Communication In Wireless Sensor Networks Research Articles

Energy efficient clustering routing protocol using novel admission allotment scheme (AAS) based intra-cluster communication for Wireless Sensor Network

Energy efficient clustering routing protocol using novel admission allotment scheme (AAS) based intra-cluster communication for Wireless Sensor Network

A modified graywolf‐basedchameleon swarm algorithm for minimizing energy consumption and enabling secure communication in wireless sensor network

SummaryThe efficiency and security of WSNs are improved by designing multiple lightweight cryptographic techniques and a 6LoWPAN protocol, depending on resource utilization and a reasonable amount of energy. This is still caused by constraints such as power resource management, authentication, key management, and flexibility protocols. To address these challenges, a novel approach called the modified gray wolf‐based chameleon swarm (MGW‐CS) algorithm is presented to select the cluster heads from WSN nodes. The MGW‐CS algorithm is an amalgamation of both improved gray wolf optimizer and chameleon swarm algorithm. During cluster head selection, the QoS parameters such as network lifetime, energy efficiency, and throughput and packet delivery ratio are improved and optimized. By presenting a lightweight and flexible cryptographic model to manage encryption complexities, the encryption parameters are automatically selected based on the currently available resources of each sensor node for data encryption. Among various WSN nodes, data exchanging and secure communication are established with the development of novel authentication and a lightweight key management model. The proposed model is implemented using the NS‐2 software. The proposed methodology offers a packet delivery rate of 98.6% for a total of 500 nodes when compared to the different state‐of‐art techniques.

Zigbee-Based Low Power Consumption Wearables Device for Voice Data Transmission

Short-range wireless technologies can transmit real-time voice, audio, picture, and video communications. Such networks’ energy usage and transmission reach are crucial, especially for portable and power autonomous devices. Voice over Zigbee technology’s goal is to create a competitive service that excels in these performance factors. IEEE standard 802.15.4 specifies two layers for low-rate WPANs: the physical layer and the media access control layer, with a data rate limit of 250 kbps. This partnership used low-level PHY and MAC layers as the foundation for developing the Zigbee network protocol, security, and applications. To overcome the problem of lowering costs and power usage to make this technology more accessible to the general public. This system displays the network’s operational data, such as wireless voice communication. This effort was made to minimize the overall cost of manufacturing such gadgets that contribute to home automation systems and related projects. The primary goal of the research was to communicate voice through low-power microcontrollers such as 8-bit microcontrollers using Zigbee. In this study, we developed a wireless sensor network (WSN) communication system based on Zigbee to securely transfer speech data over a medium-range distance (medium) and lower the equipment cost and communication expenses by 30% without compromising the data integrity. A testbed has been established to validate the fundamental functionality of the proposed ZigBee-based home network system. The suggested system’s network coverage capabilities were evaluated, as well as its packet loss and energy savings in long-term wireless network monitoring duties.

V2X Communication for Message Transmission and Warning Detection

Currently, the way that smart cars operate is that they have sensors all around the vehicle to identify and learn about adjacent objects. However, the precision of these sensors frequently has a relatively short range. Reliable long-distance data collection is becoming increasingly important as autonomous driving systems gain in popularity. The suggested remedy for this problem is a gadget that would be mounted on every moving vehicle. This gadget would transmit data about the car (size, speed, acceleration, position, heading, etc.) and receive data about nearby cars with comparable equipment. This eliminates the need for intelligent vehicles to guess what other vehicles are doing around them. Vehicles can instead get this information directly from other vehicles on the road and spend more resources monitoring/tracking non-vehicular objects and feed their information directly to an intelligent system for further complex decision making. This report mainly consists of collecting data for M2M communication and analyzing data for V2V based protocols; establishing simple V2V communication with software tool and sample data; code for V2V communication using CCA with the help of AoDV; design and simulation of hardware architecture in its application. The simulation is performed on an open-source software which is created on its latest release. The test cases run is in a simulated environment of nodal communication representing clusters of vehicles on the radar interacting with each other. These nodes have reactive protocols such as Co- operative Collision Avoidance (CCA) and Ad-Hoc On Demand Distance Vectoring (AoDV). These aim at providing early warning and message routing using unicast and multicast. The results presented in this report show that the through-put, network-life, energy consumed and distance between the nodes are crucial factors that help route message passing between nodes in a given Wireless Sensor Network (WSN). The results obtained from the project discuss WSN communication using AoDV and CCA, along with this the hardware application is built on the idea to transfer vehicle information such as acceleration and displacement using the ESP-32 control module to establish communication that validates the message transmission between these modules in offline mode.

