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 Green Clustering Protocol for Mobile Sensor Network Using Particle Swarm Optimization

Energy consumption of sensor nodes is one of the crucial issues in prolonging the lifetime of wireless sensor networks. One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization （PSO） algorithm. We define a new fitness function that can optimize the energy consumption of the whole network and minimize the relative distance between cluster heads and their respective member nodes. We also take into account the mobility factor when defining the cluster membership, so that the sensor nodes can join the cluster that has the similar mobility pattern. The performance of the proposed protocol is compared with well-known clustering protocols developed for wireless sensor networks such as LEACH （low-energy adaptive clustering hierarchy） and protocols designed for sensor networks with mobile nodes called CM-IR （clustering mobility-invalid round）. In addition, we also modify the improved version of LEACH called MLEACH-C, so that it is applicable to the mobile sensor nodes environment. Simulation results demonstrate that the proposed protocol using PSO algorithm can improve the energy consumption of the network, achieve better network lifetime, and increase the data delivered at the base station.

Lightweight Key Management Scheme Using Fuzzy Extractor for Wireless Mobile Sensor Network

The mature design of wireless mobile sensor network makes it to be used in vast verities of applications including from home used to the security surveillance.All such types of applications based on wireless mobile sensor network are generally using real time data,most of them are interested in real time communication directly from cluster head of cluster instead of a base station in cluster network.This would be possible if an external user allows to directly access real time data from the cluster head in cluster wireless mobile sensor network instead of accessing data from base station.But this leads to a serious security breach and degrades the performance of any security protocol available in this domain.Most existing schemes for authentication and cluster key management for external users,exchange a number of messages between cluster head and base station to allow external to access real time data from the base station instead of cluster head.This increase communication cost and delay in such real time access information.To handle this critical issue in cluster wireless mobile sensor network,we propose a lightweight authentication and key management scheme using a fuzzy extractor.In this scheme,any external user can access data directly from the cluster head of any cluster without the involvement of the base station.The proposed scheme only uses the one-way hash functions and bitwise XOR operations,apart from the fuzzy extractor method for the user biometric verification at the login phase.The presented scheme supports scalability for an increasing number of nodes using polynomials.The proposed scheme increases the life-time of the network by decreasing the key pool size.

Distributed nonuniform deployment for target monitoring in mobile sensor networks

In this paper,three distributed and scalable nonuniform deployment algorithms in order to enhance the quality of monitoring(QoM).Mobile sensors are to be deployed around a target of interest which can be stationary or moving,and to approximate a given weight function which is a measure of information or event density.The first two algorithms generate nonuniform deployments by inverse-transformations from a uniform deployment.They handle the situations of global coordinate system which is available and not with appropriate assumptions,respectively.The third algorithm,which relocates sensors to adjust inter-node distances based on the local measurements only,is suitable for general cases.The simulation results demonstrate the proposed algorithms can achieve reliable and satisfactory deployments.

Distributed Aggregation Algorithms for Mobile Sensor Networks with Group Mobility Model

In many applications of mobile sensor networks, such as water flow monitoring and disaster rescue, the nodes in the network can move together or separate temporarily. The dynamic network topology makes traditional spanning-tree-based aggregation algorithms invalid in mobile sensor networks. In this paper, we first present a distributed clustering algorithm which divides mobile sensor nodes into several groups, and then propose two distributed aggregation algorithms, Distance-AGG （Aggregation based on Distance）, and Probability-AGG （Aggregation based on Probability）. Both of these two algorithms conduct an aggregation query in three phases： query dissemination, intra-group aggregation, and inter-group aggregation. These two algorithms are efficient especially in mobile networks. We evaluate the performance of the proposed algorithms in terms of aggregation accuracy, energy efficiency, and query delay through ns-2 simulations. The results show that Distance-AGG and Probability-AGG can obtain higher accuracy with lower transmission and query delay than the existing aggregation algorithms.

Energy-efficient localization and target tracking via underwater mobile sensor networks

Underwater mobile sensor networks(UMSNs) with free-floating sensors are more suitable for understanding the immense underwater environment. Target tracking, whose performance depends on sensor localization accuracy, is one of the broad applications of UMSNs. However, in UMSNs, sensors move with environmental forces,so their positions change continuously, which poses a challenge on the accuracy of sensor localization and target tracking. We propose a high-accuracy localization with mobility prediction(HLMP) algorithm to acquire relatively accurate sensor location estimates. The HLMP algorithm exploits sensor mobility characteristics and the multistep Levinson-Durbin algorithm to predict future positions. Furthermore, we present a simultaneous localization and target tracking(SLAT) algorithm to update sensor locations based on measurements during the process of target tracking. Simulation results demonstrate that the HLMP algorithm can improve localization accuracy significantly with low energy consumption and that the SLAT algorithm can further decrease the sensor localization error. In addition, results prove that a better localization accuracy will synchronously improve the target tracking performance.

