Communication In Wireless Sensor Networks Research Articles

Path Planning and Secure Routing in wireless sensor networks for Multi-Constrained Quality of Service

In recent decades wireless sensor networks (WSN) are becoming important and playing important role in IoT applications. But because of limited battery power and the small size of sensor nodes, energy efficiency is the key parameter that is to be efficiently utilized. In this paper, Path Planning and Secured Routing for Multi-Constrained Quality of Service (QoS) in the WSN algorithm are proposed. The projected system can distribute the workload over alternate paths so as to keep away from congestion and minimize travel costs. It will guarantee reliable routing with less bandwidth and request a high packet delivery ratio since it keeps away from packet loss. WSN could likewise be impacted by attacks on routing resulting in altering messages and routes which can have an adverse effect on QoS parameters. The projected calculation can distribute the workload over alternate methods. Accordingly, we tend to get routing and path planning subject to multiple Quality of Service constraints for secure WSN communication.

ESPAR array design for the UHF RFID wireless sensor communication system

SummaryIn this paper, in order to improve the received signal strength (RSS) and signal quality, three arrays of electronically steerable parasitic array radiator (ESPAR) antennas are suggested for the ultra‐high frequency (UHF) radio frequency identification (RFID) communication and sensing system applications. Instead of the single antenna, the array antennas have recently been widely used in many communication systems because of their peak gains, better radiation patterns, and higher radiation efficiency. Also, there are some important issues to use the antenna array like high data rates in wireless communication systems and to better understand the many targets or sensors. In this article, a wireless sensor network (WSN) is being investigated to overcome multipath fading and interference by antenna nulling technology that can be achieved through beam control ESPAR array antennas. The proposed ESPAR array antennas exhibit higher gains like 9.63, 10.2, and 12 dBi and proper radiation patterns from one array to another. Moreover, we investigate the mutual coupling effect on the performance of array antennas with different spacing (0.5λ, 0.75λ, λ) and configurations. It is found that the worst mutual coupling reduced by −28 to −34 dB for 2 × 2 array, −3 to −43 dB for 2 × 3 array, and finally −42 dB to −51 dB due to the antenna spacing from 0.5λ to λ. Thus, these suggested antennas could effectively be applied in the WSN communication systems, internet of things (IoT) networks, and massive wireless and backscatter communication systems.

Identification and Mitigation of the Selfish Node and Its Behavior in WMN

In Wireless Sensor Network (WSN) communication, every node transmits data packets to further nodes and spend its resources like battery power, CPU time and memory. In ideal situation all the nodes forward packets to other nodes according to their requirements .Presence of selfish nodes is a very big issue in WSNs. A selfish node doesn't forward packets and utilize to its own profit but it is hesitating using personal resources for others. If such activities occurs within most of the nodes in the network, the network is disrupted. Selfish behavior detection and punishment is an essential requirement in wireless sensor networks. In our paper we have described an efficient algorithm for detection and punishment of a selfish node and the necessary action to be taken if the node is a critical node.

DR‐NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

SummaryInternet of Things (IoT) has got significant popularity among the researchers' community as they have been applied in numerous application domains. Most of the IoT applications are implemented with the help of wireless sensor networks (WSNs). These WSNs use different sensor nodes with a limited battery power supply. Hence, the energy of the sensor node is considered as one of the primary constraints of WSN. Besides, data communication in WSN dissipates more energy than processing the data. In most WSNs applications, the sensed data generated from the same location sensor nodes are identical or time‐series/periodical data. This redundant data transmission leads to more energy consumption. To reduce the energy consumption, a data reduction strategy using neural adaptation phenomenon (DR‐NAP) has been proposed to decrease the communication energy in routing data to the BS in WSN. The neural adaptation phenomenon has been utilized for designing a simple data reduction scheme to decrease the amount of data transmitted. In this way, the sensor node energy is saved and the lifetime of the network is enhanced. The proposed approach has been implanted in the existing gravitational search algorithm (GSA)‐based clustered routing for WSN. The sensed data are transmitted to CH and BS using DR‐NAP. Real sensor data from the Intel Berkeley Research lab have been used for conducting the experiments. The experiment results show 47.82% and 51.96% of improvement in network lifetime when compared with GSA‐based clustered routing and clustering scheme using Canada Geese Migration Principle (CS‐CGMP) for routing, respectively.

