Data Transmission In Wireless Sensor Networks Research Articles

Network Invulnerability Enhancement Algorithm Based on WSN Closeness燙entrality

Wireless Sensor Network (WSN) is an important part of the Internet of Things (IoT), which are used for information exchange and communication between smart objects. In practical applications, WSN lifecycle can be influenced by the unbalanced distribution of node centrality and excessive energy consumption, etc. In order to overcome these problems, a heterogeneous wireless sensor network model with small world characteristics is constructed to balance the centrality and enhance the invulnerability of the network. Also, a new WSN centrality measurement method and a new invulnerability measurement model are proposed based on the WSN data transmission characteristics. Simulation results show that the life cycle and data transmission volume of the network can be improved with a lower network construction cost, and the invulnerability of the network is effectively enhanced.

ИССЛЕДОВАНИЕ ХАРАКТЕРИСТИК СХЕМ РЕТРАНСЛЯЦИИ СИГНАЛА В БЕСПРОВОДНЫХ СЕТЯХ ДАТЧИКОВ

Wireless sensor networks (WSNs) are being actively implemented in various systems for remoteobservation and monitoring of distributed objects. WSNs have a number of undoubted advantages:flexibility, efficiency, relative cheapness, and the possibility of rapid deployment. However,the exchange of information and data is carried out in the WSN using wireless communicationchannels, which are subject to inevitable interference and noise, which leads to transmission errors and even to the loss of transmitted data packets. Another challenge, not fully resolved, is theuneven distribution of consumed energy within the WSN in the face of stringent requirements forenergy sources. Currently, there are two most widely used retransmission schemes in the loss oftransmitted data, namely, hop-by-hop and end-to-end. Most of the well-known studies devoted tothe issues of reliable data transmission in WSN using these schemes have been carried out experimentally.In addition, there are still no analytical methods for evaluating various reliabletransport solutions, which complicates the analysis of the proposed WSN. Therefore, the aim of theproposed work is the development of analytical methods and algorithms for studying the operatingcharacteristics of the signal relaying circuits in the WSN. Analytical methods are proposed forevaluating retransmission schemes in the WSN, based on a relatively new theoretical basis - thenetwork calculus for packet-switched networks, which is a tool for determining the size of the network.First, traffic, service and energy cost models are introduced. Based on these models andnetwork calculations, the maximum packet transmission delay and energy efficiency of the twomain types of retransmission schemes: hop-by-hop and end-to-end retransmission, are analyticallyestimated. According to the results of the experiment, the maximum latency and the maximumpower consumption of these two schemes are compared in several scenarios. In addition, the analyticallycalculated maximum delay is compared with the simulation results. With the proposedmethod, a suitable retransmission scheme can be selected based on the various requirements andconstraints to be set.

Grid-Based Routing Model for Energy Efficient and Secure Data Transmission in WSN for Smart Building Applications

Presently, due to the establishment of a sensor network, residual buildings in urban areas are being converted into smart buildings. Many sensors are deployed in various buildings to perform different functions, such as water quality monitoring and temperature monitoring. However, the major concern faced in smart building Wireless Sensor Networks (WSNs) is energy depletion and security threats. Many researchers have attempted to solve these issues by various authors in different applications of WSNs. However, limited research has been conducted on smart buildings. Thus, the present research is focused on designing an energy-efficient and secure routing protocol for smart building WSNs. The process in the proposed framework is carried out in two stages. The first stage is the design of the optimal routing protocol based on the grid-clustering approach. In the grid-based model, a grid organizer was selected based on the sailfish optimization algorithm. Subsequently, a fuzzy expert system is used to select the relay node to reach the shortest path for data transmission. The second stage involves designing a trust model for secure data transmission using the two-fish algorithm. A simulation study of the proposed framework was conducted to evaluate its performance. Some metrics, such as the packet delivery ratio, end-end delay, and average residual energy, were calculated for the proposed model. The average residual energy for the proposed framework was 96%, which demonstrates the effectiveness of the proposed routing design.