Velocity-Varying Target Tracking of Mobile Sensor Network Based on Flocking Control

Existing coupled distributed estimation and motion control strategies of mobile sensor networks present limitations in velocity-varying target tracking. Therefore, a velocity-varying target tracking algorithm based on flocking control is proposed herein. The Kalman-consensus filter is utilized to estimate the position, velocity and acceleration of a target. The flocking control algorithm with a velocity-varying virtual leader enables the position of the center of the mobile sensor network to converge to that of the target. By applying an effective cascading Lyapunov method, stability analysis is performed. Simulation results are provided to validate the feasibility of the proposed algorithm.

Mobile observation for distributed parameter system with moving boundary over mobile sensor networks

This paper considers the state observation for a class of distributed parameter systems(DPSs)with moving boundaries modelled by parabolic partial differential equations(PDEs).The method of mobile observation is presented to improve the observation performance of the systems and to eliminate the influence of moving boundaries on system observation with the aids of mobile sensor networks(MSNs).The MSNs which can move throughout the time-dependent spatial domain are used to provide the spatially averaged observations of the DPSs.By using the abstract evolution equation theory of parabolic PDEs and the Lyapunov stability arguments,a centralised observer is designed and a mobile control scheme for each of the mobile sensors is presented while taking account of the dynamics of the MSNs.A numerical example is finally presented to illustrate the effectiveness and the advantages of the proposed approach.

Grid-Based Localization Mechanism with Mobile Reference Node in Wireless Sensor Networks

Wireless sensor networks （WSNs） are based on monitoring or managing the sensing area by using the location information with sensor nodes. Most sensor nodes require hardware support or receive packets with location information to estimate their locations, which needs lots of time or costs. In this paper we proposed a localization mechanism using a mobile reference node （MRN） and trilateration in WSNs to reduce the energy consumption and location error. The simulation results demonstrate that the proposed mechanism can obtain more unknown nodes locations by the mobile reference node moving scheme and will decreases the energy consumption and average ocation error.

Mechanism analysis of regulating Turing instability and Hopf bifurcation of malware propagation in mobile wireless sensor networks

A dynamical model is constructed to depict the spatial-temporal evolution of malware in mobile wireless sensor networks(MWSNs). Based on such a model, we design a hybrid control scheme combining parameter perturbation and state feedback to effectively manipulate the spatiotemporal dynamics of malware propagation. The hybrid control can not only suppress the Turing instability caused by diffusion factor but can also adjust the occurrence of Hopf bifurcation induced by time delay. Numerical simulation results show that the hybrid control strategy can efficiently manipulate the transmission dynamics to achieve our expected desired properties, thus reducing the harm of malware propagation to MWSNs.

Real-time air pollution monitoring with sensors on city bus

This paper presents an experimental study on real-time air pollution monitoring using wireless sensors on public transport vehicles.The study is part of the GreenIoT project in Sweden,which utilizes Internet-of-Things to measure air pollution level in the city center of Uppsala.Through deploying low-cost wireless sensors,it is possible to obtain more fine-grained and real-time air pollution levels at different locations.The sensors on public transport vehicles complement the readings from stationary sensors and the only ground level monitoring station in Uppsala.The paper describes the deployment of wireless sensors on Uppsala buses and the integration of the mobile sensor network with the GreenIoT testbed.Extensive experiments have been conducted to evaluate the communication quality and data quality of the system.

Detecting and adaptive responding mechanism for mobile WSN

Mobile wireless sensor network(WSN)composed by mobile terminals has a dynamic topology and can be widely used in various fields.However,the lack of centralized control,dynamic topology and limited energy supply make the network layer of mobile WSN be vulnerable to multiple attacks,such as black hole(BH),gray hole(GH),flooding attacks(FA)and rushing attacks(RU).Existing researches on intrusion attacks against mobile WSN,currently,tend to focus on targeted detection of certain types of attacks.The defense methods also have clear directionality and is unable to deal with indeterminate intrusion attacks.Therefore,this work will design an indeterminate intrusion attack oriented detecting and adaptive responding mechanism for mobile WSN.The proposed mechanism first uses a test sliding window(TSW)to improve the detecting accuracy,then constructs parameter models of confidence on attack(COA),network performance degradation(NPD)and adaptive responding behaviors list,finally adaptively responds according to the decision table,so as to improve the universality and flexibility of the detecting and adaptive responding mechanism.The simulation results show that the proposed mechanism can achieve multiple types of intrusion detecting in multiple attack scenarios,and can achieve effective response under low network consumption.

