-inspired,mobile node deployment algorithm ensures effective sensing coverage for each mobile node after initial deployment.The FGA is also an energy-aware self-organization framework since it reduces energy consumption by eliminating unnecessary excessive movements.Fault-tolerance is another important feature of the GA-based approach since the FGA is resilient to losses and malfunctions of HAVs.Furthermore,the analytical results show that the authors’bio-inspired approach is effective in terms of convergence speed and area coverage uniformity.As seen from the experimental results,the FGA delivers promising results for uniform autonomous mobile node distribution over an unknown geographical terrain.Originality/value-The proposed decentralized and bio-inspired approach for autonomous mobile nodes can be used as a real-time topology control mechanism for commercial and military applications since it adapts to local environment rapidly but does not require global network knowledge.

A topology control algorithm for preserving minimum-energy paths in wireless ad hoc networks

In this paper,a distributed topology control algorithm is proposed.By adjusting the transmission power of each node,this algorithm constructs a wireless network topology with minimum-energy property,i.e.,it preserves a minimum-energy path between every pair of nodes.More-over,the proposed algorithm can be used in both homogenous and heterogeneous wireless networks,and it can also work without an explicit propagation channel model or the position information of nodes.Simulation results show that the proposed algorithm has advantages over the topology control algorithm based on direct-transmission region in terms of average node degree and power efficiency.

Valley photonic crystals for control of spin and topology

Subject Code:A04With the support by the National Natural Science Foundation of China,the research team led by Prof.Dong Jianwen(董建文)at the State Key Laboratory of Optoelectronic Materials and Technologies&School of Physics,Sun Yat-sen University,discovered the control of spin and topology in valley photonic crystals,which was published in Nature Materials(2017,DOI:10.1038/NMAT4087).

Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents

The operation of electricity grids has become increasingly complex due to the current upheaval and the increase in renewable energy production.As a consequence,active grid management is reaching its limits with conventional approaches.In the context of the Learning to Run a Power Network(L2RPN)challenge,it has been shown that Reinforcement Learning(RL)is an efficient and reliable approach with considerable potential for automatic grid operation.In this article,we analyse the submitted agent from Binbinchen and provide novel strategies to improve the agent,both for the RL and the rule-based approach.The main improvement is a N-1 strategy,where we consider topology actions that keep the grid stable,even if one line is disconnected.More,we also propose a topology reversion to the original grid,which proved to be beneficial.The improvements are tested against reference approaches on the challenge test sets and are able to increase the performance of the rule-based agent by 27%.In direct comparison between rule-based and RL agent we find similar performance.However,the RL agent has a clear computational advantage.We also analyse the behaviour in an exemplary case in more detail to provide additional insights.Here,we observe that through the N-1 strategy,the actions of both the rule-based and the RL agent become more diversified.

Free-Form Deformation with Rational DMS-Spline Volumes

In this paper, we propose a novel free-form deformation （FFD） technique, RDMS-FFD （Rational DMS-FFD）, based on rational DMS-spline volumes. RDMS-FFD inherits some good properties of rational DMS-spline volumes and combines more deformation techniques than previous FFD methods in a consistent framework, such as local deformation, control lattice of arbitrary topology, smooth deformation, multiresolution deformation and direct manipulation of deformation. We first introduce the rational DMS-spline volume by directly generalizing the previous results related to DMS-splines. How to generate a tetrahedral domain that approximates the shape of the object to be deformed is also introduced in this paper. Unlike the traditional FFD techniques, we manipulate the vertices of the tetrahedral domain to achieve deformation results. Our system demonstrates that RDMS-FFD is powerful and intuitive in geometric modeling.

A Combinational Perspective in Stimulating Cooperation in Mobile Ad Hoc Networks

In wireless ad hoc networks cooperation among nodes cannot always be assumed since nodes with limited resources and different owners are capable of making independent decisions. Cooperation problems in topology control and packet forwarding tasks have been mostly studied separately but these two tasks are not independent. Considering a joint cooperation problem by taking into account dependencies between tasks will result in more reliable and efficient networks. In this paper topology control definition is extended to cover cooperation problem in both packet forwarding and topology control in a single problem. In this definition nodes have to adjust their transmission power and decide on their relay role. This paper models the interactions of nodes as a potential game with two-dimensional utility function. The presented model, named TCFORCE （Topology Control packet FORwarding Cooperation Enforcement）, preserves the network connectivity and reduces the energy consumption by providing cooperative paths between all pairs of nodes in the network.

Some Properties for the Largest Component of Random Geometric Graphs with Applications in Sensor Networks

In this paper we consider the standard Poisson Boolean model of random geometric graphs G（Hλ,s; 1） in Rd and study the properties of the order of the largest component L1 （G（Hλ,s; 1）） . We prove that ElL1 （G（Hλ,s; 1））] is smooth with respect to A, and is derivable with respect to s. Also, we give the expression of these derivatives. These studies provide some new methods for the theory of the largest component of finite random geometric graphs （not asymptotic graphs as s - co） in the high dimensional space （d 〉 2）. Moreover, we investigate the convergence rate of E[L1（G（Hλ,s; 1））]. These results have significance for theory development of random geometric graphs and its practical application. Using our theories, we construct and solve a new optimal energy-efficient topology control model of wireless sensor networks, which has the significance of theoretical foundation and guidance for the design of network layout.