Three-Dimensional Localization Algorithm Based on LIE

A centralized three dimensional localization algorithm is proposed with the name of NMDS-MEEF, which is based on the location requirements of wireless sensor network used for monitoring large electrical equipment fault. The localization algorithm adopts a changed nonmetric multidimensional scaling in which the iterations process only makes use of the correlated data of one-hop neighbor nodes. The algorithm is more straightforward and practical. The simulation results demonstrate that the algorithm is of great advantages in improving localization accuracy, decreasing the dependence on the density of anchor nodes and reducing the influence by the accuracy of position estimation.

Large-scale distribution, communication and processing of sensed information require the operation of a highly-dynamic, dense, and widely-distributed wireless sensor network. Existing centralized and decentralized solutions require the use of information that may not be readily available to the nodes in a timely fashion. Instead of seeking such techniques, in this paper we propose an evolutionary price-based routing and bandwidth allocation algorithm for the management of information in large-scale distributed wireless sensor networks that will be (1) adaptable and responsive to demands and seek delivery of information to desired nodes despite the fact that the source and destination are not globally known, (2) efficient in allocating bandwidth, and (3) decentralized.

As localization represents the main core of various wireless sensor network applications, several localization algorithms have been suggested in wireless sensor network research. In this article, we put forward an iterative bounding box algorithm enhanced by a Kalman filter to refine the unknown node’s estimated position. In fact, several research efforts are currently in progress to extend the 2D positioning algorithm in WSNs to 3D that reflects reality and the most practical applications. Subsequently, we replace a large number of GPS-equipped anchors with a single mobile anchor. In our studies, we consider the type of range-free sensor network exploiting the wireless sensors connectivity. We assess the performance of our algorithm using exhaustive experiments on several isotropic and anisotropic topologies. Our proposed algorithm can fulfill the joint goals of algorithm transparency and accuracy for various scenarios by evaluating parameters such as localization accuracy whilst changing other simulation parameters such as the effect of communication range, mobile anchor node position and sensor node deployment topology. It has been proven by the results of the experiments that the proposed algorithm effectively reduces the location error without requiring more equipment or increasing the communication cost.

Various communication services have been provided. They include environmental monitoring and/or control, ad-hoc communication between mobile nodes, and inter-vehicle communication in intelligent transport systems. As a means of facilitating the above advanced communication services, autonomous decentralized networks, such as wireless sensor networks (Akyildiz et al., 2002; Rajagopalan & Varshney, 2006), mobile ad-hoc networks (Perkins & Royer, 1999; Johnson et al., 2003; Clausen & Jaquet, 2003; Ogier et al., 2003), and wireless mesh networks (Yamamoto et al., 2009), have been intensively researched with great interests. Especially, a wireless sensor network, which is a key network to construct ubiquitous information environments, has great potential as a means of realizing a wide range of applications, such as natural environmental monitoring, environmental control in residential spaces or plants, object tracking, and precision agriculture (Akyildiz et al., 2002). Recently, there is growing expectation for a new network service by a wireless sensor network consisting of a lot of static sensor nodes arranged in a service area and a few mobile robots as a result of the strong desire for the development of advanced systems that can flexibly function in dynamically changing environments (Matsumoto et al., 2009). In this chapter, a large scale and dense wireless sensor network made up of many static sensor nodes with global positioning system, which is a representative network to actualize the above-mentioned sensor applications, is assumed. In a large scale and dense wireless sensor network, generally, hundreds or thousands of static sensor nodes limited resources, which are compact and inexpensive, are placed in a service area, and sensing data of each node is gathered to a sink node by inter-node wireless multi-hop communication. Each sensor node consists of a sensing function to measure the status (temperature, humidity, motion, etc.) of an observation point or object, a limited function of information processing, and a simplified wireless communication function, and it generally operates on a resource with a limited power-supply capacity such as a battery. Therefore, a data gathering scheme and/or a routing protocol capable of meeting the following requirements is mainly needed to prolong the lifetime of a large scale and dense wireless sensor network composed of hundreds or thousands of static sensor nodes limited resources. 1. Efficiency of data gathering 2. Balance of communication load among sensor nodes 3. Adaptability to network topology changes

