Topology Control Algorithm Research Articles

Cross-Layer Topology Control Algorithm Based on Supermodular Game and Optimal Rigid Graph

Cross-Layer Topology Control Algorithm Based on Supermodular Game and Optimal Rigid Graph

Variational Autoencoders for Network Lifetime Enhancement in Wireless Sensors.

Wireless sensor networks (WSNs) are structured for monitoring an area with distributed sensors and built-in batteries. However, most of their battery energy is consumed during the data transmission process. In recent years, several methodologies, like routing optimization, topology control, and sleep scheduling algorithms, have been introduced to improve the energy efficiency of WSNs. This study introduces a novel method based on a deep learning approach that utilizes variational autoencoders (VAEs) to improve the energy efficiency of WSNs by compressing transmission data. The VAE approach is customized in this work for compressing WSN data by retaining its important features. This is achieved by analyzing the statistical structure of the sensor data rather than providing a fixed-size latent representation. The performance of the proposed model is verified using a MATLAB simulation platform, integrating a pre-trained variational autoencoder model with openly available wireless sensor data. The performance of the proposed model is found to be satisfactory in comparison to traditional methods, like the compressed sensing technique, lightweight temporal compression, and the autoencoder, in terms of having an average compression rate of 1.5572. The WSN simulation also indicates that the VAE-incorporated architecture attains a maximum network lifetime of 1491 s and suggests that VAE could be used for compression-based transmission using WSNs, as its reconstruction rate is 0.9902, which is better than results from all the other techniques.

A Topology Control Algorithm Taking into Account Energy and Quality of Transmission for Software-Defined Wireless Sensor Network

The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for softwaredefined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the Max Power algorithm in terms of average node degree and energy expansion ratio.

A Spectral Gap-Based Topology Control Algorithm for Wireless Backhaul Networks

This paper presents the spectral gap-based topology control algorithm (SGTC) for wireless backhaul networks, a novel approach that employs the Laplacian Spectral Gap (LSG) to find expander-like graphs that optimize the topology of the network in terms of robustness, diameter, energy cost, and network entropy. The latter measures the network’s ability to promote seamless traffic offloading from the Macro Base Stations to smaller cells by providing a high diversity of shortest paths connecting all the stations. Given the practical constraints imposed by cellular technologies, the proposed algorithm uses simulated annealing to search for feasible network topologies with a large LSG. Then, it computes the Pareto front of the set of feasible solutions found during the annealing process when considering robustness, diameter, and entropy as objective functions. The algorithm’s result is the Pareto efficient solution that minimizes energy cost. A set of experimental results shows that by optimizing the LSG, the proposed algorithm simultaneously optimizes the set of desirable topological properties mentioned above. The results also revealed that generating networks with good spectral expansion is possible even under the restrictions imposed by current wireless technologies. This is a desirable feature because these networks have strong connectivity properties even if they do not have a large number of links.

A topology control algorithm for fusion networks based on link quality

To extend the network life, an ordinal potential game is introduced into network topology control, and a network topology control algorithm based on the Theil entropy measure is designed by improving the revenue function. The revenue function is based on the Theil entropy measure, whose factors are in the residual energy of the nodes and their neighbors. By using a primary payoff function that considers all initial network factors and a secondary one that addresses connectivity in case of reduced residual energy, a segmentation function can calculate the model's payoff. Simulation experiments show that compared to the existing game algorithms of 3DK-RNG, DEBA, and EFPC, the proposed algorithm can effectively eliminate redundant links, reduce node degree and network link length, balance node energy consumption, enhance network load, and extend the network life cycle.•A Network Topology Control Algorithm Based on the Fusion of Thiel Entropy and Ordinal Potential Games.•A network topology control method for extending the network lifecycle is successfully established.•It proposes that the performance of the fusion topology control algorithm is significantly superior to other single algorithms in the paper.

