Sensor Network Topology Research Articles

PEECA: PSO-Based Energy Efficient Clustering Algorithm for Wireless Sensor Networks

In previous years, wireless sensor networks (WSNs) have fascinated lot of consideration from the scientific and technical society. The distributed characteristics and dynamic topology of sensor networks initiates very peculiar necessities in routing schemes that supposed to be met. The key feature of efficient routing protocol is energy expenditure and extension in lifetime of network. In past few years, various routing algorithms have been presented for WSNs. In this work, we focus on cluster based routing algorithms and propose a new algorithm for routing in WSNs. We perform the analysis of our new cluster based algorithms with existing algorithm on the basis of performance metrics. Simulation results shows that proposed algorithm outperform the other existing algorithms of his category.

Percolation analysis for constructing a robust modular topology based on a binary-dynamics model

In the context of Internet of Things, virtualization of wireless sensor networks is a crucial technology for sharing sensors as infrastructure. In our previous work, we proposed a brain-inspired method for constructing a robust and adaptive virtual wireless sensor network topology and showed that the method of constructing links between modules has crucial effect on robustness and adaptivity of the constructed virtual wireless sensor network topology. However, the best way of constructing a robust and adaptive virtual wireless sensor network topology is still unclear. Therefore, in this article, we use an analytical approach and propose a method for clarifying robustness of a topology according to the method of constructing links between modules. We add a new tool to a binary-dynamics model which is an analytical method for investigating percolation dynamics on a modular network. Evaluation by simulation showed that graphs in which the number of nodes selected as endpoint nodes of inter-module links and the degrees of the endpoint nodes before the link addition are large have robust connectivity in terms of the point of fragmentation of the network into modules when we fix the degree of the endpoint nodes after the link addition. After the point, the internal structure of modules may matter more. We additionally investigate an applicable range of our proposed method.

A recombination information process method of missing data in WSN

ABSTRACTWith reference to reducing dimensionality or predicting data missing mechanism, this paper approaches the function between distribution of missing data and topology of wireless sensor networks, and presents a recombination information missing data process method. As the missing data normally come from communication especially media accessing mechanism of carrier sense multiple access (CSMA) or time division multiple access (TDMA), the paper shows that the packets loss process is normally Poisson stochastic process. And the paper studies maximum missing data rates of some different topology networks (for example, the topology of star, hierarchical cluster tree, and mesh). In the end, the paper estimates the recombination information missing data processes method by simulations and experiments.

Location Dependent Key Predistribution Scheme for Square Grid and Hexagonal Grid

Objective: To design a location aware key pre-distribution scheme for wireless sensor network deployed in square grid and hexagonal grid with minimum possible keys stored in each nodes. Methods/Statistical analysis: In location dependent key predistribution coordinates of the sensor nodes are known prior to deployment. Therefore their connectivity is known prior. Grid structured network is well fitted topology for various types of application in sensor network. Coverage and connectivity issues have been studied in these kinds of network. Security for these special structured is emerging topic of study and key predistribution as well. Findings: To efficient use of preloaded keys of the sensor nodes, the keys need to be distributed smartly. As in case of a square or hexagonal grid locations are known prior therefore it gives advantage in distributing the symmetric keys over the nodes. In this paper, we propose an algorithm using adjacency matrix of the network for square and hexagonal grid network. We analyze resilience against popular attack like node capture attack and node fabrication attack at the end of this paper. Application/Improvements: Staring with single key distribution, pair-wise key distribution, random key distribution and so on, various key predistribution schemes have been proposed in literature. Taking the advantage of structured topology of sensor network the algorithm enhances the overall performance.