QoSNET: An integrated QoS network for routing protocols in large scale wireless sensor networks

Wireless sensor network(WSN) authentication schemes are the basic necessary security tool for protecting the communication authenticity and integrity in the network. In this paper we propose general authentication schemes from linear error-correcting codes and rational functions. There are very many different random code and function based authentication schemes with the same security functionality and cost. When these different and random code and function based authentication schemes are used for various parts of one large scale wireless sensor network, the resulted WSN authentication schemes constructed in this paper can resist the compromising of large number of sensor nodes for this large scale wireless sensor network with moderate communication and storage cost. The verification per node in our novel WSN authentication schemes is very fast. Thus WSN authentication schemes based on codes and rational functions can be used to resist the pollution and DoS attacks from the adversary.

A scalable approach for serial data fusion in Wireless Sensor Networks

Sensor node localization is a crucial aspect of many location-related applications that utilize wireless sensor networks. Among the many studies in the literature, multidimensional scaling-based localization techniques have been proven to be efficient, obtaining high accuracy with lower information requirements. However, when applied to large-scale wireless sensor networks with coverage holes, which are common in many scenarios, such as underground mines, the transmission path can become deviated, degrading the localization performance of this type of connectivity-based technique. Furthermore, in such complex wireless environments, non-line-of-sight reference objects, the presence of obstacles and signal fluctuations change the communication range and make it difficult to obtain an accurate position. In this article, we present a anchor-free localization scheme for large-scale wireless sensor networks called the ranging and multidimensional scaling–based localization scheme. We use ranging and non-line-of-sight error mitigation techniques to estimate accurate distances between each node pair and attempt to find inflection nodes using a novel flooding protocol to correct transmission paths that have become deviated by a coverage hole. Moreover, we replace the singular value decomposition with an iterative maximum gradient descent method to reduce the computational complexity. The results of the simulations and experiments show that our scheme performs well on wireless sensor networks with different coverage holes and is robust to varying network densities.

To solve the problems of high memory occupation, low connectivity and poor resiliency against node capture, which existing in the random key pre-distribution techniques while applying to the large scale Wireless Sensor Networks (WSNs), an Identity-Based Key Agreement Scheme (IBKAS) is proposed based on identity-based encryption and Elliptic Curve Diffie-Hellman (ECDH). IBKAS can resist man-in-the-middle attacks and node-capture attacks through encrypting the key agreement parameters using identity-based encryption. Theoretical analysis indicates that comparing to the random key pre-distribution techniques, IBKAS achieves significant improvement in key connectivity, communication overhead, memory occupation, and security strength, and also enables efficient secure rekeying and network expansion. Furthermore, we implement IBKAS for TinyOS-2.1.2 based on the MICA2 motes, and the experiment results demonstrate that IBKAS is feasible for infrequent key distribution and rekeying for large scale sensor networks.

The paper presents an innovative design for wireless sensor networks (WSNs) which can increase their performances in the precision agriculture (PA). The authors argue on the reasons why presently WSNs are not integrated in PA on a larger scale. To this end, the paper describes the state of art in WSNs used in PA, and develops the proposed solution on the basis of the identified conjectures. The conceived solution proves how nodes can have small dimensions without mitigating the communication range or energy autonomy. Small dimensions bring benefits also to costs and operations. Such results can be achieved by overcoming the misalignment between advances in unmanned agricultural vehicles (AVs) and advances in WSN. The fixed nodes and mobile nodes (AVs), cooperate to fulfil sensor and communication coverage. Endowing the WSN nodes only with necessary sensors together with an energy awareness communication algorithm adopted in resonance with PA requirements proves to be a new competitive approach. Some simulations to validate these concepts are also provided.