Transmission Congestion Management via Node-Breaker Topology Control

A novel topology control algorithm is proposed here to reduce congestion and overloads, thereby improving security margins in a power network. The proposed heuristic relies on normalized squares of the line currents as a direct indicator of transmission line loading. The sensitivity of this measure with respect to breaker positions forms the basis of the proposed heuristic to select switching actions for a reconfigured network topology that reduces the congestion and overloads while holding generation dispatch essentially fixed. While many prior works have examined this class of problem for line switching actions (i.e., topology changes that insert or remove branches), bus-bar switching actions (topology changes that merge or split nodes/buses) have received less research focus. Here, both line switching and bus-bar switching are implemented using a detailed node-breaker representation of the network. The algorithm adopts a novel form of the AC power flow that allows sparse calculation and reduced computation time. Case studies demonstrate that the proposed approach efficiently reduces congestion and overloads in the base case and in contingency situations.

Energy-Efficient Topology Control Mechanism for IoT-Oriented Software-Defined WSNs

In time-varying software-defined wireless sensor networks (SDWSNs) for Internet-of-Things (IoT) applications, the topology may change due to the interference or abnormal events, thus leading to network performance degradation. In this paper, an energy-efficient topology control (TC) mechanism applied for IoT-oriented SDWSNs is proposed to maximize the network energy efficiency (EE) during the dynamic topology maintenance. First, a hierarchical SDWSN architecture consisting of the cluster-based sensing network and the programmable relay network is presented. Second, two TC algorithms based on the link EE are proposed to apply in the cluster and relay sub-networks of SDWSN, respectively. In the cluster sub-network, the proposed distributed TC algorithm enables the link interference mitigation by employing power control and rate allocation in each cluster. In the relay sub-network, the proposed centralized TC algorithm first utilizes a specified model to construct the original topology. During the dynamic topology maintenance, the proposed centralized TC algorithm is realized by the value-iteration learning method based on a Markov decision process (MDP) model, upon which the state-transition probability (STP) of the relay sub-network is obtained, where the relay-network state is composed of the link, the queue, and the residual energy ratio states for all nodes in the relay sub-network. Finally, simulation results show that both two TC algorithms can improve the corresponding sub-network EE of time-varying SDWSN.

Application of Wireless Sensor Network Computer Technology in Financial Management System

In the current enterprise competition, the core of the management information system is the financial management information system. Building a more comprehensive and efficient financial management information system can effectively establish a more efficient innovative enterprise and promote the transformation and development of the enterprise. This paper first designs a set of financial management system templates, including general ledger, accounts receivable, and accounts payable. Second, according to the characteristics of wireless sensor network technology, this paper proposes a financial management system based on the wireless sensor network and designs a load balancing topology control algorithm (LHTCA algorithm), which balances the energy consumption of network nodes and helps to improve the network life cycle. Finally, the management system is tested and validated. The test results show that the financial management system can realize the electronicization of financial data and paperless vouchers, improve the efficiency of financial work, and promote the sharing and integration of resources.

A Survey on Geographical Based Topology Control for Ad Hoc Networks

Wireless ad hoc network nodes suffer from limited energy supply. To reduce the power consumption of the routing protocols, many routing algorithms use a subset of the nodes to participate in the routing task. For that reason, topology control for wireless ad hoc networks got great attention in recent years. Geographical locations of the network nodes are used in many topology control algorithms to enhance performance and reduce overhead. In this paper, we review the most known geographical-based topology control algorithms for Ad Hoc Networks with a focus on connectivity, locality, planarity, stretch factor, node degree, and scalability. We conduct a comparison between these algorithms as well.

TFACR: A Novel Topology Control Algorithm for Improving 5G-Based MANET Performance by Flexibly Adjusting the Coverage Radius

TFACR: A Novel Topology Control Algorithm for Improving 5G-Based MANET Performance by Flexibly Adjusting the Coverage Radius

Research on Common-mode Interference Current suppression of active neutral point clamped five-level inverter

To solve the problem of common-mode interference current in active neutral point clamped five-level (ANPC-5L) inverter, a common-mode interference current suppression scheme combining four-leg topology and model predictive control (MPC) algorithm is proposed. The common-mode loop model of the transformerless four-leg ANPC-5L inverter is presented firstly. Then the common-mode voltage with different switching states and the effect of factors on the common-mode interference current are analysed. On this basis, this paper adopts feedforward decoupling control algorithm to realize capacitor voltage decoupling control, and reasonably selects the redundant switching state of four-leg ANPC-5L topology by MPC algorithm. The proposed scheme can achieve constant common-mode voltage, so as to effectively suppress the common-mode interference current. The simulation results show that the proposed control methods are effective and feasible.