Detection and Blind Channel Estimation for UAV-Aided Wireless Sensor Networks in Smart Cities Under Mobile Jamming Attack

Unmanned aerial vehicles (UAVs) can be integrated into wireless sensor networks (WSNs) for smart city applications in several ways. Among them, a UAV can be employed as a relay in a "store-carry and forward" fashion by uploading data from ground sensors and metering devices and, then, downloading it to a central unit. However, both the uploading and downloading phases can be prone to potential threats and attacks. As a legacy from traditional wireless networks, the jamming attack is still one of the major and serious threats to UAV-aided communications, especially when also the jammer is mobile, e.g., it is mounted on a UAV or inside a terrestrial vehicle. In this paper, we investigate anti-jamming communications for UAV-aided WSNs operating over doubly-selective channels in the downloading phase. In such a scenario, the signals transmitted by the UAV and the malicious mobile jammer undergo both time dispersion due to multipath propagation effects and frequency dispersion caused by their mobility. To suppress high-power jamming signals, we propose a blind physical-layer technique that jointly detects the UAV and jammer symbols through serial disturbance cancellation based on symbol-level post-sorting of the detector output. Amplitudes, phases, time delays, and Doppler shifts - required to implement the proposed detection strategy - are blindly estimated from data through the use of algorithms that exploit the almost-cyclostationarity properties of the received signal and the detailed structure of multicarrier modulation format. Simulation results corroborate the anti-jamming capabilities of the proposed method, for different mobility scenarios of the jammer.

A new fuzzy logic approach for reliable communications in wireless underground sensor networks

A new fuzzy logic approach for reliable communications in wireless underground sensor networks

Разработка алгоритма повышения эффективности протокола маршрутизации С-LEACH

In the process of studying wireless sensor network protocols and communication mechanisms, the extension of network service life and minimization of node power consumption have become important indicators. In order to reduce the energy consumption caused by communication in a wireless sensor network, improve network scalability and extend the network lifecycle, it is important to intelligently connect network nodes using a certain clustering algorithm. The paper proposes an improved routing protocol for wireless sensors with low power consumption LEACH, based on data aggregation (C-LEACH). The Kalman filter algorithm was used to solve the problem of data accuracy on cluster member nodes. The principle of operation of the Kalman filter is explained by the example of the noise signal of the sensor. The above data modification model can be performed continuously to achieve the optimal evaluation and filtering effect. Thus, the volume of data sent by the node is reduced. Experimental results have shown that the proposed LEACH protocol based on data fusion (C-LEACH) effectively reduces data redundancy, reduces the power consumption of sensor nodes and prolongs the life cycle of wireless sensor networks compared to the traditional LEACH algorithm, significantly improves network integrity.