RETRACTED ARTICLE: Research on data transmission model of agricultural wireless sensor network based on game theory

This article has been retracted from publication in the Taylor & Francis journal, Acta Agriculturae Scandinavica, Section B — Soil & Plant Science. Following publication, concerns were raised by multiple third-parties around the content of the special issue and the decision-making process. Following an investigation by the Taylor & Francis Publishing Ethics & Integrity team in full cooperation with the Editor-in-Chief, it was confirmed that this article included in Special Issue titled “ Envisage Computer Modelling and Statistics for Agriculture”, guest edited by Gunasekaran Manogaran was not peer-reviewed appropriately, in line with the Journal's peer review standards and policy. As the stringency of the peer review process is core to the integrity of the publication process, the Editor and Publisher have decided to retract all of the articles within the above-named Special Issue. The journal has not confirmed if the authors were aware of this compromised peer review process. The journal is committed to correcting the scientific record and will fully cooperate with any institutional investigations into this matter. The authors have been informed of this decision. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines.

Fixed Point of Rational Contractions and Its Application for Secure Dynamic Routing in Wireless Sensor Networks

Security is one of the major concerns for data communication over wireless sensor networks (WSNs). Dynamic routing algorithms can provide small similarity paths of data delivery between two consecutive transmitted packets, improving data security without adding extra information or control messages. This article illustrates the iteration of the fixed point (FP) of rational contractions and generalized Banach contractions (BC) in the setting of F-metric space (F-MS). It also describes an FP of the said mappings, while restricting the imposition of the contraction only to a subset of the F-MS, the closed ball, rather than executing it on the entire F-MS. The results have been verified and supported by concise examples. Further, the application of the functional equation proved results with randomization is given to find a solution for secure dynamic routing of data transmission in WSNs. The application is a tool to analyze and model a network structure in which sensors can be deployed with high security and low risk in a greater region (sensor field), thus boosting the accuracy.

Optimal Data Transmission for WSNs with Data-Location Integration

Wireless sensor networks (WSNs) have good performance for data transmission, and the data transmission of sensor nodes has the function of symmetry. However, the wireless sensor nodes are facing great pressure in data transmission due to the increasing amount and types of data that easily cause premature energy consumption of some nodes and, thus, affects data transmission. Clustering algorithm is a common method to balance energy consumption, but the existing algorithms fail to balance the network oad effectively for big data transmission. Therefore, an optimal data transmission with data-location integration (ODTD-LI) is proposed for WSNs in this paper. For optimal data transmission, we update the network topology once for one round. In the proposed algorithm, we perform calculations of the optimal cluster heads, clustering and data transmission routing through three steps. We first deploy N homogeneous and symmetry nodes in a square area randomly and calculate the optimal number of cluster heads according to the node ocations. then, the optimal number of cluster heads, energy consumption, the distances and degrees of the nodes are taken into consideration during the clustering phase. Direct communication is carried out within a cluster, and the member nodes of the cluster pass the information directly to the cluster head. Lastly, an optimal hybrid routing from each cluster node to Sink is constructed for data transmission after clustering. The simulations verify the good performance of the proposed algorithm in view of the ifetime, average delay, coverage rate (CR) and oad balance of the network compared with the existing algorithms. Through the research conducted in this paper, we find that our work has good performance for selecting the hybrid routing in the network with the nodes randomly arranged.

Novel Fuzzy Based Crow Search Optimization Algorithm for Secure Node-to-Node Data Transmission in WSN

Various sensor nodes are interconnected with each other in wireless sensor network (WSN). WSN communicates to every node within the network wirelessly to collect data regarding the surrounding environment and send the particular data to the destination/centralised location. The sensor nodes transmit the data and the source sensor node transmits data to destination sensor nodes through various intermediary sensor nodes. Thus, secure transmission is required in which WSN must be free from malicious nodes to achieve safe transfer. In this paper, our objective is to provide secure data transmission in an efficient manner from source to destination through a trust based path namely novel fuzzy based crow search optimization algorithm (F-CSO) and optimised link state routing protocol (OLSR) protocol. Through NS3 tool, nodes are deployed in the network area and novel F-CSO is performed with respect to three parameters such as distance, degree and transmission energy. The best nodes are considered for optimization process and it must satisfy the three conditions such as lower distance between each node for transmitting the data, higher degree and higher energy for transmission. A set of nodes that satisfies this condition are gathered by the fuzzy rule technique and then further optimised by crow search optimization technique leading to exact nodes through which trust based transmissions are performed. Further, routing can be achieved by the OLSR protocol. The performance of the proposed system is compared with existing studies with respect to the system for detecting the malicious nodes with and without utilizing proposed F-CSO in terms of execution time, throughput, and packet delivery ratio. The evaluation result has shown that malicious nodes is detected in an efficient manner through the use of F-CSO, showing better results with various parameters.

