Wireless Sensor Network Architecture Research Articles

A Location Based Energy Proficient Path Routing for Internet of Things and Its Applications

The Internet of Things (IoT) is an establishment with sensors, base station, gateway, and network servers. IoT is an efficient and intellectual system that minimizes human exertion as well as right to use to real devices. This method also has an autonomous control property by which any device can control without any human collaboration. IoT-based automation has become very reasonable and it has been applied in several sectors such as manufacturing, transport, health care, consumer electronics, etc. In WSN’s smaller energy consumption sensors are expected to run independently for long phases. So much ongoing researches on implementing routing protocols for IoTbased WSNs.Energy consciousness is an essential part of IoT based WSN design issue. Minimalizing Energy consumption is well-thought-out as one of the key principles in the Expansion of routing protocols for the Internet of things. In this paper, we propose a Location based Energy efficient path routing for Internet of things and its applications its sensor position and clustering based finding the shortest path and real time implementation of Arduino based wireless sensor network architecture with the ESP8266 module. Finally, analyze the principles of Location-based energy-efficient routing and performance of QoS parameters, and then implemented automatic gas leakage detection and managing system.

Scalable asynchronous localization algorithm with mobility prediction for underwater wireless sensor networks

With the exploration of ocean resources, underwater wireless sensor networks have become a new research focus. Localization is one of most important technologies in the application of underwater wireless sensor networks. Because of the complex of underwater environment, it is difficult to realize the precisely synchronous localization in the underwater wireless sensor networks especially the large-scale networks with mobility. To solve this problem, in this paper, we propose a scalable asynchronous localization algorithm with mobility prediction. In this localization algorithm, the large-scale underwater wireless sensor network architecture is designed. Considering the node mobility, the node motion model is built based on the tidal mobility. By analyzing the asynchronous communication between the anchor nodes and ordinary nodes, the initial position of ordinary nodes is obtained and the future position of ordinary nodes is predicted and updated. The precisely located ordinary nodes are upgraded to new reference nodes and the new reference nodes locate the other unknown ordinary nodes together with the anchor nodes until the localization tasks of all ordinary nodes are completed. Simulation results confirm that the proposed localization algorithm can achieve accurate localization of mobile nodes in large-scale underwater wireless sensor networks with asynchronous clock.

Xbee-Based WSN Architecture for Monitoring of Banana Ripening Process Using Knowledge-Level Artificial Intelligent Technique.

Real-time monitoring of fruit ripeness in storage and during logistics allows traders to minimize the chances of financial losses and maximize the quality of the fruit during storage through accurate prediction of the present condition of fruits. In Pakistan, banana production faces different difficulties from production, post-harvest management, and trade marketing due to atmosphere and mismanagement in storage containers. In recent research development, Wireless Sensor Networks (WSNs) are progressively under investigation in the field of fruit ripening due to their remote monitoring capability. Focused on fruit ripening monitoring, this paper demonstrates an Xbee-based wireless sensor nodes network. The role of the network architecture of the Xbee sensor node and sink end-node is discussed in detail regarding their ability to monitor the condition of all the required diagnosis parameters and stages of banana ripening. Furthermore, different features are extracted using the gas sensor, which is based on diverse values. These features are utilized for training in the Artificial Neural Network (ANN) through the Back Propagation (BP) algorithm for further data validation. The experimental results demonstrate that the projected WSN architecture can identify the banana condition in the storage area. The proposed Neural Network (NN) architectural design works well with selecting the feature data sets. It seems that the experimental and simulation outcomes and accuracy in banana ripening condition monitoring in the given feature vectors is attained and acceptable, through the classification performance, to make a better decision for effective monitoring of current fruit condition.

A Hybrid Range-free Algorithm Using Dynamic Communication Range for Wireless Sensor Networks

Location plays a backbone role in networks, since it will great influence basic wireless sensor networks (WSNs) architecture. Distance-Vector Hop (DV-Hop) is a representative range-free localization algorithm, which is widely utilized to locate node position in location-based application. However, with poor localization accuracy, it cannot satisfy precise location-based application requirement. Consequently, we proposed a hybrid range-free algorithm depends on dynamic communication range to address low localization accuracy problem, named as DCDV-Hop. Firstly, we applied statistical methods to analyze the relationship between location error and hop count under different communication ranges. Thereafter, we employed centroid algorithm to calculate target node coordinate based on hop threshold. Finally, a weighted least square is applied to locate remaining target nodes. We conducted considerable experiments, the results demonstrated that our proposed algorithm DCDV-Hop can effectively reduce accumulate localization error and improve localization accuracy of target nodes, with stable performance. Moreover, maximum localization accuracy reached up to 91.35% and localization error reduced more than 50%, compared with DV-Hop algorithm.