Robust Hierarchical Data Fusion Scheme for Large-Scale Sensor Network

The advanced driver assistant system (ADAS) requires the collection of a large amount of information including road conditions, environment, vehicle status, condition of the driver, and other useful data. In this regard, large-scale sensor networks can be an appropriate solution since they have been designed for this purpose. Recent advances in sensor network technology have enabled the management and monitoring of large-scale tasks such as the monitoring of road surface temperature on a highway. In this paper, we consider the estimation and fusion problems of the large-scale sensor networks used in the ADAS. Hierarchical fusion architecture is proposed for an arbitrary topology of the large-scale sensor network. A robust cluster estimator is proposed to achieve robustness of the network against outliers or failure of sensors. Lastly, a robust hierarchical data fusion scheme is proposed for the communication channel between the clusters and fusion center, considering the non-Gaussian channel noise, which is typical in communication systems.

Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems.

Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K-center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms.

Energy-efficient multi-mode clusters maintenance (M2CM) for hierarchical wireless sensor networks

How to energy-efficiently maintain the topology of wireless sensor networks (WSNs) is still a difficult problem because of their numerous nodes, highly dynamic nature, varied application scenarios and limited resources. An energy-efficient multi-mode clusters maintenance (M2CM) method is proposed based on localized and event-driven mechanism in this work, which is different from the conventional clusters maintenance model with always periodically re-clustered among the whole network style based on time-trigger for hierarchical WSNs. M2CM can meet such demands of clusters maintenance as adaptive local maintenance for the damaged clusters according to its changes in time and space field., the triggers of M2CM include such events as nodes' residual energy being under the threshold, the load imbalance of cluster head, joining in or exiting from any cluster for new node or disable one, etc. Based on neighboring relationship of the damaged clusters, one can start a single cluster (inner-cluster) maintenance or clusters (inter-cluster) maintenance program to meet diverse demands in the topology management of hierarchical WSNs. The experiment results based on NS2 simulation show that the proposed method can significantly save energy used in maintaining a damaged network, effectively narrow down the influenced area of clusters maintenance, and increase transmitted data and prolong lifetime of network compared to the traditional schemes.

System-Level Energy Balance for Maximizing Network Lifetime in WSNs

Due to the limited energy supply, prolonging the network lifetime as much as possible is an important concern when designing the topology of wireless sensor networks. Different from designing complex routing and controlling sink node mobility, this paper aims at achieving system-level energy balance to maximize network lifetime. A general multi-ring structural model is developed to formulate the network lifetime by considering data flow, energy consumption on data transmission and receiving, and wireless harvesting. To explore the factors influencing the maximum network lifetime, a general optimization model considering ring depth, node densities, and inner ring transmitting probabilities is developed. Accordingly, the network optimization problem is divided into the following three scenarios: power control, non-uniform deployment, and probabilistic switching (ProSwit) routing. Particularly, ProSwit is a new method for maximizing network lifetime, and has not been considered before. Simulation results demonstrate that system-level energy balance with multi-hop routing can be achieved by exploiting all the above three schemes. Some useful topology control conclusions for prolonging network lifetime are also concluded.

Reconstruction algorithm of chaotic signal based on generalized likelihood ratio threshold-decision

Blind signal reconstruction in sensor arrays is usually a highly nonlinear and non-Gaussian problem, and nonlinear filtering is an effective way to realize state estimation from available observations. Developing the processing problem of blind signal in wireless sensor networks (WSNs) will greatly extend the application scope. Meanwhile, it also meets great challenges such as energy and bandwidth constrained. For solving the constrained problem in WSNs, the observed signals must be quantified before sending to the fusion center, which makes the overall noise unable to be modeled accurately by simple probabilistic model. To study the reconstruction issue of chaotic signal with unknown statistics in WSNs, a reconstructed method of chaotic signal based on a cost reference particle filter (CRPF) is proposed in this paper. The cost recerence cubature particle filter (CRCPF) algorithm adopts cubature-point transformation to enhance the accuracy of prediction particles, and cost-risk functions are defined to complete particle propagation. The effectiveness of proposed CRCPF algorithm is verified in the sensor network with a fusion center. Moreover, a generalized likelihood ratio functionis obtained by the cost increment of local reconstructed signals in the cluster-based sensor network topology model, which is used to reduce the network energy consumption by selecting working nodes. Simulation results show that compared with CPF and CRPF, the proposed algorithm CRCPF attains good performance in a WSN with unknown noise statistics. Meanwhile, the CRCPF algorithm realizes the compromise between energy consumption and reconstruction accuracy simultaneously, which indicates that the proposed CRCPF algorithm has the potential to extend other application scope.