Energy efficient chaotic sparrow search algorithm based clustering protocol for wireless sensor network communications

Wireless sensor networks (WSN) include a collection of autonomous sensor nodes, which are generally deployed in a harsh or hostile environment to sense the physical parameters involved in the target region. It is highly utilized for target tracking, surveillance, and data gathering applications. Since the sensors in WSN operates on limited inbuilt batteries, it is needed to design energy efficient approaches to preserve energy and extend lifetime of the network. Earlier studies have reported that clustering is an effectual manner used for accomplishing energy efficiency and it is addressed with use of metaheuristic optimization algorithms. In this view, this paper present an energy efficient chaotic sparrow search algorithm based clustering (EE-CSSAC) technique for WSN. The proposed EE-CCSAC technique is dependent upon the integration of chaotic maps into the traditional sparrow search algorithm (SSA). In addition, the EE-CCSAC technique develops a fitness function with four variables to properly select the CHs and then organize clusters, thereby achieving energy efficiency. The experimental validation of the EE-CCSAC system takes place and the outcomes are related to recent clustering approaches. The simulation outcomes exhbited the effective outcome of the EE-CCSAC method on the other ones with respec to distinct estimation parameters.

An improved underwater wireless sensor network communication using Internet of Things and signal to noise ratio analysis

AbstractUnderwater acoustic (UWA) channels are widely regarded as one of the most challenging communication mediums. Low frequencies are best for acoustic propagation, and the bandwidth available for communication is extremely small. The worst channel situation often limits the efficiency of UWA communication systems due to the difficulty and time‐varying nature of the UWA channel. To solve the existing limitations related with underwater signal transmission and communication, an improved underwater communication system incorporated with Internet of Things (IoT) is proposed in this work. The proposed system utilizes the orthogonal signal division multiplexing modulation technique. Here the signal transmission process is achieved with the help of an IoT network system. An improved AdaBoost channel estimation algorithm is used to obtain the channel information. This work utilizes an improved stochastic gradient descent optimization method for selecting the suitable mode of signal transmission based on the estimated channel. Further, an adaptive recursive least square channel equalization algorithm is used for channel compensation. The simulation results are obtained with the help of the MATLAB platform. The performance is analyzed in terms of parameters such as signal to noise ratio, bit error rate, and mean square error. A comparison of the proposed method is also made with the existing methods. The evaluation results show that the proposed method performs better than the existing methods.

Connection Quality Prediction and Nonlinear Control of Power Grid Communication Wireless Network

Learn about effective and uncontrolled gambling on wireless networks. Firstly, according to the control purpose, considering the reliability requirement of microgrid for network communication, the characteristics of wireless sensor network communication quality of service in microgrid, the influence of wireless connection reliability, and the mathematical standard of wireless communication are determined. Then, according to the estimation of the occurrence time of wireless communication link reliability, the reliability of wireless sensor network communication link in a smart grid is improved based on a fuzzy nonlinear control algorithm. Finally, the security and reliability of the control system described in this paper are measured by simulation. The experimental results show that the reliability of the wireless communication estimation time estimation algorithm and the power control algorithm based on fuzzy control can estimate the reliability, shortsightedness, and accuracy of good connections in real time. By adjusting the output power of the node, the connection quality and reliability can be controlled stably.

An Improved Stacked Auto Encoder based Data Compression Technique for WSNs

Abstract: Because of the limited energy available to sensor nodes in wireless sensor networks (WSNs), data compression is critical in these networks. The majority of the time, data communication results in energy consumption; however, by minimizing data transmission and reception, the lifetime of sensor nodes may usually be extended significantly. To compress sensor data, we present a new Improved Stacked RBM Auto-Encoder model, which is built of two layers: an encode layer and a decode layer, which is described in detail in this work. Data from sensors is compressed and decompressed in the encode layer; data from sensors is reconstructed and compressed in the decode layer. The encode layer and the decode layer are both made up of four conventional Restricted Boltzmann Machines that are used throughout the system (RBMs). We also present an energy optimization strategy that, by trimming the parameters of the model, can further minimize the energy consumption of the model storage and calculation. We evaluate the model's performance by comparing it to the data acquired by Intel Lab in the environment. Assuming that the model's compression ratio is 10, the average Percentage RMS Difference value is 9.84 percent, and the average temperature reconstruction error value is 0.312 degrees Celsius. It is possible to minimize the energy consumption of node communication in WSNs by 92 percent. When compared to the traditional method, the proposed model achieves higher compression efficiency and reconstruction accuracy while maintaining the same compression ratio as the old method. The results of our experiments demonstrate that the new neural network model can not only be applied to data compression for WSNs, but it also has high compression efficiency and an excellent transfer learning capability. Keywords: Data Compression; Stacked-Autocoder; transfer learning; energy, consumption optimization