SCDAP –secured cluster based data aggregation protocol for energy efficient communication in wireless sensor networks

A network of real time devices that can sense and transmit the information from the deployed environment by using multi hop communication is called as Wireless Sensor Network (WSNs). Despite the rapid advancement of WSN, where an increasing number of physical devices so called as sensors nodes are connected with each other, providing the improved security with optimized energy consumption during data transmission, communication and computation remains huge challenge. In wireless sensor networks, numerous sensor nodes are deployed in the physical environment to sense and collect the required information from the given environment. The sensed information is needed to be transmitted from the nodes to the control station in an energy efficient manner. Data aggregation is one kind of techniques which will optimize the energy usage in wireless sensor networks during the data transmission. In data aggregation, the unnecessary data is removed which will significantly reduce energy of the nodes during data transmission. However, collected data during the data aggregation should be completely protected and there are various threats that can be launched by the intruders to carry out unauthorised data access and can cause threat to the integrity of the network. Therefore, ensuring data security during the data aggregation process is very important and essential for the security of the network. In this paper, a Secure Cluster based Data Aggregation Protocol (SCDAP) have been proposed to provide better security through secure authentication and verification process, and to reduce overall energy consumption of the network by implementing secure clustering process to eliminate the redundant data in the network. Moreover, the proposed system is more efficient in generating public and private keys for effective and secure data transmission and verification process. The proposed system is experimentally tested in NS-3 tool and proves that the proposed system reduces high energy consumption, computational and communicational cost, end-to-end delay and improves the packet delivery ratio. Moreover, the proposed system provides better security in the network when compared to other existing systems during the data aggregation.

A Performance Analysis of Wireless Sensor Networks in Recent Years

Wireless Sensor networks (WSNs) have become one of the most interesting areas of research in the past few years. Undoubtedly, wireless transmission techniques are used for all node-to-node communication. Additionally, because wireless sensor networks are self- organized, independent of fixed infrastructure, and their topologies vary on a regular basis, broadcasting is the default method of communication in WSNs. But a handful of sensor nodes in long-lasting networks have dynamically accomplished it. They are autonomous systems that share common sensors, centralized nodes, and a back-end server. The real-time independent sensor data is initially transmitted by the common sensors, and finally, the back- end server receives the sensed data to do additional process and performance analysis. Wireless sensor networks (WSNs) are hybrid nodes with wireless communication interfaces, data sensing, processing, and storage capabilities that are rapidly expanding in number. It is used for many different things in daily life, including tracking vehicles, keeping an eye out for fires in the forest, finding and tracking soldiers for military usage, keeping an eye on the oceans and seas, and creating intelligent places.

Adaptive Compressed Sampling Based on EMD for Wireless Sensor Networks

Image acquisition and communication in wireless sensor networks (WSNs) are key issues for some applications that require image sensing. Lowering the sampling rate and reducing the amount of data to be transmitted can greatly save hardware costs and power consumption to overcome communication bottlenecks. To serve this purpose, block compressed sampling (CS) can be used. For block CS, the sparsity of the signal to be sampled is an important parameter. On the sampling side of sensor nodes, we cannot obtain the complete digital signal. Therefore, it is challenging to perform adaptive rate sampling for block CS. In this article, a novel rate adaptive allocation block CS scheme based on empirical mode decomposition (EMD) is proposed. First, we calculate an energy matrix of measurement results (EMMR) and perform EMD on EMMR. Considering the high computational complexity of 2-D EMD, which will increase the burden on the sampling side, we propose a 1-D EMD based on zigzag scanning to decompose EMMR. Then, we can obtain an energy distribution map (EDM) of high-frequency components of EMMR. Finally, the adaptive allocation of sampling rate is carried out according to the EDM of high-frequency components. On the reconstruction side of WSN, we propose a reconstruction algorithm based on residual measurement results, which can further improve the reconstruction accuracy of images. The experiment results show that the proposed scheme has improved the accuracy in general compared with the previous schemes, and the subjective quality of the reconstructed images is also improved.

Massive Data Storage Solution for IoT Devices Using Blockchain Technologies.

The Internet of Things (IoT) concept involves connecting devices to the internet and forming a network of objects that can collect information from the environment without human intervention. Although the IoT concept offers some advantages, it also has some issues that are associated with cyber security risks, such as the lack of detection of malicious wireless sensor network (WSN) nodes, lack of fault tolerance, weak authorization, and authentication of nodes, and the insecure management of received data from IoT devices. Considering the cybersecurity issues of IoT devices, there is an urgent need of finding new solutions that can increase the security level of WSNs. One issue that needs attention is the secure management and data storage for IoT devices. Most of the current solutions are based on systems that operate in a centralized manner, ecosystems that are easy to tamper with and provide no records regarding the traceability of the data collected from the sensors. In this paper, we propose an architecture based on blockchain technology for securing and managing data collected from IoT devices. By implementing blockchain technology, we provide a distributed data storage architecture, thus eliminating the need for a centralized network topology using blockchain advantages such as immutability, decentralization, distributivity, enhanced security, transparency, instant traceability, and increased efficiency through automation. From the obtained results, the proposed architecture ensures a high level of performance and can be used as a scalable, massive data storage solution for IoT devices using blockchain technologies. New WSN communication protocols can be easily enrolled in our data storage blockchain architecture without the need for retrofitting, as our system does not depend on any specific communication protocol and can be applied to any IoT application.

