scholarly journals The effects of LT-SN on energy dissipation and lifetime in wireless sensor networks

Author(s):  
Zeydin Pala

Wireless sensor networks (WSNs) still attract the attention of researchers, users and the private sector despite their low power and low range tendency for malfunction. This attraction towards WSNs results from their low cost structure and the solutions they offer for many prevalent problems. Many conditions, which remain unforeseen or unexpected during the design of the system, may arise after the initialization of the system. Similarly, many situations where security vulnerabilities take place may emerge in time in WSNs operating normally. In this study, we called nodes which enter sleeping mode without any further waking up and causing a sparser number of nodes in the network without any function in data transmission as Long-Term Sleep Nodes (LT-SN); and considered energy spaces caused by such nodes as a problem; and established two Linear Programming (LP) models based on the efficiency of the present nodes. We offered two different models which present the effect of sensor nodes, which were initially operating in wireless sensor network environment and did not wake up following sleep mode, on network lifetime. The results of the present study report that as the number of LT-SN increases, the lifetime of the network decreases.

2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.


2020 ◽  
Author(s):  
Ademola Abidoye ◽  
Boniface Kabaso

Abstract Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime


Sensor nodes are exceedingly energy compelled instrument, since it is battery operated instruments. In wsn network, every node is liable to the data transmission through the wireless mode [1]. Wireless sensor networks (WSN) is made of a huge no. of small nodes with confined functionality. The essential theme of the wireless sensor network is energy helpless and the WSN is collection of sensor. Every sensor terminal is liable to sensing, store and information clan and send it forwards into sink. The communication within the node is done via wireless network [3].Energy efficiency is the main concentration of a desining the better routing protocol. LEACH is a protocol. This is appropriate for short range network, since imagine that whole sensor node is capable of communication with inter alia and efficient to access sink node, which is not always correct for a big network. Hence, coverage is a problem which we attempt to resolve [6]. The main focus within wireless sensor networks is to increase the network life-time span as much as possible, so that resources can be utilizes efficiently and optimally. Various approaches which are based on the clustering are very much optimal in functionality. Life-time of the network is always connected with sensor node’s energy implemented at distant regions for stable and defect bearable observation [10].


Author(s):  
Lina M. Pestana Leão de Brito ◽  
Laura M. Rodríguez Peralta

As with many technologies, defense applications have been a driver for research in sensor networks, which started around 1980 due to two important programs of the Defense Advanced Research Projects Agency (DARPA): the distributed sensor networks (DSN) and the sensor information technology (SensIT) (Chong & Kumar, 2003). However, the development of sensor networks requires advances in several areas: sensing, communication, and computing. The explosive growth of the personal communications market has driven the cost of radio devices down and has increased the quality. At the same time, technological advances in wireless communications and electronic devices (such as low-cost, low-power, small, simple yet efficient wireless communication equipment) have enabled the manufacturing of sensor nodes and, consequently, the development of wireless sensor networks (WSNs).


2012 ◽  
Vol 463-464 ◽  
pp. 261-265
Author(s):  
Fei Hui ◽  
Xiao Le Wang ◽  
Xin Shi

In this paper, hazardous materials transportation monitoring system is designed, implemented, and tested using Wireless Sensor Networks (WSNs). According to energy consumption and response time during clustering of Wireless Sensor Networks LEACH (Low Energy Adaptive Clustering Hierarchy) routing protocol, we proposed STATIC-LEACH routing protocol based on static clustering, it can effectively reduce energy consumption of the wireless sensor nodes and reduce network latency of cluster. With WSN and GSM/GPRS, low cost and easy deployment remote monitoring is possible without interfering with the operation of the transportation.