A mechanism of topology optimization for underwater acoustic sensor networks based on autonomous underwater vehicles

Limited energy, high mobility, and unsteady acoustic communication links render the underwater acoustic sensor networks subject to performance reduction. To solve this problem, a topology optimization method, also called TO-A algorithm, is developed based on topology reconfiguration. First, the proposed method optimizes the coverage rate of underwater acoustic sensor networks by adjusting the location of sensor nodes through simulating fish behaviors. Second, to optimize the connectivity of underwater acoustic sensor networks, the proposed method, using edge nodes, repairs disconnected positions and eliminates key nodes in underwater acoustic sensor networks. Third, a topology optimization strategy, also called TO-DA algorithm, is developed for Double-autonomous underwater vehicles to improve the robustness and adaptability of the network topology. When the inherent law of underwater acoustic sensor networks topology formation is further found, the method for optimizing network topology is proposed, which based on the triangle principle eliminates those key nodes and can help with the survivability of network regeneration. The method proves reasonable and valid by stimulation and contrast examinations. The comparison of TO-A algorithm and TO-DA algorithm shows that under low energy consumption, TO-A algorithm can keep the network coverage at about 97% for a long time, connectivity rate above 89%, while the TO-DA algorithm can improve the survivability of the network by above 50% at the expense of 8.5% of the network coverage.

Routing Topologies of Wireless Sensor Networks for Health Monitoring of a Cultural Heritage Site.

This paper provides a performance evaluation of tree and mesh routing topologies of wireless sensor networks (WSNs) in a cultural heritage site. The historical site selected was San Juan Bautista church in Talamanca de Jarama (Madrid, Spain). We report the preliminary analysis required to study the effects of heating in this historical location using WSNs to monitor the temperature and humidity conditions during periods of weeks. To test which routing topology was better for this kind of application, the WSNs were first deployed on the upper floor of the CAEND institute in Arganda del Rey simulating the church deployment, but in the former scenario there was no direct line of sight between the WSN elements. Two parameters were selected to evaluate the performance of the routing topologies of WSNs: the percentage of received messages and the lifetime of the wireless sensor network. To analyze in more detail which topology gave the best performance, other communication parameters were also measured. The tree topology used was the collection tree protocol and the mesh topology was the XMESH provided by MEMSIC (Andover, MA, USA). For the scenarios presented in this paper, it can be concluded that the tree topology lost fewer messages than the mesh topology.

A Movement-Assisted Deployment of Collaborating Autonomous Sensors for Indoor and Outdoor Environment Monitoring.

Using mobile robots or unmanned vehicles to assist optimal wireless sensors deployment in a working space can significantly enhance the capability to investigate unknown environments. This paper addresses the issues of the application of numerical optimization and computer simulation techniques to on-line calculation of a wireless sensor network topology for monitoring and tracking purposes. We focus on the design of a self-organizing and collaborative mobile network that enables a continuous data transmission to the data sink (base station) and automatically adapts its behavior to changes in the environment to achieve a common goal. The pre-defined and self-configuring approaches to the mobile-based deployment of sensors are compared and discussed. A family of novel algorithms for the optimal placement of mobile wireless devices for permanent monitoring of indoor and outdoor dynamic environments is described. They employ a network connectivity-maintaining mobility model utilizing the concept of the virtual potential function for calculating the motion trajectories of platforms carrying sensors. Their quality and utility have been justified through simulation experiments and are discussed in the final part of the paper.

A Wireless Sensor Network Topology Control Method Based on Hypergraph

A Wireless Sensor Network (WSN) model is proposed. The model is based on the hypergraph theory which partitions the topology structure of the WSN. The partition is performed intermittently to optimize the structure of the WSN. Compared with HEED, the proposed model preforms better to extend the network lifetime. Although the model is centralized, it is applicable for most scenarios where a distributed model is needed.

