Model Design of Wireless Sensor Network Based on Scale-Free Network Theory

Wireless Sensor Network (WSN) technology has the potential to have impact on many aspects of Precision Agriculture (PA). However, current WSN applications in Precision Agriculture all adopt the traditional client/sever model, data are sent from the source to the destination, because of hugeous data, high concurrency and strong signal interference in Precision Agriculture and the extremely limited sensor network resources, such client/sever model hampers WSN applications in Precision Agriculture.[ This paper presents a mobile-based agent of wireless sensor network model MAPA, MAPA avoids the large agricultural intermediate data transmission through migrating the computing to the resource source, and consequently it prolongs the sensor network lifetime and promotes the WSN applications in Precision Agriculture.

Research in wireless sensor networks is ongoing at a large scale for applications deployable world-wide like forest monitoring etc. To design, deploy and evaluate novel wireless systems, large and critical application requires a substantial effort. One of the major applications of wireless sensor networks is in event detection. The main objective of this paper is to monitor the forest tree theft and alert using wireless sensor networks. In forest monitoring application, event occurrence is rare, so the communication node is kept in at sleep mode. Whenever an event occurrence has been detected by sensor, it triggers the communication node. Subsequently, the event is reported to the sink node as quickly as possible and an alert is generated. In addition to this, the second objective of this work is power harvesting and power managing that has been achieved using event detection technique.

Wireless sensor networks (WSNs) consist of a large number of small, low data rate and inexpensive nodes that communicate in order to sense or control a physical phenomenon. The major difference between the WSN and the traditional wireless network is that sensors are very sensitive to energy consumption. Moreover, the performance of the sensor network applications highly depends on the lifetime of the network and we expect the lifetime of several months to several years. Thus, energy saving is crucial in designing long-lived wireless sensor networks. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous driven networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations .

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.

This paper combines the research of wireless sensor networks and sports training and proposes a wireless sensor network‐based intelligent sports training system. According to the requirements of the system, this design uses the wireless sensor network system as the platform for development and the ZigBee module for wireless communication. The advantage of this system is to transmit the obtained information to the ZigBee coordinator module, and after the processing of information and the resultant decision, a nonwearable unmonitored motion training model based on visual sensing is proposed. The motion terminal collects video data streams of user motion actions and extracts features to establish HMM motion recognition algorithm to achieve recognition of motion actions, automatic counting, and intelligent scoring functions. The template matching algorithm based on dynamic time regularization and weighted Euclidean distance realizes a universal real‐time motion recognition algorithm with high standard and low latency and can guide the user’s motion action based on similarity calculation. The intelligent sports training system is designed and developed to maintain a high‐quality human‐computer interaction experience with a real‐time feedback client and uploads sports data to a cloud server via the HTTP protocol, which supports real‐time sports proximity query and training plan development on the website. After practical application tests, the intelligent sports training system based on the wireless sensor network proposed in this paper is stable and reliable and adds fun and competitiveness to boring sports. The research of this paper has some reference value for the application of wireless sensor networks and the research of the motion recognition algorithm.

Complex social network analysis methods have been applied extensively in various domains including online social media, biological complex networks, etc. Complex social networks are facing the challenge of information overload. The demands for efficient complex network analysis methods have been rising in recent years, particularly the extensive use of online social applications, such as Flickr, Facebook and LinkedIn. This paper aims to simplify the network complexity through partitioning a large complex network into a set of less complex networks. Existing social network analysis methods are mainly based on complex network theory and data mining techniques. These methods are facing the challenges while dealing with extreme large social network data sets. Particularly, the difficulties of maintaining the statistical characteristics of partitioned sub-networks have been increasing dramatically. The proposed Normal Distribution (ND) based method can balance the distribution of the partitioned sub-networks according to the original complex network. Therefore, each subnetwork can have its degree distribution similar to that of the original network. This can be very beneficial for analyzing sub-divided networks and potentially reducing the complexity in dynamic online social environment.

