LIS: Localization based on an intelligent distributed fuzzy system applied to a WSN

The localization of the sensor nodes is a fundamental problem in wireless sensor networks. There are a lot of different kinds of solutions in the literature. Some of them use external devices like GPS, while others use special hardware or implicit parameters in wireless communications.In applications like wildlife localization in a natural environment, where the power available and the weight are big restrictions, the use of hungry energy devices like GPS or hardware that add extra weight like mobile directional antenna is not a good solution.Due to these reasons it would be better to use the localization’s implicit characteristics in communications, such as connectivity, number of hops or RSSI. The measurement related to these parameters are currently integrated in most radio devices. These measurement techniques are based on the beacons’ transmissions between the devices.In the current study, a novel tracking distributed method, called LIS, for localization of the sensor nodes using moving devices in a network of static nodes, which have no additional hardware requirements is proposed.The position is obtained with the combination of two algorithms; one based on a local node using a fuzzy system to obtain a partial solution and the other based on a centralized method which merges all the partial solutions. The centralized algorithm is based on the calculation of the centroid of the partial solutions.Advantages of using fuzzy system versus the classical Centroid Localization (CL) algorithm without fuzzy preprocessing are compared with an ad hoc simulator made for testing localization algorithms.With this simulator, it is demonstrated that the proposed method obtains less localization errors and better accuracy than the centroid algorithm.     

Paired Measurement Localization: A Robust Approach for Wireless Localization

Location awareness remains the key for many potential future applications of distributed wireless ad hoc sensor networks (WSNs). While the location of a WSN node can be estimated by incorporating Global Positioning System (GPS) devices, it is not suitable to embed GPS receivers in every node considering the cost and size of these devices as well as from an optimization point of view. However, a small number of WSNs nodes called anchor nodes are able to resolve their location either through fixed deployment or using GPS receivers, and thereby provide the reference framework for localization of other nodes. The measurement devices in individual nodes are often erroneous for tiny WSNs nodes, and hence, robustness is a major issue for localization. In this paper, a theoretical localization framework in the presence of noise is postulated, which achieves accurate positioning compared to the existing theoretical approaches. The paired measurement localization (PML) strategy is evaluated through simulations under various noise conditions and environmental modeling, and practically verified by a testbed implementation with real motes. The results corroborate the improved positioning as well as the robustness of PML for ad hoc wireless sensor networks in the presence of noise.     

基于RSSI自适应三维加权质心定位算法

针对无线传感网络RSSI加权质心定位算法精度较低的问题,提出了一种采用RSSI值作为加权因子的三维加权质心定位算法。依据RSSI值自适应缩小定位区域,并根据筛选出的最优参考节点构建三维球体定位模型。仿真结果表明,改进的定位算法在相同测试条件下,在精度与稳定性上相较传统加权质心算法有了大幅提高。     

Monte Carlo localization of wireless sensor networks with a single mobile beacon

One of the most important tasks in sensor networks is to determine the physical location of sensory nodes as they may not all be equipped with GPS receivers. In this paper we propose a localization method for wireless sensor networks (WSNs) using a single mobile beacon. The sensor locations are maintained as probability distributions that are sequentially updated using Monte Carlo sampling as the mobile beacon moves over the deployment area. Our method relieves much of the localization tasks from the less powerful sensor nodes themselves and relies on the more powerful beacon to perform the calculation. We discuss the Monte Carlo sampling steps in the context of the localization using a single beacon for various types of observations such as ranging, Angle of Arrival (AoA), connectivity and combinations of those. We also discuss the communication protocol that relays the observation data to the beacon and the localization result back to the sensors. We consider security issues in the localization process and the necessary steps to guard against the scenario in which a small number of sensors are compromised. Our simulation shows that our method is able to achieve less than 50% localization error and over 80% coverage with a very sparse network of degree less than 4 while achieving significantly better results if network connectivity increases.     

An optimised resource aware approach to information collection in ad hoc networks

In ad hoc networks there is a need for all-to-one protocols that allow for information collection or “sensing” of the state of an ad hoc network and the nodes that comprise it. Such protocols may be used for service discovery, auto-configuration, network management, topology discovery or reliable flooding. There is a parallel between this type of sensing in ad hoc networks and that of sensor networks. However, ad hoc networks and sensor networks differ in their application, construction, characteristics and constraints. The main priority of sensor networks is for the flow of data from sensors back to a sink, but in an ad hoc network this may be of secondary importance. Hence, protocols suitable to sensor networks are not necessarily suitable to ad hoc networks and vice versa. We propose, Resource Aware Information Collection (RAIC), a distributed two phased resource aware approach to information collection in ad hoc networks. RAIC utilises a resource aware optimised flooding mechanism to both disseminate requests and initialise a backbone of resource suitable nodes responsible for relaying replies back to the node collecting information. RAIC in the process of collecting information from all nodes in an ad hoc network is shown to consume less energy and introduce less overhead compared with Directed Diffusion and a brute force approach. Importantly, over multiple successive queries (in an energy constrained environment), the use of resource awareness allows for the load of relaying to be distributed to those nodes most suitable, thereby extending the lifetime of the network.     