On the Lifetime of Asynchronous Software-Defined Wireless Sensor Networks

In this article, we consider a software-defined wireless sensor network (WSN) architecture which conserves energy by applying asynchronous duty cycling. In asynchronous sensor networks, the overhearing adversely impacts the energy consumption of the nodes. Using a mathematical model, we compute the maximum lifetime of the network and accordingly propose a multichannel operation and transmit power control to reduce the effect of overhearing in asynchronous networks. Our comprehensive test results confirm that for the network with load-aware nonuniform sensor node deployment, the network lifetime is much higher compared to a uniform deployment. We also show that the use of data aggregation software-defined WSNs (SDWSNs) can improve the network lifetime as compared to the data gathering networks.

Wireless Sensor Network with Power Management System for Water Level Regulation in Paddy Fields

Paddy cultivation is one of the major crops cultivated in India. Normally paddy cultivation is grown twice in a year, where the consumption of water is high during the cultivation. The monitoring of the water level continuously is a little bit tedious to the farmer. However, with the assistance of advanced technology, the burden on the farmer can be reduced. So, in this study, we are proposing the Wireless Sensor Network (WSN) architecture-based water level regulating system. WSN architecture consists of three nodes like sensor node, cluster head node, and sink node. With the assistance of the float sensor and ZigBee wireless communication module, the sensor node which is deployed in the paddy field senses the water level data and communicates to the sink node. The cluster head node monitors the sensor nodes of the cluster of paddy fields and controls the actuator concerning the water level. Sink node is generally located nearby farmer location, with the assistance of sink node the farmer observer the status of water level in their paddy fields in the LCD display. This system enhances in maintaining the optimal level of water and also reduces the burden on the farmer for continuous monitoring. Especially the sensor node follows the power management system, where the power interruption is avoided.

Efficient fault-tolerant routing in IoT wireless sensor networks based on path graph flow modeling with Marchenko–Pastur distribution (EFT-PMD)

In the internet of things (IoT) based wireless sensor network (WSN), the nodes are scattered to segregate the rapt data in the relevant field of application. In general, sensor nodes of IoT possess heterogeneous property and display cluster-based routing to transmit the data as it is considered as an efficient routing method. When one or more cluster heads (CHs) fail, the sensed data of sensor nodes that are currently serving cannot be forwarded by the faulty CHs. Consequently, data of the IoT application will not be sufficiently sensed by the sink node (gateway). As a result, information processing of this field will be affected profusely. This paper focuses on the development of a paired cluster fault-tolerant disjoint path routing in a path graph and a novel approach to solve this dilemma in polynomial time of the degree of the graph. The objective of this proposed IoT–WSN architecture is to diminish the latency, end-to-end delay as well as energy consumption and thereby improving the performance in terms of throughput and packet delivery ratio. The performance of this proposed method in IoT–WSN network is measured and affirmed using benchmark network simulator.

UAV-Aided trustworthy data collection in federated-WSN-enabled IoT applications

In emerging applications of the Internet of Things (IoT), wireless sensor networks (WSNs) are usually federally deployed for these purposes of data gathering, tracking and monitoring. Under the universal WSN architecture, a mass of collected data will be converged on deployed sinks. Therefore, reasonable solutions for sink deployment must be achieved to optimally operate federated-WSN-enabled IoT applications. To address this issue, the deployment of unmanned aerial vehicles (UAVs) acting as mobile sinks is investigated, in which a new concept of ‘great full-coverage subgraph’ with the most complete connectivity is introduced to generate candidate areas for deploying UAVs. Thereby, the investigation is transformed into solving a traditional K-center problem formulated as a multi-objective joint optimization with multiple constraints. Subsequently, to address serious security vulnerabilities on UAV-aided trustworthy data collection, a lightweight authority authentication model using specific procedures is investigated to enforce the data collection session to be conducted only by both trusted sensors and UAVs with an acceptable authentication delay. Finally, numerical analysis and evaluation results are shown to demonstrate efficiencies of investigations.