Dynamic topology control algorithm for node deployment in mobile underwater wireless sensor networks

AbstractSensors in underwater wireless sensor networks (UWSNs) can drift up to 3 m/s due to ocean currents, marine organisms, or passing vessels. In existing node deployment and localization techniques, node mobility and network disconnections are not taken into account. This article proposes a dynamic topology control algorithm for node deployment (DTCND) in mobile UWSN. This work aims to monitor the node mobility to predict nodes' location for ensuring coverage and connectivity. The sensor nodes are deployed randomly at different depths. The anchor nodes observe the signal quality index, energy drain rate, and node density at every time interval and detect node disconnections based on the variations in these observed metrics. After receiving the beacon messages from the anchor nodes, the courier nodes incline to move toward the target region for satisfying the coverage and connectivity constraints. Simulation results show that the proposed algorithm attains 5% higher connectivity when compared to energy‐efficient localization algorithm (EELA) and 9% higher connectivity when compared to adaptive triangular deployment algorithm (ATDA). The residual energy is also higher by 3% and 18% when compared to EELA and ATDA, respectively. The deployment cost and delay of DTCND also decrease when compared to EELA and ATDA, which results into efficient data collection.

RDMST- A Novel Distributed Topology Control Algorithm for Low Probability of Detection Mobile Communication Networks

One aim of a military tactical network is to Lower the Probability of Detection, LPD, in order to hide the network from a possible adversary. Whilst there are numerous ways that communications can be hidden from an adversary the approach used in this paper is to minimise the transmitted power of the network's radios, whilst keeping the radios connected. Results from previous simulation experiments demonstrated the potential efficacy of these algorithms. In this paper we have implemented these algorithms into mobile radios and performed field trials to determine whether the LPD algorithm would transfer over into a more realistic environment. Problems associated with the noisy wireless medium were overcome and promising results obtained. This paper describes the field trials of the LPD algorithm, discusses some emerging issues, and presents the results from these trials.

A fault-tolerant topology control algorithm for wireless ultraviolet light covert communication network in cluster UAV

A fault-tolerant topology control algorithm for wireless ultraviolet light covert communication network in cluster UAV

Multi-Input Ćuk Inverter Based on Model Predictive Control

In this paper multi-input Cuk- derived buck-boost inverter is presented based on Model Predictive Control (MPC). The control technique is applied to multi- input Cuk- derived buck-boost inverter because of the several features such as reduction of passive elements compared with two-stage topologies and the family of impedance inverters such as Z-source Inverter (ZSI), Quazi Source Inverter(QSI), T-Source Inverter (TSI), and Y-Source Inverter (YSI) .in addition , it is suitable for photovoltaic applications as it has the ability to boost the DC voltage from the PV cells and also invert it to AC voltage in the one stage. The model predictive control is applied in this paper to get a high response in the dynamic changes. In addition, more than one variable can be controlled in the same cost function, all the aforementioned features of the MPC can be achieved by using a technical called reducing horizon technique has been used. As the actual values are measured and compared with the reference for several solutions, the less accurate error will be given to use as action for the switched control. The power topology circuit and control algorithm have been validated by MATLAB/SIMULINK Software.

WSN Topology Control algorithm for High Speed Railway Monitoring

In order to solve the safety problems caused by the continuous improvement of train speed and the continuous growth of railway scale, it is inevitable to apply wireless sensor network (WSN) to train operation environment monitoring. In order to prolong the survival time of wireless monitoring network, the game theory is used to construct a distributed topology model. In order to solve the problem of network lifetime shortening caused by uneven energy consumption of nodes, the Theil index is introduced to improve the energy consumption balance of nodes, and a topology control algorithm for energy consumption balance (EBTCA) is proposed. Experiments show that the algorithm has good results in terms of network lifetime and energy balance.