Wireless sensor networks (WSNs) are emerging rapidly as a new generation of sensor networks. Despite intensive research in wireless sensor networks (WSNs), limited work has been found in the open literature in the field of WSNs. In particular, quality-of-service (QoS) management in WSNs remains an important issue yet to be investigated. As an attempt in this direction, this paper develops a logic for QoS management (LFQMS) scheme for WSNs with constrained resources and in dynamic and unpredictable environments. Taking advantage of the feedback control technology, this scheme deals with the impact of unpredictable changes in traffic load on the QoS of WSNs. It utilizes a logic controller inside each source sensor node to adapt sampling period to the deadline miss ratio associated with data transmission from the sensor to the sensor. The deadline miss ratio is maintained at a pre-determined desired level so that the required QoS can be achieved. The (LFQMS) has the advantages of generality, scalability, and simplicity. Simulation results show that the (LFQMS) can provide WSNs with QoS support.

As an information acquisition and processing method, wireless sensor network is also an important component of the Internet of Things. As a key core technology of wireless sensor networks, localization technology has become an important direction in the current and future research of wireless sensor networks, which is also a key issue related to the real application of wireless sensor networks and the Internet of Things. The research of localization algorithm based on intelligent computing technology is paid more attention. In this paper, a novel intelligent computing method — grey wolf optimization was used to localization in wireless sensor network and proposed a novel localization algorithm. The validity and practicability of the proposed algorithm were verified by simulation experiments. The convergence performance and localization result was discussed and compared by the classical traditional intelligent computing methods—particle swarm optimization algorithm. Moreover, the localization performance under different anchor node proportion and different communication radius were analyzesed in this paper. The simulation results show that the proposed algorithm has higher localization accuracy, and it needs fewer anchor nodes and smaller communication radius to achieve the same accuracy, thus saving cost.

We present a case study that considers the application of runtime verification technology to a wireless sensor application. The case study is performed using the SURGE TinyOS application for multi-hop routing, which executes on the Avrora TinyOS simulator. We discuss the problems we have encountered in the course of case study. The problems include unclear correctness properties for wireless network applications (indicating ad hoc development process) and inadequate tool support. A wireless sensor network usually comprises of a collection of tiny devices with built-in processors that can gather physical and environment information such as temperature, light, sound, etc., and communicate with one another over radio. Many wireless sensor network applications sit on top of an operating system called TinyOS and are mostly written in nesC, an extension of C that provides a component-based programming paradigm. Most of wireless sensor network applications are developed and tested on a simulator before they are deployed in the environment because testing and debugging directly on physical devices are very difficult, especially when the network consists of many nodes, and may not provide enough information for debugging. A simulator usually produces detailed execution information and can help find errors. However, even with the simulator and nesC, the current state of development tools for wireless sensor network still requires very low-level programming, which makes it hard for the developers to maintain a high-level view of the system operation. During the validation stage, lack of sophisticated debugging tools for sensor networks makes it difficult to make the connection between a high-level functional or performance requirement and a particular aspect of system implementation. This paper investigates a high-level approach to examine execution data from a simulator and analyze it using runtime verification. The technique 1) identifies and formally specifies high-level requirements for the system under development, 2) monitors a distributed wireless sensor network application using data provided by the simulator, and 3) checks for timing and dynamic properties to gain understanding of the relevant behaviors of wireless sensor nodes and to provide a systematic approach in finding bugs and errors. A particular runtime verification used inthis paper is MaC. MaC provides specification languages capable of expressing functional, timing, and probabilistic properties to specify requirements or patterns of errors. Properties can, for example, examine periodic behaviors or identify a faulty node. MaC then monitors and checks a wireless sensor network application against its specification by observing data produced by a simulator. The motivation for applying the monitoring and checking technique to check wireless sensor network applications is threefold: 1) raise the development level for wireless sensor network, 2) provide a mechanism for understanding high-level behaviors of the system in terms of low-level observation, and 3) provide a tool based on the acceptance of the state of the art development tool for sensor networks.

