Distributed localization for anchor-free sensor networks

Geographic location of nodes is very useful in a sensor network. Previous localization algorithms assume that there exist some anchor nodes in this kind of network, and then other nodes are estimated to create their coordinates. Once there are not anchors to be deployed, those localization algorithms will be invalidated. Many papers in this field focus on anchor-based solutions. The use of anchors introduces many limitations, since anchors require external equipments such as global position system, cause additional power consumption. A novel positioning algorithm is proposed to use a virtual coordinate system based on a new concept--virtual anchor. It is executed in a distributed fashion according to the connectivity of a node and the measured distances to its neighbors. Both the adjacent member information and the ranging distance result are combined to generate the estimated position of a network, one of which is independently adopted for localization previously. At the position refinement stage the intermediate estimation of a node begins to be evaluated on its reliability for position mutation; thus the positioning optimization process of the whole network is avoided falling into a local optimal solution. Simulation results prove that the algorithm can resolve the distributed localization problem for anchor-free sensor networks, and is superior to previous methods in terms of its positioning capability under a variety of circumstances.

Optimal distributed resource allocation in a wireless sensor network for control systems

Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited. Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.

Improved control of distributed parameter systems using wireless sensor and actuator networks:An observer-based method

In this paper,the control problem of distributed parameter systems is investigated by using wireless sensor and actuator networks with the observer-based method.Firstly,a centralized observer which makes use of the measurement information provided by the fixed sensors is designed to estimate the distributed parameter systems.The mobile agents,each of which is affixed with a controller and an actuator,can provide the observer-based control for the target systems.By using Lyapunov stability arguments,the stability for the estimation error system and distributed parameter control system is proved,meanwhile a guidance scheme for each mobile actuator is provided to improve the control performance.A numerical example is finally used to demonstrate the effectiveness and the advantages of the proposed approaches.

Distributed event region fault-tolerance based on weighted distance for wireless sensor networks

Event region detection is the important application for wireless sensor networks（WSNs）, where the existing faulty sensors would lead to drastic deterioration of network quality of service.Considering single-moment nodes fault-tolerance, a novel distributed fault-tolerant detection algorithm named distributed fault-tolerance based on weighted distance（DFWD） is proposed, which exploits the spatial correlation among sensor nodes and their redundant information.In sensor networks, neighborhood sensor nodes will be endowed with different relative weights respectively according to the distances between them and the central node.Having syncretized the weighted information of dual-neighborhood nodes appropriately, it is reasonable to decide the ultimate status of the central sensor node.Simultaneously, readings of faulty sensors would be corrected during this process.Simulation results demonstrate that the DFWD has a higher fault detection accuracy compared with other algorithms, and when the sensor fault probability is 10%, the DFWD can still correct more than 91% faulty sensor nodes, which significantly improves the performance of the whole sensor network.

An Approach of Distributed Joint Optimization for Cluster-based Wireless Sensor Networks

Wireless sensor networks (WSNs) are energyconstrained, so energy saving is one of the most important issues in typical applications. The clustered WSN topology is considered in this paper. To achieve the balance of energy consumption and utility of network resources, we explicitly model and factor the effect of power and rate. A novel joint optimization model is proposed with the protection for cluster head. By the mean of a choice of two appropriate sub-utility functions, the distributed iterative algorithm is obtained. The convergence of the proposed iterative algorithm is proved analytically. We consider general dual decomposition method to realize variable separation and distributed computation, which is practical in large-scale sensor networks. Numerical results show that the proposed joint optimal algorithm converges to the optimal power allocation and rate transmission, and validate the performance in terms of prolonging of network lifetime and improvement of throughput. © 2014 Chinese Association of Automation.

Distributed Plume Source Localization Using Hierarchical Sensor Networks

A hierarchical wireless sensor networks(WSN) was proposed to estimate the plume source location.Such WSN can be of tremendous help to emergency personnel trying to protect people from terrorist attacks or responding to an accident.The entire surveillant field is divided into several small sub-regions.In each sub-region,the localization algorithm based on the improved particle filter(IPF) was performed to estimate the location.Some improved methods such as weighted centroid,residual resampling were introduced to the IPF algorithm to increase the localization performance.This distributed estimation method eliminates many drawbacks inherent with the traditional centralized optimization method.Simulation results show that localization algorithm is efficient for estimating the plume source location.

ENERGY EFFICIENT DISTRIBUTED STEGANOGRAPHY FOR SECURE COMMUNICATION IN WIRELESS MULTIMEDIA SENSOR NETWORKS

A secure communication mechanism is necessary in the applications of Wireless Multimedia Sensor Networks (WMSNs), which is more vulnerable to security attacks due to the presence of multimedia data. Additionally, given the limited technological resources (in term of energy, computation, bandwidth, and storage) of sensor nodes, security and privacy policies have to be combined with energy-aware algorithms and distributed processing of multimedia contents in WMSNs. To solve these problems in this paper, an energy efficient distributed steganography scheme, which combines steganography technique with the concept of distributed computing, is proposed for secure communication in WMSNs. The simulation results show that the proposed method can achieve considerable energy efficiency while assuring the communication security simultaneously.

