Asynchronous Resilient Wireless Sensor Network for Train Integrity Monitoring

Wireless sensor networks (WSNs) are an essential technology for the Internet of Things (IoT) and Machine-to-Machine (M2M), and node locations on them are indispensable for IoT and M2M applications. Therefore, we proposed a Cloud-based Self-Organizing localization (Cloud-SOL), which is composed of a WSN and a cloud computing environment with which the WSN connects. The Cloud-SOL aggregates the WSN's neighbor node list to the cloud computing environment and can estimate precise node locations using the WSN's aggregated topology information. However, it requires multi-hop topology with a high hop count for the WSNs. In this paper, we propose a virtual network topology for Cloud-SOL and show its implementation. The virtual network topology dynamically and ideally configures the WNS topology in cloud computing environment to the Clod-SOL without dependence on actual WSN topology.

In this paper, the reliability of data transmission in social networks is thoroughly studied and analyzed using wireless sensor network topology technology. This paper, based on the introduction of sensor network reliability analysis-related technology, combined with the characteristics, and needs of the sensor network itself, focuses on the study of the reliability analysis of the sensor network under the state of perturbation scheme. Based on the idea of making full use of data changes to respond to the sensor state, this paper takes the actual monitoring data of the wireless sensor network as the research object, selects the temporal correlation and spatial correlation of the measured environmental data as the reliability index by extracting the features of the wireless sensor network data, and proposes the Evidential reasoning rule- (ER-) based wireless sensor network data reliability assessment model based on Evidential reasoning rule (ER) is proposed. The data are mined, analyzed, and quantified from the perspective of content popularity, and the interest indicators of nodes on data under content popularity are analyzed to derive stable interest quantification values. Combined with the network properties, i.e., node autoassembly community, we analyze the data dissemination characteristics of social networks in wireless sensor network topology environment and derive the upper and lower bounds of data transmission capacity under node interest-driven and its variation on network performance. Social relationships among nodes affected by social attributes are considered; in turn, the data forwarding behavior of nodes is modeled using data transmission probability and data reception probability; finally, the data forwarding process is analyzed and a closed expression for the average end-to-end transmission capacity is derived in turn.

The focus of this paper is to use Cellular Automata for simulating a series of topology control algorithms in Wireless Sensor Network using various environments. In this paper, we introduced the use of cellular automata in Wireless sensor networks to control Topology. In the network the sensor nodes are redundantly deployed in the same field. Due to this redundant deployment the many nodes in the network have remained in their active state simultaneously. This causes reduction in the global energy of the network and step-up in the lifetime of the mesh. Thus, the principal aim of the topology control algorithms is to cut the initial topology of wireless sensor network by avoiding noise and hold out the life of the mesh.KeywordsCellular AutomataLarge scale wireless sensor networkLifetimedistributed computing

Wireless sensor networks (WSNs) consist of a large number of small devices or nodes, called micro controller units (MCUs) and located in homes and/or offices, to be operated through the internet from anywhere, making these devices smarter and more efficient. Quality of service routing is one of the critical challenges in WSNs, especially in surveillance systems. To improve the efficiency of the network, in this article we proposes a distributed learning fractal algorithm (DFLA) to design the control topology of a wireless sensor network (WSN), whose nodes are the MCUs distributed in a physical space and which are connected to share parameters of the sensors such as concentrations of , humidity, temperature within the space or adjustment of the intensity of light inside and outside the home or office. For this, we start defining the production rules of the L-systems to generate the Hilbert fractal, since these rules facilitate the generation of this fractal, which is a fill-space curve. Then, we model the optimization of a centralized control topology of WSNs and proposed a DFLA to find the best two nodes where a device can find the highly reliable link between these nodes. Thus, we propose a software defined network (SDN) with strong mobility since it can be reconfigured depending on the amount of nodes, also we employ a target coverage because distributed learning fractal algorithm (DLFA) only consider reliable links among devices. Finally, through laboratory tests and computer simulations, we demonstrate the effectiveness of our approach by means of a fractal routing in WSNs, by using a large amount of WSNs devices (from 16 to 64 sensors) for real time monitoring of different parameters, in order to make efficient WSNs and its application in a forthcoming Smart City.

Aimed at the current status of PV solar monitoring system as well as the PV solar monitoring network requirements, and application of Wireless Sensor Networks(WSN) to PV solar monitoring system is proposed. The Wireless Sensor Networks structure of PV solar monitoring system based on ZigBee and GPRS and topology of ZigBee Wireless Sensor Networks for PV solar monitoring were presented. Experiments show that the system meets the demand for PV monitoring system in terms of data acquisition and transmission, and has some advantages at installation and networking, it's the ideal solution of PV monitoring system.

The hierarchical topology of wireless sensor networks can effectively reduce the consumption in communication. Clustering algorithm is the foundation to realize herarchical structure, so it has been extensive researched. On the basis of Leach algorithm, a distance density based clustering algorithm (DDBC) is proposed, considering synthetically the distribution density of around nodes and the remaining energy factors of the node to dynamically banlance energy usage of nodes when selecting cluster heads. We analyzed the performance of DDBC through compared with the existing other clustering algorithms in simulation experiment. Results show that the proposed method can generare stable quantity cluster heads and banlance the energy load effectively.