Neural-based approach for localization of sensors in indoor environment

Location of wireless sensor nodes is an important piece of information for many applications. There are many algorithms present in literature based on Received Signal Strength (RSSI) to estimate the location. However the radio signal propagation is easily influenced by diffraction, reflection and scattering. Therefore algorithms purely based on RSSI may not accurately predict the position of the node. In the present work, an algorithm for estimating the position of mobile nodes is proposed which is based on a combination of Received Signal Strength (RSSI) and Link Quality Indicator (LQI). Artificial Neural Networks are used to establish the relationship between the location of the mobile node and the experimentally obtained values of RSSI and LQI. Two different algorithms namely, Bayesian Regularization and Gradient Descent are used to develop the neural network model. Proposed algorithms improve the localization accuracy and perform better than other state-of-the-art algorithms.     

Nonparametric belief propagation for self-localization of sensor networks

Automatic self-localization is a critical need for the effective use of ad hoc sensor networks in military or civilian applications. In general, self-localization involves the combination of absolute location information (e.g., from a global positioning system) with relative calibration information (e.g., distance measurements between sensors) over regions of the network. Furthermore, it is generally desirable to distribute the computational burden across the network and minimize the amount of intersensor communication. We demonstrate that the information used for sensor localization is fundamentally local with regard to the network topology and use this observation to reformulate the problem within a graphical model framework. We then present and demonstrate the utility of nonparametric belief propagation (NBP), a recent generalization of particle filtering, for both estimating sensor locations and representing location uncertainties. NBP has the advantage that it is easily implemented in a distributed fashion, admits a wide variety of statistical models, and can represent multimodal uncertainty. Using simulations of small to moderately sized sensor networks, we show that NBP may be made robust to outlier measurement errors by a simple model augmentation, and that judicious message construction can result in better estimates. Furthermore, we provide an analysis of NBP's communications requirements, showing that typically only a few messages per sensor are required, and that even low bit-rate approximations of these messages can be used with little or no performance impact.     

The Effects of Physical Layer on the Routing Wireless Protocol

Mobile ad hoc networks (MANETs) are characterized by multiple entities, a frequently changing network topology and the need for efficient dynamic routing protocols. In MANETs, nodes are usually powered by batteries. Power control is tightly coupled with both the physical and medium access layers (MACs). However, if we increase the transmission power, at the same time we increase the interference to other nodes which diminish the transport capacity of wireless systems. Thus, the routing protocols based on hop count metric suffer from performance degradation when they operate over MANET. Routing in ad hoc wireless networks is not only a problem of finding a route with shortest length, but it is also a problem of finding a stable and good quality communication route in order to avoid any unnecessary packet loss. Cross-layer design of ad hoc wireless networks has been receiving increasing attention recently. Part of these researches suggests that routing should take into account physical layer characteristics. The goal of this paper is to improve the routing reliability in MANET and to reduce power consumption through cross-layer approach among physical, MAC and network layers. The proposed cross-layer approach is based on signal to interference plus noise ratio (SINR) and received signal strength indication (RSSI) coming from the physical layer. This solution performs in one hand the ad hoc on-demand distance vector routing protocol by choosing reliable routes with less interferences using SINR metric and in another hand; it permits to reduce the power transmission when sending the data packets by using RSSI metric.     

有限区域同时同频全双工跳频自组网性能研究

该文针对有限区域的同时同频全双工(CCFD)跳频自组网络,通信节点位置不等价,受非对称互干扰和自干扰影响的场景,开展有限区域全双工跳频自组网的通信性能分析。以网络频带利用率为性能指标,推导出节点位置分布条件下的网络频带利用率闭合表达式,并提出一种降低网络互干扰的节点位置优化分布方法。理论和仿真结果表明,有限区域全双工跳频自组网的性能与频点个数、通信距离、节点个数强相关,且全双工自组网络的性能与半双工网络相比,其占优区域受节点个数约束。     

DV Based Positioning in Ad Hoc Networks

Many ad hoc network protocols and applications assume the knowledge of geographic location of nodes. The absolute position of each networked node is an assumed fact by most sensor networks which can then present the sensed information on a geographical map. Finding position without the aid of GPS in each node of an ad hoc network is important in cases where GPS is either not accessible, or not practical to use due to power, form factor or line of sight conditions. Position would also enable routing in sufficiently isotropic large networks, without the use of large routing tables. We are proposing APS – a localized, distributed, hop by hop positioning algorithm, that works as an extension of both distance vector routing and GPS positioning in order to provide approximate position for all nodes in a network where only a limited fraction of nodes have self positioning capability.     

Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks

A maximum likelihood (ML) acoustic source location estimation method is presented for the application in a wireless ad hoc sensor network. This method uses acoustic signal energy measurements taken at individual sensors of an ad hoc wireless sensor network to estimate the locations of multiple acoustic sources. Compared to the existing acoustic energy based source localization methods, this proposed ML method delivers more accurate results and offers the enhanced capability of multiple source localization. A multiresolution search algorithm and an expectation-maximization (EM) like iterative algorithm are proposed to expedite the computation of source locations. The Crame/spl acute/r-Rao Bound (CRB) of the ML source location estimate has been derived. The CRB is used to analyze the impacts of sensor placement to the accuracy of location estimates for single target scenario. Extensive simulations have been conducted. It is observed that the proposed ML method consistently outperforms existing acoustic energy based source localization methods. An example applying this method to track military vehicles using real world experiment data also demonstrates the performance advantage of this proposed method over a previously proposed acoustic energy source localization method.     

An analysis of error inducing parameters in multihop sensor node localization

Ad hoc localization of wireless sensor nodes is a fundamental problem in wireless sensor networks. Despite the recent proposals for the development of ad hoc localization algorithms, the fundamental behavior in systems using measurements has not been characterized. In this paper, we take a first step toward such a characterization by examining the behavior of error inducing parameters in multihop localization systems in an algorithm independent manner. We first derive the Crame Rao Bound for Gaussian measurement error for multihop localization systems using distance and angular measurements. Later on, we use these bounds on a carefully controlled set of scenarios to study the trends in the error induced by the measurement technology accuracy, network density, beacon node concentration, and beacon uncertainty. By exposing these trends, the goal of this paper is to develop a fundamental understanding of the error behavior that can provide a set of guidelines to be considered during the design and deployment of multihop localization systems.     

Optimal trajectory determination of a single moving beacon for efficient localization in a mobile ad-hoc network

An ad hoc network of small robots (sensor nodes) adjusting their positions to establish network connectivity would be able to provide a communication infrastructure in an urban battlefield environment. A sensor node would be capable of moving to a particular position to establish network connectivity, provided it knows its current position, positions of other sensor nodes and the radio propagation characteristics of the sensor area.In this paper, we present a pseudo formation control based trajectory algorithm to determine the optimal trajectory of a moving beacon used in localization of the sensor nodes in real-time. The trajectory and the frequency of transmission of the GPS based position information of the moving beacon influences the accuracy of localization and the power consumed by the beacon to localize. Localization accuracy and reduction in the number of position information messages can be achieved, in real-time, by determining the optimal position from where the beacon should transmit its next position information. This will decrease the time required to localize, and power consumed by the beacon in comparison to random or predetermined trajectories.We first show that optimal position determination is a pseudo formation control problem. Next, we show the pseudo formation control problem formulated as an unconstrained optimization problem under the free space propagation model. We further present the modeling of the beacon incorporating the trajectory algorithm based on the pseudo formation control in a discrete event simulator. Simulation results, comparing the performance of localization with pseudo formation control based trajectory against random waypoint and predetermined trajectories for the beacon are presented. The simulation results show that the localization accuracy is significantly improved along with reduction in the number of position information messages transmitted when the beacon traverses along the pseudo formation control based trajectory.     

Collaborative beamforming for distributed wireless ad hoc sensor networks

The performance of collaborative beamforming is analyzed using the theory of random arrays. The statistical average and distribution of the beampattern of randomly generated phased arrays is derived in the framework of wireless ad hoc sensor networks. Each sensor node is assumed to have a single isotropic antenna and nodes in the cluster collaboratively transmit the signal such that the signal in the target direction is coherently added in the far-field region. It is shown that with N sensor nodes uniformly distributed over a disk, the directivity can approach N, provided that the nodes are located sparsely enough. The distribution of the maximum sidelobe peak is also studied. With the application to ad hoc networks in mind, two scenarios (closed-loop and open-loop) are considered. Associated with these scenarios, the effects of phase jitter and location estimation errors on the average beampattern are also analyzed.     