Distributed Sensor Network Based on RFID System for Localization of Multiple Mobile Agents

This paper presents a distributed wireless sensor network for multiple mobile agents localization. Localization of mobile agents, such as mobile robots, humans, and moving objects, in an indoor space is essential for robot-robot interaction (RRI) and human-robot interaction (HRI). The standard localization system, which is based on sensors installed in the robot body, is not suitable for multiple agents. Therefore, the concept of sensor network, which uses wireless sensors distributed in a specified space, is used in this study. By analyzing related studies, two solutions are proposed for the localization of mobile agents including humans: a new hardware system and a new software algorithm. The first solution focuses on the architectural design of the wireless sensor network for multiple agent localization. A passive RFID system is used, and then the architecture of the sensor network is adapted to suit the target system. The second solution centers on a localization algorithm based on the sensor network. The proposed localization algorithm improves the accuracy in the multiple agent localization system. The algorithm uses the displacement conditions of the mobile agents and the recognition changes between the RFID tags and RFID reader. Through experiments using a real platform, the usefulness of the proposed system is verified.

Improved control for distributed parameter systems with time-dependent spatial domains utilizing mobile sensor-actuator networks

A guidance policy for controller performance enhancement utilizing mobile sensor-actuator networks （MSANs） is proposed for a class of distributed parameter systems （DPSs）, which are governed by diffusion partial differential equations （PDEs） with time-dependent spatial domains. Several sufficient conditions for controller performance enhancement are presented. First, the infinite dimensional operator theory is used to derive an abstract evolution equation of the systems under some rational assumptions on the operators, and a static output feedback controller is designed to control the spatial process. Then, based on Lyapunov stability arguments, guidance policies for collocated and non-collocated MSANs are provided to enhance the performance of the proposed controller, which show that the time-dependent characteristic of the spatial domains can significantly affect the design of the mobile scheme. Finally, a simulation example illustrates the effectiveness of the proposed policy.

Estimation of spatially distributed processes using mobile sensor networks with missing measurements

This paper investigates the estimation problem for a spatially distributed process described by a partial differential equation with missing measurements.The randomly missing measurements are introduced in order to better reflect the reality in the sensor network.To improve the estimation performance for the spatially distributed process,a network of sensors which are allowed to move within the spatial domain is used.We aim to design an estimator which is used to approximate the distributed process and the mobile trajectories for sensors such that,for all possible missing measurements,the estimation error system is globally asymptotically stable in the mean square sense.By constructing Lyapunov functionals and using inequality analysis,the guidance scheme of every sensor and the convergence of the estimation error system are obtained.Finally,a numerical example is given to verify the effectiveness of the proposed estimator utilizing the proposed guidance scheme for sensors.

A Distributed Dynamic Clustering Algorithm for Wireless Sensor Networks

This paper proposes a distributed dynamic k-medoid clustering algorithm for wireless sensor networks （WSNs）, DDKCAWSN. Different from node-clustering algorithms and protocols for WSNs, the algorithm focuses on clustering data in the network. By sending the sink clustered data instead of practical ones, the algorithm can greatly reduce the size and the time of data communication, and further save the energy of the nodes in the network and prolong the system lifetime. Moreover, the algorithm improves the accuracy of the clustered data dynamically by updating the clusters periodically such as each day. Simulation results demonstrate the effectiveness of our approach for different metrics.

Distributed Target Location in Wireless Sensors Network: An Approach Using FPGA and Artificial Neural Network

This paper analyzes the implementation of an algorithm into a FPGA embedded and distributed target location method using the Received Signal Strength Indicator (RSSI). The objective is to show a method in which an embedded feedforward Artificial Neural Network (ANN) can estimate target location in a distributed fashion against anchor failure. We discuss the lack of FPGA implementation of equivalent methods and the benefits of using a robust platform. We introduce the description of the implementation and we explain the operation of the proposed method, followed by the calculated errors due to inherent Elliott function approximation and the discretization of decimal values used as free parameters in ANN. Furthermore, we show some target location estimation points in function of different numbers of anchor failures. Our contribution is to show that an FPGA embedded ANN implementation, with a few layers, can rapidly estimate target location in a distributed fashion and in presence of failures of anchor nodes considering accuracy, precision and execution time.

A New MAC Protocol for Moving Target in Distributed Wireless Sensor Networks

A wireless sensor network (WSN) is composed of many nodes with limited power supply;most nodes are stationary in the network which could probably involve a few mobile nodes. Various medium access control (MAC) protocols specially aimed at a target locating application for WSNs have been proposed. However, most of these protocols based on the problem of energy-limited does not consider the mobility of nodes. Therefore, in order to solve such problem, this paper proposes a MAC protocol—Distribute Moving-MAC (DM-MAC). Under the condition of keeping high network coverage, the protocol utilizes the redundancy of nodes to strengthen the robustness and energy efficiency of network, and decreases the packet loss rate of the mobile node’s communication links for realizing reliable communication of two nodes. Simulation indicates that the new protocol has higher energy efficiency, lower packet loss rate and higher network coverage which suit for wireless sensor network with mobile nodes well.