Weighted Boost Spearman Correlative Dual Cluster Head for Robust Transmission in Wsn

Wireless Sensor Networks (WSNs) are widely used in various applications, but they are often subject to environmental factors that result in poor network performance and packet loss. To address this challenge, correlation-based routing algorithms have been proposed. However, the performance of these algorithms degrades when the correlation between nodes is low. In this paper, we propose a Weighted Boost Spearman Correlative Dual Cluster Head (WBSCDCH) approach for robust transmission in WSNs. The proposed approach uses weighted boosting to assign higher transmission power to cluster heads with low correlation and utilizes dual cluster heads for efficient data collection and transmission. Our simulation results show that the proposed approach outperforms existing algorithms in terms of packet delivery ratio, energy consumption, and end-to-end delay. This paper contributes to the field of WSNs by providing a novel approach for improving the robustness of data transmission in WSNs.

Energy-efficient hierarchical routing in wireless sensor networks based on fog computing

Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the twenty-first 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 the energy consumption of sensor nodes 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. 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 algorithm that can be used to construct an 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. We are aware that in WSNs, the certainty of the sensed data collected by a sensor node can vary due to many reasons such as environmental factors, drained energy, and hardware failures.

Wavelet-Based Least Common Ancestor Algorithm for Aggregate Query Processing in Energy Aware Wireless Sensor Network

Wireless sensor network (WSN) is developed as a network of sensors, which engage in sensing and transmitting the data to the sink node. The constraints, such as energy, memory, and bandwidth insist the researchers to develop an efficient method for data transmission in WSN. Accordingly, this paper introduces a data aggregation mechanism based on query processing, Wavelet-based Least Common Ancestor-Sliding window (WLCA-SW). The energy-loss and memory-crisis is well addressed using the proposed WLCA-SW through the successive steps of query processing, duplicate detection, data compression using the wavelet transformation, and data aggregation. The proposed WLCA-SWA is developed with the integration of the weighed sliding window and Least Common Ancestor (LCA), which enables the energy-aware aggregate query processing and de-duplication such that the duplicate records are detected potentially prior to the communication of the sensed data to the sink node. It is prominent that the weighed sliding window is the extension of the existing time-based sliding windows. The effectiveness of the proposed aggregate processing approach is evaluated based on the metrics, such as number of alive nodes, data reduction rate, data-loss percentage, and residual energy, which is found to be 33, 85%, 8.222%, and 0.0610 J at the end of 1000 rounds using 150 nodes for analysis. Moreover, the proposed method has the minimum aggregation error of 0.03, when the analysis is performed using 50 nodes.

WITHDRAWN: Developing a software reliability evaluation model for wireless sensor networks based on analysis of software fault growth

Abstract Due to potential of various application in emergency and security monitoring fields, fault tolerance monitoring in wireless sensor networks (WSNs) software reliability became one of the most fundamental concern in computer field. In WSNs Previous literature had been proposed about how to improve network reliability. However the work done on establishing evaluating models of reliability for WSNs are insufficient yet. In this article, a model for wireless sensor networks (WSNs) is developed for the reliability evaluation. This network state based model can effectively do the evaluation of the probability of successful transmission of data in WSNs with the consideration of the work states of both the sensor node’s different modules. For WSNs we did the evacuation for reliability of in both tasks i.e., single, multi-task modes. At the same time, how different network topologies, affect the reliability of WSNs is also discussed respectively. To evaluate the reliability of WSNs the simulation attempts are shown in results that impacts network state on reliability and the effectiveness in different reliable mechanisms.

A New wireless sensor networks Routing Algorithm Based on SPIN Protocols and Circumference Technique

In Wireless Sensor Networks (WSNs), the data transmission might be specified as a major challenge. Various protocols of routing were suggested for saving energy throughout the transmission of data in WSNs. The protocols of routing which are on the basis of data centric method were adequate in such regard which are performing data’s in-network aggregations for yielding energy- saving data dissemination, such sensor nodes have a few of limitations because of their limited, computing power, storage capacity, and limited energy. The data have been routed between nodes with the use of various routing protocols. In addition, there are a few routing protocols for WSNs, all such protocols attempted on eliminating a few of such limitations. A Circumference-based SPIN protocol, (C-SPIN), is going to implement for eliminating the limited energy as well as data overlap with the use of right-most data movement method.