Distributed trigger counting algorithms for arbitrary network topology

AbstractThe distributed trigger counting (DTC) problem is a fundamental block for many distributed applications. Particularly, such a problem is to raise an alert while the number of triggers received by the whole system reaches a pre‐defined amount. There have been a few algorithms proposed to solve the DTC problem in the literature. However, these existing algorithms are all under the assumption that each process knows what kind of network topology the whole system forms as well as playing distinct kind of role in the system. The foregoing assumption is not practical for wireless sensor networks because the network topology of a wireless sensor network cannot be obtained in advance, and the roles of all processes are basically identical during the computation. In this paper, we propose a novel distributed algorithm to solve the DTC problem, free of any aforementioned global assumption. Moreover, in order to reduce the message complexity of our algorithm, we further propose a more message‐efficient version, only with one extra requirement that all processes have learned ahead the number of processes in the system. Copyright © 2016 John Wiley & Sons, Ltd.

Stability analysis of decentralized event-triggered H∞ control using the quadratic convex approach

This paper studies the stability analysis of the decentralized event-triggered H∞ control with communication delays using the quadratic convex approach. Unlike the decentralized event-triggered mechanism (ETM), which only uses the information from the sensor itself by considering the communication topology of the wireless sensor network, a more general decentralized ETM is first proposed by using the information from both the sensor itself and its neighbours. Then, a time-delay system model with parameters of the decentralized ETM, directed graph information, communication delays and external disturbances is presented. In addition, novel delay-dependent asymptotic stability criteria are derived by using the augmented Lyapunov–Krasovski functional (LKF), which contains the cross terms of variables and quadratic terms multiplied by a higher degree scalar function. Unlike some prior results using the first-order convex combination property, our derivation applies the quadratic convex approach with the augmented LKF, which results in less conservatism. Moreover, sufficient conditions for the co-design of the controller and the decentralized ETM are obtained. Finally, numerical examples confirm the effectiveness of the proposed method.

Tackling the flip ambiguity in wireless sensor network localization and beyond

There have been significant advances in range-based numerical methods for sensor network localizations over the past decade. However, there remain a few challenges to be resolved to satisfaction. Those issues include, for example, the flip ambiguity, high level of noises in distance measurements, and irregular topology of the concerning network. Each or a combination of them often severely degrades the otherwise good performance of existing methods. Integrating the connectivity constraints is an effective way to deal with those issues. However, there are too many of such constraints, especially in a large and sparse network. This presents a challenging computational problem to existing methods. In this paper, we propose a convex optimization model based on the Euclidean Distance Matrix (EDM). In our model, the connectivity constraints can be simply represented as lower and upper bounds on the elements of EDM, resulting in a standard 3-block quadratic conic programming, which can be efficiently solved by a recently proposed 3-block alternating direction method of multipliers. Numerical experiments show that the EDM model effectively eliminates the flip ambiguity and retains robustness in terms of being resistance to irregular wireless sensor network topology and high noise levels.

Adaptive and intelligent wireless sensor networks through neural networks: an illustration for infrastructure adaptation through Hopfield network

This paper proposes embedding an artificial neural network into a wireless sensor network in fully parallel and distributed computation mode. The goal is to equip the wireless sensor network with computational intelligence and adaptation capability for enhanced autonomous operation. The applicability and utility of the proposed concept is demonstrated through a case study whereby a Hopfield neural network configured as a static optimizer for the weakly-connected dominating set problem is embedded into a wireless sensor network to enable it to adapt its network infrastructure to potential changes on-the-fly and following deployment in the field. Minimum weakly-connected dominating set defined for the graph model of the wireless sensor network topology is employed to represent the network infrastructure and can be recomputed each time the sensor network topology changes. A simulation study using the TOSSIM emulator for TinyOS-Mica sensor network platform was performed for mote counts of up to 1000. Time complexity, message complexity and solution quality measures were assessed and evaluated for the case study. Simulation results indicated that the wireless sensor network embedded with Hopfield neural network as a static optimizer performed competitively with other local or distributed algorithms for the weakly connected dominating set problem to establish its feasibility.