Cryptanalysis and enhancement of an authentication protocol for secure multimedia communications in IoT-enabled wireless sensor networks

Cryptanalysis and enhancement of an authentication protocol for secure multimedia communications in IoT-enabled wireless sensor networks

Near Ground Pathloss Propagation Model Using Adaptive Neuro Fuzzy Inference System for Wireless Sensor Network Communication in Forest, Jungle and Open Dirt Road Environments.

In Wireless Sensor Networks which are deployed in remote and isolated tropical areas; such as forest; jungle; and open dirt road environments; wireless communications usually suffer heavily because of the environmental effects on vegetation; terrain; low antenna height; and distance. Therefore; to solve this problem; the Wireless Sensor Network communication links must be designed for their best performance using the suitable electromagnetic wave behavior model in a given environment. This study introduces and analyzes the behavior of the LoRa pathloss propagation model for signals that propagate at near ground or that have low transmitter and receiver antenna heights from the ground (less than 30 cm antenna height). Using RMSE and MAE statistical analysis tools; we validate the developed model results. The developed Fuzzy ANFIS model achieves the lowest RMSE score of 0.88 at 433 MHz and the lowest MAE score of 1.61 at 433 MHz for both open dirt road environments. The Optimized FITU-R Near Ground model achieved the lowest RMSE score of 4.08 at 868 MHz for the forest environment and lowest MAE score of 14.84 at 868 MHz for the open dirt road environment. The Okumura-Hata model achieved the lowest RMSE score of 6.32 at 868 MHz and the lowest MAE score of 26.12 at 868 MHz for both forest environments. Finally; the ITU-R Maximum Attenuation Free Space model achieved the lowest RMSE score of 9.58 at 868 MHz for the forest environment and the lowest MAE score of 38.48 at 868 MHz for the jungle environment. These values indicate that the proposed Fuzzy ANFIS pathloss model has the best performance in near ground propagation for all environments compared to other benchmark models.

Modern Energy Optimization Approach for Efficient Data Communication in IoT-Based Wireless Sensor Networks

Many researchers are drawn to mobile wireless sensor networks (WSN) and the Internet of Things (IoT) because of the significant challenges of power consumption and network connectivity. A technique that takes into consideration the characteristics such as network probability, the identified region of individual nodes, and the radius of the whole identified region is presented in this article. Free-space propagation is carried out in the region of interest. This approach assures network connection, long-term communication sustainability, and maximum energy efficiency. It was discovered that a mathematical network model can be built using the probability theory. It has been possible to examine and evaluate the changes in sensor nodes as a function of distance from the detection region using this approach. As a result, a correlation has been established between a network’s communication radius and the identified region. Additionally, a novel method has been developed to reduce energy consumption and sustain connectivity through boosting the connectivity feature. Notably, IoT-based WSN architectures require more energy optimization than any other network, because they have resource-limited nodes. Also, a simulation plot of the proposed approach’s mathematical network scheme is shown to show if it works. The proposed method consumes much less energy averagely 40% compared to the existing methods, which are LEACH, ZTR, and DSR when the radius is 100.