Chaotic Butterfly Optimization with Optimal Multi-key Image Encryption Technique for Wireless Sensor Networks

Wireless sensor network (WSN) comprises a set of sensor nodes, mainly used for data collection and tracking process. The imaging sensors in WSN captures the images from the target environment, which needs to be securely transmitted to the base station (BS). Since data transmission in WSN takes place through wireless links, security is a major challenging issue involved in the design of WSN. Image encryption is a commonly available solution to securely transmit the images to destination without comprising security. Therefore, this study designs a novel Chaotic Butterfly Optimization with Optimal Multi-key Image Encryption (CBO-OMKIE) technique for WSN. The goal of the CBO-OMKIE technique is to securely encrypt the images in WSN. The proposed CBO-OMKIE technique involves the design of multi-key based image encryption technique to accomplish security in WSN. In addition, the CBO algorithm is applied to determine the optimal keys involved in the encryption process and it helps for improving the security level to a maximum extent. The performance validation of the CBO-OMKIE technique takes place using benchmark test images and the outcomes were examined under several aspects. The simulation outcome pointed out the enhanced security analysis of the CBO-OMKIE technique over the other techniques.

Enhanced authentication and key management scheme for securing data transmission in the internet of things

The Internet of Things (IoT), with its smartness and intelligence, is gradually changing human life by allowing everyday objects to be connected to the Internet. With the prevalence of the IoT, wireless sensor networks (WSNs) are attracting worldwide attention, because they cover a wide range of IoT applications. The sensors collect data from the physical world and communicate with each other through wireless links. Ensuring the security and privacy of WSNs’ communication is challenging. Recently, a secure authentication and key management scheme was proposed to secure data transmission in WSNs. In this paper, we show that this scheme has various security flaws, such as replay attack, denial of service attack, impersonation attack, and lack of mutual authentication and session key agreement. Then, we propose an enhanced scheme to overcome the identified security weaknesses. The security of the enhanced scheme is formally verified using the Burrows–Abadi–Needham logic and the Automated Validation of Internet Security Protocols and Applications tool. Our proposed scheme is more secure, efficient, and suitable for WSN-based IoT applications than recent related methods.

Energy-Efficient Algorithm for Reliable Routing of Wireless Sensor Networks

Quality of service (QoS) routing is one of the critical challenges in wireless sensor networks (WSNs), especially for surveillance systems. Multihop data transmission of WSNs, due to the high packet loss and energy-efficiency, requires reliable links for end-to-end data delivery. Current multipath routing works can provision QoS requirements like end-to-end reliability and delay, but suffer from a significant energy cost. To improve the efficiency of the network with multiconstraints QoS parameters, in this paper we model the problem as a multiconstrained optimal path problem and propose a distributed learning automaton (DLA) based algorithm to preserve it. The proposed approach leverages the advantage of DLA to find the smallest number of nodes to preserve the desired QoS requirements. It takes several QoS routing constraints like end-to-end reliability and delay into account in path selection. We simulate the proposed algorithm, and the obtained results verify the effectiveness of our solution. The results demonstrate that our algorithm has a better performance than current state-of-the-art competitive algorithms in terms of end-to-end delay and energy-efficiency.

Data Collection with Accuracy-Aware Congestion Control in Sensor Networks

Data collection is a fundamental and critical function of wireless sensor networks (WSNs) for the cyber-physical systems (CPS) to estimate the state of the physical world. However, unstable network conditions impose significant challenges in guaranteeing the data accuracy that is essential for the reliable estimation of physical states. Without efficiently resolving congestion during data transmission in WSNs, packet loss due to congestion can significantly degrade the data quality. Various congestion control schemes have been proposed to address this issue. Most of them rely on reducing transmitted data samples to eliminate the congestion, which, however, could lead to abysmally high estimation error. In this paper, we analyze the impact of congestion control on the data accuracy and propose a Congestion-Adaptive Data Collection scheme (CADC) to efficiently resolve the congestion under the guarantee of data accuracy. CADC mitigates congestion by adaptive lossy compression while ensuring a given overall data estimation error bound in a distributed manner. Considering that for a CPS application different data items may have different priorities, we also propose a weighted CADC scheme such that the data with higher priority has less distortion. We further adapt CADC to guarantee the accuracy of specific aggregate computations. Extensive simulations demonstrate the effectiveness and efficiency of CADC.