Efficient flooding with passive clustering-an overhead-free selective forward mechanism for ad hoc/sensor networks

High capacity real-time data communications in sensor networks usually require multihop routing and ad hoc routing protocols. Unfortunately, ad hoc routing protocols usually do not scale well and cannot handle dense situations efficiently. These two issues-scalability and density-are the major limitations when we apply ad hoc routing schemes to sensor networks. Passive clustering (PC) classifies ad hoc/sensor nodes into critical and noncritical nodes without any extra transmission. By 2-b piggybacking and monitoring user traffic (e.g., data polling requests from a sink), PC deploys the clustering structure "for free". Moreover, PC makes even the first flooding as efficient as all subsequent floodings (i.e., no initialization overhead). PC introduces many benefits, including efficient flooding and density adaptation. As a result, PC reduces control overhead of ad hoc routing protocols significantly and, as a consequence, enables ad hoc routing in large, dense sensor networks. The resulting structure can be utilized in cluster-based ad hoc network/sensor networking as well as for active node selection.     

Energy efficient multi-channel media access control for dense wireless ad hoc and sensor networks

Traditional single-channel MAC protocols for wireless ad hoc and sensor networks favor energy-efficiency over throughput. More recent multi-channel MAC protocols display higher throughput but less energy efficiency. In this article we propose NAMAC, a negotiator-based multi-channel MAC protocol in which specially designated nodes called negotiators maintain the sleeping and communication schedules of nodes within their communication ranges in static wireless ad hoc and sensor networks. Negotiators facilitate the assignation of channels and coordination of communications windows, thus allowing individual nodes to sleep and save energy. We formally define the problem of finding the optimal set of negotiators (i.e., minimizing the number of selected negotiators while maximizing the coverage of the negotiators) and prove that the problem is NP-Complete. Accordingly, we propose a greedy negotiator-election algorithm as part of NAMAC. In addition, we prove the correctness of NAMAC through a rigorous model checking and analyze various characteristics of NAMAC—the throughput of NAMAC, impact of negotiators on network capacity, and storage and computational overhead. Simulation results show that NAMAC, at high network loads, consumes 36 % less energy while providing 25 % more throughput than comparable state-of-art multi-channel MAC protocols for ad hoc networks. Additionally, we propose a lightweight version of NAMAC and show that it outperforms (55 % higher throughput with 36 % less energy) state-of-art MAC protocols for wireless sensor networks.     

Position and orientation in ad hoc networks

Position and orientation information of individual nodes in ad hoc networks is useful for both service and application implementation. Services that can be enabled by availability of position include routing and querying. At application level, position is required in order to label the reported data in a sensor network, whereas position and orientation enable tracking.Nodes in an ad hoc network may have local capabilities such as the possibility of measuring ranges to neighbors, angle of arrival (AOA), or global capabilities, such as GPS and digital compasses. This article investigates the possibility of using local capabilities to export global capabilities using a distributed, localized, hop by hop method. We show how position and orientation of all the nodes in a connected ad hoc network can be determined with a small fraction of landmarks that can position/orient themselves, given that all nodes have some combination of local capabilities.     

Detecting unauthorized and compromised nodes in mobile ad hoc networks

Security of mobile ad hoc networks (MANET) has become a more sophisticated problem than security in other networks, due to the open nature and the lack of infrastructure of such networks. In this paper, the security challenges in intrusion detection and authentication are identified and the different types of attacks are discussed. We propose a two-phase detection procedure of nodes that are not authorized for specific services and nodes that have been compromised during their operation in MANET. The detection framework is enabled with the main operations of ad hoc networking, which are found at the link and network layers. The proposed framework is based on zero knowledge techniques, which are presented through proofs.     

TrANTHOCNET:信任性蚁群自组织路由算法

 移动自组网依靠多点协作完成路由任务,可信的路由协议需要节点之间建立一定的信任关系,但大多数信任路由模型只追求路由的信任性而忽略了健壮性.本文基于ANTHOCNET算法,设计了兼顾信任性和健壮性的TrANTHOCNET算法.引入模糊Petri网的形式化推理算法处理节点之间的不确定关系,并利用位置信息对信息素实时更新以提高路由健壮性.实验结果表明TrANTHOCNET较ANTHOCNET、AODV和T-AODV均表现出较强的抵抗恶意节点攻击的能力,在路由性能方面也验证了本算法的有效性.     

Unidirectional link-state advertisement based on power control for MANET

Link states are studied in ad hoc network. The characters of unidirectional links are discussed. Unidirectional link-state advertisement based on power control mechanism (ULAPC) for mobile ad hoc networks (MANET) is designed. ULAPC is able to advertise unidirectional link-state to relational nodes. And it may offer help for process of routing discovery in ad hoc network. Based on ULAPC, the routing method solving the problem of unidirectional link is described in ad hoc network. Simulation results show the performance of ULAPC is better than the traditional routing protocols in many aspects.