Aerospace ◽  
2006 ◽  
Author(s):  
Shashank Priya ◽  
Dan Popa ◽  
Frank Lewis

Wireless sensor networks (WSN) have tremendous potential in many environmental and structural health monitoring applications including, gas, temperature, pressure and humidity monitoring, motion detection, and hazardous materials detection. Recent advances in CMOS-technology, IC manufacturing, and networking utilizing Bluetooth communications have brought down the total power requirements of wireless sensor nodes to as low as a few hundred microwatts. Such nodes can be used in future dense ad-hoc networks by transmitting data 1 to 10 meters away. For communication outside 10 meter ranges, data must be transmitted in a multi-hop fashion. There are significant implications to replacing large transmission distance WSN with multiple low-power, low-cost WSN. In addition, some of the relay nodes could be mounted on mobile robotic vehicles instead of being stationary, thus increasing the fault tolerance, coverage and bandwidth capacity of the network. The foremost challenge in the implementation of a dense sensor network is managing power consumption for a large number of nodes. The traditional use of batteries to power sensor nodes is simply not scalable to dense networks, and is currently the most significant barrier for many applications. Self-powering of sensor nodes can be achieved by developing a smart architecture which utilizes all the environmental resources available for generating electrical power. These resources can be structural vibrations, wind, magnetic fields, light, sound, temperature gradients and water currents. The generated electric energy is stored in the matching media selected by the microprocessor depending upon the power magnitude and output impedance. The stored electrical energy is supplied on demand to the sensors and communications devices. This paper shows the progress in our laboratory on powering stationary and mobile untethered sensors using a fusion of energy harvesting approaches. It illustrates the prototype hardware and software required for their implementation including MEMS pressure and strain sensors mounted on mobile robots or stationary, power harvesting modules, interface circuits, algorithms for interrogating the sensor, wireless data transfer and recording.


Many researches have been proposed for efficiency of data transmission from sensor nodes to sink node for energy efficiency in wireless sensor networks. Among them, cluster-based methods have been preferred In this study, we used the angle formed with the sink node and the distance of the cluster members to calculate the probability of cluster head. Each sensor node sends measurement values to header candidates, and the header candidate node measures the probability value of the header with the value received from its candidate member nodes. To construct the cluster members, the data transfer direction is considered. We consider angle, distance, and direction as cluster header possibility value. Experimental results show that data transmission is proceeding in the direction of going to the sink node. We calculated and displayed the header possibility value of the neighbor nodes of the sensor node and confirmed the candidates of the cluster header for data transfer as the value. In this study, residual energy amount of each sensor node is not considered. In the next study, we calculate the value considering the residual energy amount of the node when measuring the header possibility value of the cluster.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhe Wei ◽  
Shuyan Yu ◽  
Wancheng Ma

In view of the spatiotemporal limitations of traditional healthcare services, the use of wireless communication has become one of the main development directions for the medical system. Compared with the traditional methods, applying the potential and benefits of the wireless sensor networks has more advantages such as low cost, simplicity, and flexible data acquisition. However, due to the limited resources of the individual wireless sensor nodes, traditional security solutions for defending against internal attacks cannot be directly used in healthcare based wireless sensor networks. To address this issue, a negative binomial distribution trust with energy consideration is proposed in this study. The proposed method is lightweight and suitable to be operated on the individual healthcare sensors. Simulations show that it can effectively deal with the internal attacks while taking the energy saving into consideration.


2014 ◽  
Vol 11 (3) ◽  
pp. 1017-1035 ◽  
Author(s):  
Young-Long Chen ◽  
Mu-Yen Chen ◽  
Fu-Kai Cheung ◽  
Yung-Chi Chang

Energy is limited in wireless sensor networks (WSNs) so that energy consumption is very important. In this paper, we propose a hybrid architecture based on power-efficient gathering in sensor information system (PEGASIS) and low-energy adaptive clustering hierarchy (LEACH). This architecture can achieve an average distribution of energy loads, and reduced energy consumption in transmission. To further extend the system lifetime, we combine the intersection-based coverage algorithm (IBCA) with LEACH architecture and the hybrid architecture to prolong the system lifetime that introducing sensor nodes to enter sleep mode when inactive. This step can save more energy consumption. Simulation results show that the performance of our proposed LEACH architecture with IBCA and the hybrid architecture with IBCA perform better than LEACH architecture with PBCA in terms of energy efficiency, surviving nodes and sensing areas.


2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Farzad Kiani

Energy issue is one of the most important problems in wireless sensor networks. They consist of low-power sensor nodes and a few base station nodes. They must be adaptive and efficient in data transmission to sink in various areas. This paper proposes an aware-routing protocol based on clustering and recursive search approaches. The paper focuses on the energy efficiency issue with various measures such as prolonging network lifetime along with reducing energy consumption in the sensor nodes and increasing the system reliability. Our proposed protocol consists of two phases. In the first phase (network development phase), the sensors are placed into virtual layers. The second phase (data transmission) is related to routes discovery and data transferring so it is based on virtual-based Classic-RBFS algorithm in the lake of energy problem environments but, in the nonchargeable environments, all nodes in each layer can be modeled as a random graph and then begin to be managed by the duty cycle method. Additionally, the protocol uses new topology control, data aggregation, and sleep/wake-up schemas for energy saving in the network. The simulation results show that the proposed protocol is optimal in the network lifetime and packet delivery parameters according to the present protocols.


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