Performance Analysis of AODV with Sectoring in Resource Constrained Ad-Hoc Communication Network

In this paper the performance of an adaptive sectoring ad hoc on demand distance vector based routing algorithm applied for overall reliability improvement of wireless sensor networks (WSNs) with limited resources is considered. Reliable and energy efficient data transmission in WSNs to prolong their network lifetime is an important and challenging issue, which is proposed to be solved via the implementation of an energy efficient reliable data transfer scheme for WSNs named as “Adaptive Sectoring Scheme for Reliability”. In this approach, a given sensor field is divided into sectors activated one at a time by the occurrence of an event. To minimize the congestion as well as to increase the energy efficiency and maximize the packet delivery ratio, the sectoring process is adjusted dynamically according to a predefined reliability of the data transfer. Simulation experiments show that the proposed scheme leads to an improvement in reliability and energy consumption.

Trust Aware Moth Flame Optimization based Secure Clustering for Wireless Sensor Networks

Wireless sensor networks (WSN) encompass numerous sensor nodes deployed in the physical environment to sense parameters and transmit to the base station (BS). Since the nodes in WSN communicate via a wireless channel, security remains a significant issue that needs to be resolved. The choice of cluster heads (CHs) is critical to achieving secure data transmission in WSN. In this aspect, this article presents a novel trust-aware mothflame optimization-based secure clustering (TAMFO-SC) technique for WSN. The goal of the TAMFO-SC technique is to determine the trust level of the nodes and determine the secure CHs. The proposed TAMFO-SC technique initially determines the nodes' trust level, and the node with maximum trust factor can be chosen as CHs. In addition, the TAMFO-SC technique derives a fitness function using two parameters, namely residual energy and trust level. The inclusion of trust level in the CH selection process helps to accomplish security in WSN. A comprehensive experimental analysis exhibits the promising performance of the TAMFO-SC technique over the other compared methods.

An Energy-Efficient Region Source Routing Protocol for Lifetime Maximization in WSN

As the sensor layer of Internet of Things (IOT), enormous amount of sensor nodes are densely deployed in a hostile environment to monitor and sense the changes in the physical space. Since sensor nodes are driven with limited power batteries, it is very difficult and expensive for wireless sensor networks (WSNs) to extend network lifetime. In order to achieve reliable data transmission in WSNs, energy efficient routing protocol is a crucial issue in extending the network lifetime of a network. However, traditional routing protocols usually propagate throughout the whole network to discover a reliable route or employ some cluster heads to undertake data transmission for other nodes, which both require large amount energy consumption. In this paper, to maximize the network lifetime of the WSN, we propose a novel energy efficient region source routing protocol (referred to ER-SR). In ER-SR, a distributed energy region algorithm is proposed to select the nodes with high residual energy in the network as source routing node dynamically. Then, the source routing nodes calculate the optimal source routing path for each common node, which enables partial nodes to participate in the routing process and balances the energy consumption of sensor nodes. Furthermore, to minimize the energy consumption of data transmission, we propose an effective distance-based ant colony optimization algorithm to search the global optimal transmission path for each node. Simulation results demonstrate that ER-SR exhibits higher energy efficiency, and has moderate performance improvements on network lifetime, packet delivery ratio, and delivery delay, compared with other routing protocols in WSNs.

An Integrated Fast Data Transmission Scheme Based on Network Coding

Network coding has been investigated to improve the data transmission performance of wireless sensor networks (WSNs), and reduce data redundancy in data centers. In recent years, the amount of sensor data transmitted to data centers for analysis has increased dramatically, and traditional transmission schemes have encountered problems due to low transmission efficiency under conditions with massive data transmission. These problems are caused by the use of multiple codecs (including several coding and recoding codecs at the sensor nodes, one for decoding at the data gateway, one for coding for redundant storage and one for decoding to obtain original sensor data) and inefficient decoding processes. To solve these problems, we present an integrated fast data transmission scheme based on network coding. We consider the data transmission of WSNs and storage at data centers simultaneously so that codecs at data gateways can be avoided, and the encoded data can be stored directly in data centers. Furthermore, we design a gradient constraint flooding protocol based on network coding for data-intensive WSNs, and implement a fast, parallel decoding scheme for the data center. Our experimental results show that our scheme has the better performance in terms of rapid data delivery and decoding speed than traditional schemes.