Design of Digital Aerial Photography System for UAV based on Wireless Sensor Network

The traditional UAV aerial photography system has the disadvantages of unclear imaging, low system efficiency and poor flight control effect. Thus, a digital aerial photography system based on wireless sensor network is proposed. Firstly, the principle of aerial photography system is analyzed, and the wireless sensor network is set up. A large number of wireless sensor nodes are deployed in the interval, and functions such as wireless communication and calculation are completed by nodes; the SN-RN data acquisition layer, the RN-UAV relay transmission layer and the UAV-DC mobile aggregation layer are designed to form a wireless sensor network architecture, and the UAV digital aerial photography technology is combined to form the wireless sensor network. Experiments show that the medium error, maximum error and medium error limit of the digital aerial photography of the UAV are low, the total working time of the system is short, and the accuracy of the flight execution of the UAV is maintained between 93%-95%, and always stable. Therefore, the overall imaging effect of this method is better, the system work efficiency is higher, the system control effect is better, and it is more practical and advantageous.

Resource Management in Cloud Radio Access Network: Conventional and New Approaches.

Cloud radio access network (C-RAN) is a promising mobile wireless sensor network architecture to address the challenges of ever-increasing mobile data traffic and network costs. C-RAN is a practical solution to the strict energy-constrained wireless sensor nodes, often found in Internet of Things (IoT) applications. Although this architecture can provide energy efficiency and reduce cost, it is a challenging task in C-RAN to utilize the resources efficiently, considering the dynamic real-time environment. Several research works have proposed different methodologies for effective resource management in C-RAN. This study performs a comprehensive survey on the state-of-the-art resource management techniques that have been proposed recently for this architecture. The resource management techniques are categorized into computational resource management (CRM) and radio resource management (RRM) techniques. Then both of the techniques are further classified and analyzed based on the strategies used in the studies. Remote radio head (RRH) clustering schemes used in CRM techniques are discussed extensively. In this research work, the investigated performance metrics and their validation techniques are critically analyzed. Moreover, other important challenges and open research issues for efficient resource management in C-RAN are highlighted to provide future research direction.

Precision agriculture and farming using Internet of Things based on wireless sensor network

AbstractIn the recent past, the agriculture and farming industry has become the precision network connectivity of sensors with a new dimension of Internet of Things (IoT) technology. The cloud computing and wireless sensor network‐ (WSN) based extensive distance network in IoT can be applied to the agriculture and farming industry in a remote area. In this paper, we propose scalable wireless sensor network architecture for monitoring and control using IoT for agriculture and farming in a remote area. One of the significant managements in precision agriculture and farming (PAF) is water resource irrigation and proper utilization of water resources. Appropriate utilization of water irrigation management can be achieved by applying WSN technology using IoT. The efficient communication of various wireless sensors is processed using IoT in PAF to improve the productivity of farmers. We have analyzed the WSN structure based on throughput maximization, latency minimization, high signal‐to‐noise ratio (SNR), minimum mean square error, and improved coverage area. The experimental results have proved that the proposed methodology provides better performance than conventional IoT‐based agriculture and farming.

Merging of IoT and WSN for Real-Time Air Condition Monitoring Systems Towards Medan Smart City

Lots use of motorbike and car vehicles, industrial gas disposal, ciga-rette smoke and also forest fires cause high levels of air pollution in the city of Medan, North Sumatra, Indonesia. Based on these problems, an air condition monitoring device was built with the concept of low cost and low power, with a wireless sensor network (WSN) architecture from end device hardware, data col-lecting, data processing in gateway, and data visualization. IRIS hardware plat-forms are used in this system, whereas the communication between base station and gateway via internet networking. Therefore, people can monitor the air condi-tion results by real-time through a website-based application or an android smartphone.

EA-MAC: A QoS Aware Emergency Adaptive MAC Protocol for Intelligent Scheduling of Packets in Smart Emergency Monitoring Applications