Wireless sensor networks consist of a large number of low-cost, low-power, and multifunctional sensor nodes that communicate over short distances through wireless links. Such sensor networks are ideal candidates for a wide range of applications such as monitoring of critical infrastructures, data acquisition in hazardous environments, industry control systems, vehicular networks, and military operations. Wireless sensor networks introduce new security challenges due to their dynamic topology, severe resource constraints, and absence of a trusted infrastructure. The purpose of this special issue is to publish high-quality research papers as well as review articles addressing recent advances of wireless sensor network security. In this special issue, we will explore the topic of security challenges and solutions for the wide application of wireless sensor networks in different areas, such as RFID and smart grid. RFID has been widely used in logistics and internet of things. Smart grid leverages sensor networks to better balance the load of the power grid. Both of them have great impact on the daily life and areweak points of thewhole economy,which attract the attention of terrorists. The feasible attacks and defense solutions are still not clear.The papers in this volume also cover several important foundational security services for wireless sensor networks, such as key management, key distribution, secure cluster formation, secure architecture for multihop communication, intrusion prediction, and secure localization. All these foundational security services are critical bases for application of wireless sensor networks. We hope that the papers in this volume engender further thinking about new security challenges for wireless sensor networks and even further “out-of-the-box” ideas about how to solve new security problems for wireless sensor networks.

Monitoring and automatic control of building environment is a crucial application of Wireless Sensor Network (WSN) in which maximizing network lifetime is a key challenge. Previous research into the performance of a network in a building environment has been concerned with radio propagation within a single floor. We investigate the link quality distribution to obtain full coverage of signal strength in a four-storey building environment, experimentally. Our results indicate that the transitional region is of particular concern in wireless sensor network since it accommodates high variance unreliable links. The transitional region in a multi-storey building is mainly due to the presence of reinforced concrete slabs at each storey and the fac┬©ade which obstructs the radio signal and introduces an additional absorption term to the path loss.

At 2010, we are at the effective end of the first decade of Wireless Sensor Network (WSN) research and that the aspects such as energy efficient routing have pretty much had their day as the sensing, computing and energy technologies have now moved on. There now seems to be a consensus in the field as to what the next challenges are. This paper will describe some of those challenges for the next decade and discuss some of the key impediments hindering WSN research. From this we report a small experiment whereby we try to take on board some of the critiques we put forward to see what we come up with. To this end, we indeed show how a simple solution can help to solve many of the problems we list, and in doing so, highlight some of the difficulties in keeping to our own recommendations regarding the future direction of WSN research.

Internet of Things (IOT) is experiencing a super-fast growing phase. Wireless Sensor Networks (WSN), as the “five sense organs” and teleneuron of IOT, is developing fast along. Owing to the application-oriented characteristics of WSN, WSN applications may differ enormously in implementation methods. The WSN developers may have to rewrite the code for each and every application. Along with the increasing demand to WSN applications, WSN developers may have heavier tasks of programming for these applications. Thanks to TinyOS and NesC, an operating system and programming language designed especially for WSN, raises the WSN application's programming to a higher level. Large number of supported sensor hardware plus system provided and user-de-fined libraries eases WSN application programmers' jobs. How-ever, the massive amount of nodes' communication and networking, and security protection slows down the development pace. A unified and empirical WSN application implementation platform is one of the available solutions to the problem. This paper introduces an empirical WSN application implementation platform, which avails the WSN developers build an application with unified code template and network packet generation and processing strategies.

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.

The article deals with an improved analysis of the train flow system in Ukraine’s railway network. The main objective of the investigation is to reveal the peculiarities of the car flow destination system and to apply up-to-date knowledge for higher efficiency of railway transport. To solve the scientific problem the methods of complex network analysis have been used, thereby determining the basic statistic factors of the network topology. It has been proved that the destination network of ’s train formation plan is characterized by scale invariance. The revealed peculiarities of assortative mixing have made the understanding of the system’s processes simpler. The results obtained can be applied in analysis of the transportation system survivability of ’s railway network.