Cooperative distributed target tracking algorithm in mobile wireless sensor networks

The paper proposes a cooperative distributed target tracking algorithm in mobile wireless sensor networks.There are two main components in the algorithm:distributed sensor-target assignment and sensor motion control.In the key idea of the sensor-target assignment,sensors are considered as autonomous agents and the defined objective function of each sensor concentrates on two fundamental factors:the tracking accuracy and the tracking cost.Compared with the centralized algorithm and the noncooperative distributed algorithm,the proposed approach will not only lead to reasonable measuring performance but also benefit system with low computational complexity and communication energy.Also,a sensor motion algorithm based on gradient control is presented in the paper to trace the targets to reduce tracking error.Simulation results show that the cooperative distributed sensor assignment algorithm has advantages over the centralized algorithm without sacrificing much tracking performance.

A New Protocol for the Detection of Node Replication Attacks in Mobile Wireless Sensor Networks

Wireless sensor networks （WSNs） are often deployed in harsh environments. Thus adversaries can capture some nodes, replicate them and deploy those replicas back into the strategic positions in the network to launch a variety of attacks. These are referred to as node replication attacks. Some methods of defending against node replication attacks have been proposed, yet they are not very suitable for the mobile wireless sensor networks. In this paper, we propose a new protocol to detect the replicas in mobile WSNs. In this protocol, polynomial-based pair-wise key pre-distribution scheme and Counting Bloom Filters are used to guarantee that the replicas can never lie about their real identifiers and collect the number of pair-wise keys established by each sensor node. Replicas are detected by looking at whether the number of pair-wise keys established by them exceeds the threshold. We also derive accurate closed form expression for the expected number of pair-wise keys established by each node, under commonly used random waypoint model. Analyses and simulations verify that the protocol accurately detects the replicas in the mobile WSNs and supports their removal.

Mobile sensors’patrol path planning in unobservable border region

Purpose-The border control becomes challenging when a protected region is large and there is a limited number of border patrols.This research paper proposes a novel heuristic-based patrol path planning scheme in order to efficiently patrol with resource scarcity.Design/methodology/approach-The trespasser influencing score,which is determined from the environmental characteristics and trespassing statistic of the region,is used as a heuristic for measuring a chance of approaching a trespasser.The patrol plan is occasionally updated with a new trespassing statistic during a border operation.The performance of the proposed patrol path planning scheme was evaluated and compared with other patrol path planning schemes by the empirical experiment under different scenarios.Findings-The result from the experiment indicates that the proposed patrol planning outperforms other patrol path planning schemes in terms of the trespasser detection rate,when more environment-aware trespassers are in the region.Research limitations/implications-The experiment was conducted through simulated agents in simulated environment,which were assumed to mimic real behavior and environment.Originality/value-This research paper contributes a heuristic-based patrol path planning scheme that applies the environmental characteristics and dynamic statistic of the region,as well as a border surveillance problem model that would be useful for mobile sensor planning in a border surveillance application.

Distributed Algorithms for Event Reporting in Mobile-Sink WSNs for Internet of Things

Wireless Sensor Networks（WSNs） have many applications, such as climate monitoring systems, fire detection, smart homes, and smart cities. It is expected that WSNs will be integrated into the Internet of Things（IoT）and participate in various tasks. WSNs play an important role monitoring and reporting environment information and collecting surrounding context. In this paper we consider a WSN deployed for an application such as environment monitoring, and a mobile sink which acts as the gateway between the Internet and the WSN. Data gathering is a challenging problem in WSNs and in the IoT because the information has to be available quickly and effectively without delays and redundancies. In this paper we propose several distributed algorithms for composite event detection and reporting to a mobile sink. Once data is collected by the sink, it can be shared using the IoT infrastructure. We analyze the performance of our algorithms using WSNet simulator, which is specially designed for event-based WSNs. We measure various metrics such as average residual energy, percentage of composite events processed successfully at the sink, and the average number of hops to reach the sink.