Addressing the Directionality Challenge through RSSI-Based Multilateration Technique, to Localize Nodes in Underwater WSNs by Using Magneto-Inductive Communication

The deployment and efficient use of wireless sensor networks (WSNs) in underwater and underground environments persists to be a difficult task. In addition, the localization of a sensor Rx node in WSNs is an important aspect for the successful communication with the aforementioned environments. To overcome the limitations of electromagnetic, acoustic, and optical communication in underwater and underground wireless sensor networks (UWSNs), magneto-inductive (MI) communication technology emerged as a promising alternative for usage in UWSNs with a wide range of applications. To make the magneto-inductive underwater wireless sensor networks (MI-UWSNs) more efficient, recently, various research studies focused on the optimization of the physical layer, MAC layer, and routing layer, but none of them has taken into account the effect of directionality. Despite the directionality issue posed by the physical nature of a magnetic field, the unique qualities of MI communication open up a gateway for several applications. The directionality issue of MI sensors is a critical challenge that must be taken into account while developing any WSN protocol or localization algorithm. This paper highlights and discusses the severity and impact of the directionality issue in designing a localization algorithm for magneto-inductive wireless sensor networks (MI-WSNs). A received signal strength indicator (RSSI)-based multilateration localization algorithm is presented in this paper, where a minimum of 2 and maximum of 10 anchor Tx nodes are used to estimate the position of the sensor Rx nodes, which are deployed randomly in a 15 m × 15 m simulation environment. This RSSI-based multilateration technique is the most suitable option that can be used to quantify the impact of directionality on the localization of a sensor Rx node.

Complex Modified Projective Difference Function Synchronization of Coupled Complex Chaotic Systems for Secure Communication in WSNs

Complex-variable chaotic systems (CVCSs) have numerous advantages over real-variable chaotic systems in chaos communication due to their increased unpredictability, confidentiality, and the ease of implementation. Synchronization between the master and slave systems in CVCSs is key to achieving encryption and decryption. However, existing synchronization schemes for CVCSs require the amplitude of the chaotic signal to be much larger than that of the plaintext. Moreover, traditional chaotic masking of complete synchronization (CS) requires uniformity between the transmitter and receiver ends. Therefore, we propose a complex modified projective difference function synchronization (CMPDFS) of CVCSs to address these issues, where the modified projective matrix helps address the issues with the amplitude. The receiver end is reconstructed without uniformity of the transmitter. We design the CMPDFS controller and propose a new secure communication scheme for wireless sensor networks (WSNs). The basic principle is fundamentally different from traditional chaotic masking. Simulation results and security analysis demonstrate that the CMPDFS communication scheme has a large key space, high sensitivity to encryption keys, high security, and an acceptable encryption speed. Hence, the proposed scheme can improve the security of WSNs. Moreover, it also can be applied to similar communication systems.

Analysis of Energy Consumption in Wireless Body Area Network Usingmac Protocols (baseline And Smac)

Abstract A Wireless Body Area Network (WBAN) is a short-range network that consists of a coordinator and a gathering of low-power sensors that can be embedded in, or attached to the human body. A WBAN can be used for a diversity of new uses which including online health control, home/health care, pharmacy, multimedia, and sports, among many more, all of which take advantage of the unrestricted mobility that WBANs can provide. In the medical industry, for example, a patient may be fitted with a WBAN of sensors that continuously track basic biological functions including temperature, blood pressure, heart rate, electrocardiogram (ECG), breathing, and so on. The patient does not have to lie in bed and can move around freely in the room or even leave the hospital for a short period of time. This increases the patient's feature of life while further lowering treatment costs. Furthermore, evidence gathered over a prolonged period of time and in the patient's natural habitat provides more useful knowledge, allowing for a more definitive and, in some cases, quicker diagnosis. Sensors connected to the human body are normally battery-powered devices with brief lifetimes. Institute of Electrical and Electronics Engineers (IEEE) 802.15.6 standard is the typical choice for low power ingestion and reliable short-range communication for Wireless Body Sensor Networks (WBSNs). The effects are demonstrated using the Omnet++ simulator and its Castalia extension for WBANs