With 17.5% of world population, food safety and security is of primary concern in India. Despite increase in food grain production in last decade, there is heavy loss of food grains during transit and storage. This is due to lack of adequate infrastructures and technologies to monitor adverse environmental conditions that result in storage losses. In this paper, we propose a topology for wireless sensor networks called two-tailed chain topology that is suitable for efficiently monitoring of environmental factors in food grain depots. The proposed topology is designed by considering all infrastructure constraints of a food grain depot. Results show that the proposed topology is better than traditional topologies in terms of detection accuracy and coverage.

Power-Law topology has been proved to be an effective technique to improve fault tolerance. With the motivation of construct reliable topology for wireless sensor networks, a Power-Law Evolving Model (PLEW) of wireless sensor networks by stochastic placement is proposed in this article. In a dynamic evolving process of Wireless Sensor Networks, there are four types of events as follows: adding new nodes, nodes failure, adding new links, and links failure. The dynamics of nodes and links are integrated into the evolving model consequently. By using the continuum theory, the theoretical computing and simulated results show that the degree distribution of this model follows a power law. The scale-free properties revealed in this model can be applied into the scenarios required high dependability, such as national defense or survivability systems.

Directional antennas in wireless sensor networks (WSNs) have several advantages including the enhanced capacity of the network, longer range of transmission, better spatial reuse and lower interference. By enhancing the alleviating contention and the range of communication, the directional antennas improve the performance of WSNs. In common, various methods like localisation, power management, data aggregation and optimisation obtain these advantages in WSNs; however, the reliability requirements and the energy concerns make the antenna technology more advantageous. When compared with methods, in which the directional antennas provide advantages like the extended range of transmission, energy savings, better prevention of wormhole attack, long coverage and high interference tolerance. This review provides a detailed study of recent improvements and open research problems on directional antennas in WSN applications. First, the introduction and the background of directional antennas briefly based on their classification radiation patterns and advantages in directional communication in WSNs. During the past years, a number of directional antennas are designed for the applications of WSNs. In this study, recently developed directional antennas and their applications in WSNs are reviewed. The applications of directional antenna in WSNs are classified into security benefits, localisation, convergecast, contention reduction and energy efficiency.

The topology of wireless sensor networks (WSNs) can be controlled through changing the transmission power of each node. We propose an adaptive energy efficient topology (AEET) algorithm where each node adaptively adjusts its transmission radius by local decisions about its residual power and optimal transmission radius. We give detailed AEET and analyses the communication radius in an ideal linear model and two cases of the adaptive topology control. The AEET mechanism and the topology control procedure are also given. AEET guarantees a suitable connected node set through interaction. The resulting network topology increases WSNs lifetime by adaptively adjusting transmission power. Through simulating AEET, the result proves AEET scheme is able to prolong lifetime.

In this paper, we use complex network theory to analyze the evolving topology of wireless sensor networks (WSNs). Based on the BA model, we propose a novel complex network model, i.e., Neighborhood Log-on and Log-off model with energy awareness (NLL-E). NLL-E assumes locally preferential attachment, which exists in many complex networks. We further consider node addition and invalidation in topology evolvement, and add compensation mechanism for network robustness. The statistical properties and dynamics of NLL-E are analytically studied. Numerical simulations indicate that, comparing with BA, NLL-E has decreased average path length and increased network connectivity.

Balance energy-efficient and real-time with reliable communication protocol for wireless sensor network

Wireless industrial sensor networks are wireless sensor networks which have been adapted to industrial applications. Most techniques for wireless sensor networks can be applied to wireless industrial sensor networks. However, for industrial applications of wireless industrial sensor networks, new requirements such as real-time, reliable delivery need to be considered. In this paper, we propose EARQ, which is a novel routing protocol for wireless industrial sensor networks. It provides real-time, reliable delivery of a packet, while considering energy awareness. In EARQ, a node estimates the energy cost, delay and reliability of a path to the sink node, based only on information from neighboring nodes. Then, it calculates the probability of selecting a path, using the estimates. When packet forwarding is required, it randomly selects the next node. A path with lower energy cost is likely to be selected, because the probability is inversely proportional to the energy cost to the sink node. To achieve real-time delivery, only paths that may deliver a packet in time are selected. To achieve reliability, it may send a redundant packet via an alternate path, but only if it is a source of a packet. Experimental results show that EARQ is suitable for industrial applications, due to its capability for energy efficient, real-time, reliable communications.

Slowing of alpha rhythm in thinner sniffers : H. Miyake, S. Iijima and Y. Hishikawa (Yokosuka and Osaka, Japan)

In many applications of wireless sensor networks (WSNs), sensors are deployed in hostile environments where an adversary can eavesdrop communications. To secure communications in WSNs, the q-composite key predistribution scheme has been widely recognized as a suitable approach. In this paper, we investigate connectivity in secure WSNs operating under the q-composite scheme, in consideration of different link constraints: the unreliability of wireless links and the requirement that two sensors have to be within certain distance to have a link. We formally derive conditions on how to scale the model parameters so that the network is securely connected with high probability when the number of sensors becomes large. The results are given in the form of zero-one laws and provide useful guidelines for designing securely and reliably connected sensor networks.