In this paper, we consider the multiple sinks placement problem in energy constrained large-scale Wireless Sensor Networks (WSN). First, some fundamental design parameters in WSNs are investigated such as nodes deployment, the network architecture, sink velocity and transmission range. Each of these parameters is analysed and discussed according to its influence on the energy consumption in a WSN. Second, a simple and efficient approach for the placement of multiple sinks within large-scale WSNs is proposed. The objective is to determine optimal sinks’ positions that maximize the network lifetime by reducing energy consumption related to data transmissions from sensor nodes to different sinks. Balanced graph partitioning techniques are used to split the entire WSN into connected sub-networks. Smaller sub-networks are created, having similar characteristics and where energy consumption can be optimized independently but in the same way. Therefore, different approaches and mechanisms that enhance the network lifetime in small-size WSN can be deployed inside each sub-network. Performance results show that the proposed technique significantly enhances the network lifetime.KeywordsLarge-Scale Wireless Sensor Networksmultiple sinksdesign parametersenergy efficiencygraph partitioning

Identifying locations of sensor nodes in wireless sensor networks (WSNs) is significant for both network operations and most application level tasks. Although, geographical positioning system (GPS) based localization schemes are used for determining node locations but the cost of GPS devices and non-availability of GPS signals in indoor environments prevent their use in large scale WSNs. A substantial amount of research work exist that intend at obtaining precise and relative spatial locations of sensor nodes without requiring large amount of specialized hardware. Mobile anchor assisted localization is one typical approach that significantly reduces the implementation cost by using limited number of mobile anchors. In this survey, we present key issues and inherent challenges faced by the mobile anchor assisted localization techniques in WSNs. We take a closer look at the algorithmic approaches of various important fine-grained mobile anchor assisted localization techniques applicable in WSNs. In addition, we highlight the error refinement mechanisms adopted by the state-of-the-art works associated with their approaches. Well known mobile anchor trajectories presented in existing works are also reviewed. Finally, open research issues are discussed for future research scope in this field.

A survey on mobility-assisted localization techniques in wireless sensor networks

Wireless sensor networks (WSNs) are quickly becoming an essential part of today's modern infrastructure, and it is becoming crucial to consider time synchronisation problems in WSNs. Furthermore, one of the main design issues in WSN time synchronisation is the efficient use of energy at each sensor node to prolong the lifespan of the network. This paper describes a new energy-efficient time protocol based on the spanning tree of the network model graph in a WSN. Three major cases are discussed: 1) time synchronisation using the energy-efficient spanning tree (EST) protocol in a WSN with approximately 300 sensors; 2) an improved EST protocol in large-scale WSNs; 3) an improved EST protocol under weighted graph. Additionally, a series of practical algorithms are proposed in this paper, where both energy and time efficient can be clearly shown through a number of simulated examples along with their comparative results.

Data acquisition from multi-hop large-scale outdoor wireless sensor network (WSN) deployments for environmental monitoring is full of challenges. This is because of the severe resource constraints on tiny battery-operated motes (e.g., bandwidth, memory, power, and computing capacity), the data acquisition volume from large-scale WSNs, and the highly dynamic wireless link conditions in outdoor harsh communication environments. We present a novel compressed sensing approach, which can recover the sensing data at the sink with high fidelity when a very few data packets need to be collected, leading to a significant reduction of the network transmissions and thus an extension of the WSN lifetime. Interplaying with the dynamic WSN routing topology, the proposed approach is both efficient and simple to implement on the resource-constrained motes without motes’ storing of any part of the random projection matrix, as opposed to other existing compressed sensing-based schemes. We further propose a systematic method via machine learning to find a suitable representation basis, for any given WSN deployment and data field, which is both sparse and incoherent with the random projection matrix in compressed sensing for data collection. We validate our approach and evaluate its performance using a real-world outdoor multi-hop WSN testbed deployment in situ . The results demonstrate that our approach significantly outperforms existing compressed sensing approaches by reducing data recovery errors by an order of magnitude for the entire WSN observation field while drastically reducing wireless communication costs at the same time.