Dynamic Spatial-Correlation-Aware Topology Control of Wireless Sensor Networks Using Game Theory

With the increasing applications of Internet of Things (IoT), service quality becomes more and more important. The topology control of wireless sensor networks (WSN) is one of the key techniques to optimize the quality of service (QoS) of IoT. Game theory is an efficient approach of WSN topology control through global optimization, which resolves the conflicting objectives of self-regard sensor nodes. However, many existing topology control algorithms using game theory waste energy due to the transmission of redundant sensed data. In this study, we present a novel dynamic spatial-correlation-aware topology control method (TC-GSC) using game theory to reduce the redundant data. In TC-GSC, the monitoring region is divided into several spatial-correlation areas, and only one active node is periodically selected for each area. Based on the collected information of active nodes, the sink node computes the transmitting power level using game theory and generates the connected topology. Moreover, the WSN topology can be dynamically updated when the active node’s remaining energy becomes greatly uneven, or the active node’s working time exceeds the threshold. Extensive simulation results demonstrate that TC-GSC can effectively improve the energy balance of nodes and significantly reduce the energy waste, thus prolonging the lifetime of networks.

A New Topology Control Algorithm in Software Defined Wireless Rechargeable Sensor Networks

In wireless networks, the network coverage and sustainable operations are closely interlinked. These are the most critical problems in any wireless sensor networks (WSNs), which are based on software defined networks. However, in previous literature, these problems are always considered separately. Consequently, these problems are not addressed in an efficient manner. In this work, we focus on new network structures known as software defined wireless rechargeable sensor networks (SDWRSNs) to ensure long-term operations and full coverage of the network simultaneously. In this work, we propose the least nodes deployment and charging algorithm (LNDCA) based on the homology theory. In the proposed LNDCA, the SDN controller requests the mobile chargers to replenish the energy for the node with the lowest energy. Additionally, the algorithm fully covers the whole network by using minimum number of nodes and ensures continuous operations in the network. The simulation results and analysis conducted in this work show that the proposed algorithm performs well in terms of energy consumption, coverage, and sustainable operations.

Two-stage Topology Control Strategy for Software-defined UAV Networks Against Jamming Attack

Software-defined network (SDN) technology brings new methods to the autonomous control of UAV networks. Aiming at the deterioration of UAV network wireless communication quality caused by jamming attacks, we propose a two-stage topology control algorithm to improve network service quality. The first stage is the redeployment of the control plane consisted by the relay UAVs. We calculate the position of the jammers based on Received Signal Strength Indication (RSSI), and then we first redeploy the position of the Relay UAVs. The second stage is the redeployment of the data plane consisted by the mission UAVs. Mission UAVs that lose control links due to jamming are redeployed according to the historical state of controllers, and other UAVs are redeployed according to the new state of controllers. The performance metric is the weighted average of load balancing, redeployment delay and Signal to Interference plus Noise Ratio (SINR). The experimental results show that compared with the Distance Closest Migration (DCM) strategy and the Distributed Hopping Algorithm (DHA), the comprehensive performance of the proposed algorithm is better.

Research and Design Based on Smart Street Lights Network and Adaptive Dimming Method

In order to respond to the call of "smart city" and combine the actual demand of urban road lighting, this paper studies and designs a network based on smart streetlights and adaptive dimming algorithm. In order to improve the efficiency of data transmission in the smart street lamp monitoring network, an unequal clustering topology control algorithm based on band network (UCTC-BN) is proposed to establish a band topology for data Communication. When selecting the cluster head nodes, the algorithm adopts the candidate cluster head mechanism, and the candidate cluster head determines the non-uniform competition radius according to the remaining energy of the nodes and the distance from the sink nodes, thus achieving the goal of balancing the network energy consumption. In view of the low intelligence of street lights dimming and poor energy saving effect, an improved self-adaptive dimming algorithm based on K-means++ and DAG-SVM is studied, the light and traffic volume are clustered and six-classification dimming model is constructed to realize the intelligent dimming of street lights. Experimental results show that the system can efficiently transmit environmental data and comprehensively adjust street lamp lights, effectively reducing street lamp power consumption.