Heuristics for designing multi-sink clustered WSN topologies

In this study, the problem of building cluster-based topologies for Wireless Sensor Networks with several sinks is considered. The optimization relies on different levels of decision: choosing which sensors are masters and balancing the load among sinks. The topology associated with each sink is modeled as an Independent Dominating Set with Connecting requirements (IDSC). Thus, the solution is a partition of a given graph into as many IDSC as there are sinks. In addition, several optimization criteria are proposed to implicitly or explicitly balance the topology. The network lifetime is improved since it benefits from a clustered structure and the number of hops control. The former reduces the average amount of messages to be sent and the latter improves the average energy consumption for messages to be sent. Different combinations of criteria are proposed in lexicographical order. They are compared in terms of maximum number of clusters per topology, of deviation between the smallest and the biggest number of clusters considering all topologies, and of total number of clusters in the final topology. Two local searches, a two-step local search and a Variable Neighborhood Descent, are developed. Each one is embedded into a multi-start framework. Results are provided for instances with up to 10000 sensors and up to five sinks.

Topology Management for Reducing Energy Consumption and Tolerating Failures in Wireless Sensor Networks

We investigated energy efficient and fault tolerant topologies for wireless sensor networks (WSNs), addressing the need to minimize communication distances because the energy used for communication is proportional to the 2nd to 6th power of the distance. We also investigated the energy hole phenomenon, in which non-uniform energy usage among nodes causes non-uniform lifetimes. This, in turn, increases the communication distances and results in a premature shutdown of the entire network. Because some sensor nodes in a WSN may be unreliable, it must be tolerant to faults. A routing algorithm called the “energy hole aware energy efficient communication routing algorithm” (EHAEC) was previously proposed. It solves the energy hole problem to the maximum extent possible while minimizing the amount of energy used for communication, by generating an energy efficient spanning tree. In this paper, we propose two provisioned fault tolerance algorithms: EHAEC for one-fault tolerance (EHAEC-1FT) and the active spare selecting algorithm (ASSA). EHAEC-1FT is a variation of EHAEC. It identifies redundant communication routes using the EHAEC tree and guarantees 2-connectivity (i.e., tolerates the failure of one node). The ASSA attempts to find active spare nodes for critical nodes. It uses two impact factors, I± and I² , which can be adjusted so that the result is either more fault tolerant or energy efficient. The spare nodes fix failures by replacing them. In our simulations, EHAEC was 3.4 to 4.8 times more energy efficient than direct data transmission, and thus extended the WSN lifetime. EHAEC-1FT outperformed EHAEC in terms of energy efficiency when fault tolerance was the most important, and a fault tolerant redundancy was created when or before a failure occurred. Moreover, we demonstrated that the ASSA was more energy efficient than EHAEC-1FT, and the effect of using different I± and I² .

Investigations optimum scheduling and TCP mechanism of hybrid topology sensor network in building SHM

Abstract Sensor technology has opened up numerous opportunities to advanced health and maintenance monitoring of civil infrastructure such as large buildings. Compare to traditional tactics, it offers a better way of providing relevant information regarding the condition of building structure at a lower price and greater range. Numerous domestic buildings, especially long-span buildings, have a low-profile frequency response that is challenging to accurately measure with the application of sensors suitable for integration with lower-cost, lower-power-profile wireless sensor networks. To cover the whole area of interest, sensor network topology is one of the most important issues. The objective of this article is to investigate of hybrid topology scheduling algorithm to determine the optimum TCP (Transmission Control Mechanism) mechanism for assessing large building structural health data using various kinds TCP and scheduling algorithm. Result show that, the Full TCP mechanism is selected as optimum TCP mechanism for monitoring building structural health data.