Distributed Algorithms for Maximizing Lifetime in Clustered Wireless Sensor Networks Using Energy-harvesting Relay Nodes

Motivated by recent developments in wireless sensor networks(WSNs),we present distributed clustering algorithms for maximizing the lifetime of WSNs,that is,the duration until the first node dies.We study the joint problem of prolonging network lifetime by introducing clustering techniques and energy-harvesting(EH)nodes.First,we propose a distributed clustering algorithm for maximizing the lifetime of clustered WSN,which includes EH nodes,serving as relay nodes for cluster heads(CHs).Second,graph-based and LP-based EH-CH matching algorithms are proposed which serve as benchmark algorithms.Extensive simulation results show that the proposed algorithms can achieve optimal or suboptimal solutions efficiently.

An Ellipsoidal Set-Membership Approach to Distributed Joint State and Sensor Fault Estimation of Autonomous Ground Vehicles

This paper is concerned with the problem of distributed joint state and sensor fault estimation for autonomous ground vehicles subject to unknown-but-bounded(UBB)external disturbance and measurement noise.In order to improve the estimation reliability and performance in cases of poor data collection and potential communication interruption,a multisensor network configuration is presented to cooperatively measure the vehicular yaw rate,and further compute local state and fault estimates.Toward this aim,an augmented descriptor vehicle model is first established,where the unknown sensor fault is modeled as an auxiliary state of the system model.Then,a new distributed ellipsoidal set-membership estimation approach is developed so as to construct an optimized bounding ellipsoidal set which guarantees to contain the vehicle’s true state and the sensor fault at each time step despite the existence of UBB disturbance and measurement noises.Furthermore,a convex optimization algorithm is put forward such that the gain matrix of each distributed estimator can be recursively obtained.Finally,simulation results are provided to validate the effectiveness of the proposed approach.

Self-Triggered Consensus Filtering over Asynchronous Communication Sensor Networks

In this paper,a self-triggered consensus filtering is developed for a class of discrete-time distributed filtering systems.Different from existing event-triggered filtering,the self-triggered one does not require to continuously judge the trigger condition at each sampling instant and can save computational burden while achieving good state estimation.The triggering policy is presented for pre-computing the next execution time for measurements according to the filter’s own data and the latest released data of its neighbors at the current time.However,a challenging problem is that data will be asynchronously transmitted within the filtering network because each node self-triggers independently.Therefore,a co-design of the self-triggered policy and asynchronous distributed filter is developed to ensure consensus of the state estimates.Finally,a numerical example is given to illustrate the effectiveness of the consensus filtering approach.

A Novel Negative Multinomial Distribution Based Energy-Efficient Reputation Modeling for Wireless Sensor Networks(WSNs)

In wireless sensor networks(WSNs),nodes are usually powered by batteries.Since the energy consumption directly impacts the network lifespan,energy saving is a vital issue in WSNs,especially in the designing phase of cryptographic algorithms.As a complementary mechanism,reputation has been applied to WSNs.Different from most reputation schemes that were based on beta distribution,negative multinomial distribution was deduced and its feasibility in the reputation modeling was proved.Through comparison tests with beta distribution based reputation in terms of the update computation,results show that the proposed method in this research is more energy-efficient for the reputation update and thus can better prolong the lifespan of WSNs.

RELOCATION ALGORITHM FOR NON-UNIFORM DISTRIBUTION IN MOBILE SENSOR NETWORK

Energy is the determinant factor for the survival of Mobile Sensor Networks(MSN).Based on the analysis of the energy distribution in this paper,a two-phase relocation algorithm is proposed based on the balance between the energy provision and energy consumption distribution.Our main objectives are to maximize the coverage percentage and to minimize the total distance of node movements.This algorithm is designed to meet the requirement of non-uniform distribution network applications,to extend the lifetime of MSN and to simplify the design of the routing protocol.In ad-dition,test results show the feasibility of our proposed relocation algorithm.

Analysis on the Resilience of Key Pre-distribution in Sensor Networks

Resilience against node capture is one of the main indicators of the key pre-distribution security in sensor networks.On providing the attack model and the definition of the resilience against node capture of sensor networks,the resilience of basic random key pre-distribution,Q-composite random key pre-distribution and their reinforced schemes are analyzed and compared in depth.Research results show that the size of key pool,the numbers of the keys stored in nodes and the value of Q determine the resilience of random key pre-distribution.The tradeoff between the resilience,security connectivity and costs in sensor networks is presented.These researches lay a foundation on the design of the secure protocol and the algorithm in the specific application environment of sensor networks.