The evolution of the wireless sensor network (WSN) in recent years has reached its greatest heights and applications are increasing day by day, one such application is Smart Emergency Monitoring Systems (SMESs) which is in vision of implementation in every urban and rural areas. The implementation of WSN architecture in the Smart Monitoring Systems needs an intelligent scheduling mechanism that efficiently handles the high traffic load as well as the emergency traffic load without sacrificing the energy efficiency of the network. However, the traditional scheduling algorithms such as First Come First Served (FCFS), Round Robin, and Shortest Job First (SJF) cannot meet the requirements of high traffic load in SMESs. To address these shortcomings, this paper presents Emergency Adaptive Medium Access Control protocol (EA-MAC), a fuzzy priority scheduling based Quality-of-service (QoS)-aware medium access control (MAC) protocol for hierarchical WSNs. EA-MAC protocol employs the most powerful fuzzy logics to schedule the sensor nodes with both normal and emergency traffic load without any data congestion, and packet loss and maintaining the better QoS which is considered to be more important in SMESs applications. Moreover, a novel rank-based clustering mechanism in EA-MAC protocol prolongs the network lifetime by minimizing the distance between the Cluster Head (CH) and the Base Station (BS). Both analytical and simulation models demonstrate the superiority of the EA-MAC protocol in terms of energy consumption, transmission delay and data throughput when compared with the existing Time Division Multiple Access (TDMA) based MAC protocols such as LEACH protocol and Cluster Head Election Mechanism-Based On Fuzzy Logic (CHEF) protocol.

A Wireless Sensor Networks Security Protocol Architecture

A wireless sensor network is made up of extremely small autonomous units capable of sensing, computing and communicating. There are numerous restrictions on wireless sensor networks as the resource available to the wireless sensor network is limited. Thus, a number of clustering protocols in a routing sensor organization of sensor networks have been proposed in the literature which increase the throughput, save energy and decrease the delay in the system. In this paper, we put forward SNP, the one of its type link layer security architecture for wireless sensor networks. In this, the design vulnerabilities which were found in the protocols such as 802.11b and GSM are addressed using SNP. Security protocols have very conservative approach while guaranteeing the security and typically add up around 16-32 bytes as overhead. Owing to the scenario that sensor networks have limited supply of energy, little memory and low power processors, a 30 byte packet is more of unaffordable luxury for the wireless sensor networks. In SNP, the different trade-offs between separate cryptographic algorithms and wireless sensor network limitations are used to find an optimum point where packet overhead, security and resource requirements are met.

A Stochastic Game Approach for Collaborative Beamforming in SDN-Based Energy Harvesting Wireless Sensor Networks

Collaborative beamforming (CB) has recently emerged as a promising technique for transmission range extension and energy consumption reduction in wireless sensor networks (WSNs). However, due to the constrained energy and limited data processing capabilities of sensor nodes, the performance optimization of CB mainlobe and sidelobe control (SC) encounters challenges in the practical deployment. To address these challenges, we present an architecture of software-defined energy harvesting WSN (SD-EHWSN) for CB communications. Specifically, we first design the mechanism of CB communications based on the software-defined network (SDN) architecture to reduce the communication and computational overhead of sensor nodes. Then, we consider solar energy-harvesting system to achieve long-term operation of WSN and utilize a stationary Markov (SM) chain to model the arrival process of solar energy. Based on the stochastic nature of solar energy, a stochastic game model is developed to formulate the problem of CB optimization in SD-EHWSN, and the existence proof of Nash equilibria is provided. Based on the analytical results, we propose a reinforcement learning algorithm to maximize the long-term signal-to-noise ratio (SNR) performance with SC and prove the convergence of the algorithm. Simulation results are presented to validate the efficiency of the proposed scheme for CB communications in SD-EHWSN.

Performance Analysis of Software-Defined Multihop Wireless Sensor Networks

In this article, we propose a model-based characterization of energy consumption in a software-defined wireless sensor network (SD-WSN) architecture in an effort to examine the implications for network performance when making the WSN reprogrammable. The proposed model consists of breaking down all key functions involved in the correct functioning of an SD-WSN, namely; neighbor discovery, neighbor advertisement, network configuration, and data collection. The model is analyzed from a multihop network perspective. We consider two static SD-WSN scenarios to examine scalability, and one scenario to assess the performance implications in a pseudo-dynamic SD-WSN. Extensive simulation results are presented regarding the control overhead introduced, the percentage of alive nodes and remaining energy, and the impacts on network lifetime. We show that the accumulated control overhead is inversely proportional to the interaction period with the controller, whereas the remaining energy and the network lifetime are directly proportional to this parameter. Results show that the control overhead, for static SD-WSNs, can take up to 10%-29% of the total data flowing to the controller for the large SD-WSN and 6-19% for the small SD-WSN. For a pseudo-dynamic network, the control overhead can take up to two-thirds of the total data sent to the controller, and the network lifetime was reduced by up to 80% compared with the static scenarios.

An Improved Energy-Efficient Routing Protocol for Wireless Sensor Networks.