Chinese Translation Errors in English Machine Translation Based on Wireless Sensor Network Communication Algorithm

Globalization is a trend in the future, and the exchanges among countries in the world in economy, politics, and culture are becoming more and more frequent. In order to overcome the increasingly prominent language barriers, translation has become an indispensable “bridge” for communication between countries. Manual translation has long been unable to meet the growing needs of translation. So, machine translation came into being, especially in recent years, machine translation has developed rapidly. Compared with manual translation, machine translation has unique advantages, that is, fast translation speed and free access. With the gradual improvement of the quality of machine translation, the quality of translation has basically met the requirements of rough reading, which makes machine translation one of the hotspots in recent years. However, to achieve the level of intensive reading, the quality of machine translation needs to be further improved. A thorough study of translation error analysis is an important step to improve the quality of machine translation. At present, there are few studies on error analysis of business English in academic circles, and most of them are just simple classification of translation errors, lacking in in-depth empirical research. This study aims to study the advantages and disadvantages of machine translation in translation practice based on wireless sensor network communication algorithms, analyze the typical errors in machine translation, put forward the idea that posttranslation editing can make up for the shortcomings of machine translation, treat English machine translation more objectively, make full use of machine translation tools, combine machine translation with post-manual editing perfectly, improve translation speed, and guarantee translation quality at the same time.

A Secure Authentication Scheme for Wireless Sensor Networks Based on DAC and Intel SGX

Wireless sensor networks (WSNs) are widely implemented in military, intelligent medical, intelligent transportation, space exploration, and other fields. However, the authentication and communication of WSNs are carried out in the harsh external environment via a public channel, which is more vulnerable to various attacks than the traditional networks. Authentication is the key technology of security measures, but a common authentication scheme is not suitable for WSNs due to limitations of memory, computing, and energy consumption. Therefore, designing a secure and efficient authentication scheme is essential in WSNs. In recent years, several studies proved that the dynamic authentication credential (DAC) is efficient for enhancing the security of the authentication scheme. This article designs a secure authentication scheme for WSNs based on DAC and Intel software guard extensions (SGX). Compared with other DAC authentication schemes, our scheme provides the confirmation action of DAC rotation, which can effectively prevent the asynchronous update problem caused by packet loss. In order to resist the privileged user attack and the authentication table leakage attack, we choose the SGX, which can protect the data in use, as the trusted execution environment in the gateway node, and we adopt SGX to store the master key for protecting the authentication table. Finally, the security of our authentication scheme is verified by BAN logic, the simulation tool AVISPA, and informal security analysis. Through the consumption overhead analysis, the NS3 simulation result, and detailed comparison with other recent schemes, we conclude that our scheme is practical and achieves better security with less overhead.

The Design of Formulation of Triangulation Network Model Using Simulate Environment for Co-Operative Communication in WSN using Matlab

Abstract: Wireless Sensor Networks (WSNs) gained universal attention now a day owing to This innovative is sensing technology to incorporate an immense number sensor nodes or motes set up in an area of perceive any continuously are fluctuating physical to phenomena. These tiny sensor nodes sense and process the sensed data and transfer this information to a base station or sink via radio frequency (RF) channel. The small size of these sensors is an advantage as it can be easily embedded within any device or in any environment. This feature has attracted the use of WSNs in immense applications especially in monitoring and tracking; the most prominent being the surveillance applications. But this type of tiny sizes of sensors to nodes restricts to resourcing capabilities. Usually to WSNs are install to application area to the human intervention of quite risk and difficult. The sense information might to need to taking the critical decisions to emergency applications. So maintaining the connectivity of the network is of utmost importance. The efficient use of the available resources to the maximum extend is a necessity to prolong the network lifetime. Most of research the area of WSNs has concentrate on energy efficiency where the design of energy efficient routing protocols plays a major role. The triangulations rules were applied for 20, 50 and 100 nodes demonstration for WSNs integrated with co-operative communications.