Cluster-based hierarchical routing protocols play an essential role in decreasing the energy consumption of wireless sensor networks (WSNs). A low-energy adaptive clustering hierarchy (LEACH) has been proposed as an application-specific protocol architecture for WSNs. However, without considering the distribution of the cluster heads (CHs) in the rotation basis, the LEACH protocol will increase the energy consumption of the network. To improve the energy efficiency of the WSN, we propose a novel modified routing protocol in this paper. The newly proposed improved energy-efficient LEACH (IEE-LEACH) protocol considers the residual node energy and the average energy of the networks. To achieve satisfactory performance in terms of reducing the sensor energy consumption, the proposed IEE-LEACH accounts for the numbers of the optimal CHs and prohibits the nodes that are closer to the base station (BS) to join in the cluster formation. Furthermore, the proposed IEE-LEACH uses a new threshold for electing CHs among the sensor nodes, and employs single hop, multi-hop, and hybrid communications to further improve the energy efficiency of the networks. The simulation results demonstrate that, compared with some existing routing protocols, the proposed protocol substantially reduces the energy consumption of WSNs.

Strengthening IoT-WSN Architecture for Environmental Monitoring

Saving the environment is the alarming red-hot topic of this trendy world. A proper arrangement is required to monitor different environmental pollutions. Many researchers and volunteers are developing and deploying Wireless Sensor Networks (WSN) for this purpose. Internet-of-Things (IoT) is one of the widely used cost-effective modern technologies to design wireless sensor nodes. Three fresh functional modules are introduced in this work to constitute the proposed work named as ‘Strengthening IoT-WSN Architecture for Environmental Monitoring’ (SIAEM) which is indented to overcome some impuissance of applying generalized wireless sensor network architecture in the field of environmental pollution monitoring. The functional modules introduced in this work are Customized Clustering of IoT-WSN Nodes (CCIN) and Energy Aware State Change Routing Protocol (EASCRP). The objective of this proposed IoT-WSN architecture is to reduce the Latency, Jitter, End-to-End delay and Power Consumption whereas, improving the performance parameters such as Throughput and Packet Delivery Ratio. The impact of proposed method in the performance of IoT-WSN network is measured and stated using benchmark network simulator.

Quality of Service in Wireless Sensor Networks: Imperatives and Challenges

: A Wireless Sensor Network (WSN) is an effective sensing technology that is used to replicate the human capability of sensing, collecting, computing, processing and transmitting the data that is collected from a very large area. In recent past, sensor technology has shown tremendous development in the field of environment & health monitoring, military surveillance, vehicle tracking, and detection. The participating sensor nodes are prone to failure because of limited resources. The topology of the networks is highly dynamic in nature because of frequent failure of the sensor nodes. The Quality of Service support to highly dynamic networks is one of the challenging tasks. The dynamic nature, unpredictable topology, the demand of miniature size of the devices, tiny size of sensors and limited resources attract the researchers towards the designing of QoS aware protocols. This paper has discussed the architecture, applications, life cycle and types of WSN. Further, various QoS protocols, their limitations, and challenges have also been discussed. Further, this paper presents the most important open issues and challenges in providing QoSs provisioning to the WSN as QoS routing, energy consumption, bandwidth utilization, security, and mobility. This comprehensive review surely helps the researchers to find the new existing challenges and also help them to design new research problems for their future work.

Improved Multiple Gateway Node Based Routing Architecture for Heterogeneous Wireless Sensor Network

In modern era, with technologies shifting from wired to wireless technologies, Wireless Sensor Networks (WSNs) play an essential role in advancement of technology. WSNs have limited battery .In this paper, we propose Improved Multiple Gateway Node (MGN) based Routing Architecture (IMRA) that increases both network lifetime and stability period of the network and also improves energy efficiency. It uses the technique of load balancing and considers average energy of the network to improve aforementioned parameters. IMRA is event-driven protocol and has four MGNs with unlimited power which makes this protocol efficient for use in disaster prone areas like earthquakes, forest fires etc. saving millions of lives. Wireless Sensor Networks (WSNs) play an essential role in advancement of technology. Various disasters like earthquakes, forest fires, etc. can be sensed in advance using latest technology in WSNs and preventive measures can be taken. IMRA surpasses other protocols by increasing Stability Period, Half Node Dead and Network lifetime by 58.18%, 55.94% and 52.96% respectively as compared to traditional MRA and by 156.99%, 86.2% and 90.12% respectively as compared to Threshold sensitive Energy Efficient Delay aware Routing Protocol(TEDRP).