Classification of Secure Routing Protocols in Wireless Sensor Networks

A wireless sensor network (WSN) is a collection of wirelessly connected multifunction sensor devices (referred to as wireless sensor nodes) in an area that requires sensing. In WSNs, wireless sensor nodes have a short transmission range, and processing capacity, storage, and power supply to the node are also limited. In addition, WSNs often include a significant number of sensor nodes, deployed in a large area to meet the requirements set forth, and communication in WSNs must be through multi-hop communication connections. Therefore, the secure routing protocols (SRPs) in WSNs are responsible for finding and maintaining secure and reliable connection routes and are especially energy-efficient (because the wireless sensor node is limited in terms of the power supply). Therefore, energy-efficient routing, as well as secure communication and data transmission between wireless sensor nodes are fundamental challenges for providing security services in WSNs. Currently, many energy-efficient and SRPs in WSNs have been proposed. In this paper, we synthesize the classification and arrangement of energy-efficient and SRPs, as well as provide a method to calculate attack probability (AP) for secure routing in WSN.

An overview of NFC Technology for Wireless Communication

This article discusses about wireless communication technologies such as IEEE 802.15.4, Wireless Sensor Network (WSN), Ultra-High Frequency (UHF) and Near Field Communication (NFC) technologies are described. The part of industry and everyday life could be significantly impacted by Wireless Sensor Networks (WSN). A wireless sensor network (WSN) is a collection of sensor nodes that communicate with one another using wireless technologies. These nodes gather data and send it to the gateway across the Internet, the informal cloud. In a WSN, node-to-node communication may be multi-hop or direct. Every new concept or technology attempts to be integrated into the WSN in order to increase efficiency, improve user experience, and consume less power. Near Field Communications (NFC), a type of wireless networking technology allows to establish simple, secure and interactive communication. iPack is a technology that focuses on integrating NFC into pre-existing systems to create a Wireless Sensor Network (WSN) that supports NFC. Furthermore, data from a sensor node can be transferred to devices with a single touch by using this method. NFC with WSN is a single hop communication. The NFC interface also offers a safe wireless connection.

PERFORMANCE ANALYSIS OF GMSK-BASED COOPERATIVE COMMUNICATION IN WIRELESS SENSOR NETWORKS

An efficacious energy model based on Gaussian minimum shift keying (GMSK) for cooperative communication is proposed in this paper. The influence of the rate at which data are transmitted, distance, severity of fading, and quantity of participating nodes on the energy expended for communication by the proposed model is investigated through simulations. The influence of the rate at which data are transmitted and the quantity of participating nodes on the energy expended in circuitry is also studied. Through the simulations, it is apparent that the energy consumed by the circuit dominates the energy consumed for transmission for all of the transmission data rates, path loss exponents, bit error rates, and transmission distances considered.

Enhanced Security with Improved Defensive Routing Mechanism in Wireless Sensor Networks

In recent scenario of Wireless Sensor Networks (WSNs), there are many application developed for handling sensitive and private data such as military information, surveillance data, tracking, etc. Hence, the sensor nodes of WSNs are distributed in an intimidating region, which is non-rigid to attacks. The recent research domains of WSN deal with models to handle the WSN communications against malicious attacks and threats. In traditional models, the solution has been made for defending the networks, only to specific attacks. However, in real-time applications, the kind of attack that is launched by the adversary is not known. Additionally, on developing a security mechanism for WSN, the resource constraints of sensor nodes are also to be considered. With that note, this paper presents an Enhanced Security Model with Improved Defensive Routing Mechanism (IDRM) for defending the sensor network from various attacks. Moreover, for efficient model design, the work includes the part of feature evaluation of some general attacks of WSNs. The IDRM also includes determination of optimal secure paths and Node security for secure routing operations. The performance of the proposed model is evaluated with respect to several factors; it is found that the model has achieved better security levels and is efficient than other existing models in WSN communications. It is proven that the proposed IDRM produces 74% of PDR in average and a minimized packet drop of 38% when comparing with the existing works.

Layered routing algorithm for wireless sensor networks based on energy balance

Aiming at the shortcomings of traditional LEACH routing protocol in wireless sensor network (WSN) data transmission applications, such as high total energy consumption, low residual energy and short network life, a hierarchical routing algorithm based on energy balance is proposed. This algorithm is based on the energy consumption model of WSN communication, and adopts the non-uniform clustering algorithm to introduce the threshold. According to the relationship between the distance between cluster head node and sink node and the threshold, the implementation method of network communication is selected. In addition, a simple correlation multi-path route is designed to realise the multi hop communication between clusters. By considering the communication cost and the residual energy value of nodes, the hierarchical route with balanced energy consumption is realised. Experimental results show that the algorithm has obvious advantages in balancing network energy consumption and prolonging network lifetime.

An Intrusion Detection Using Machine Learning Algorithm Multi-Layer Perceptron (MlP): A Classification Enhancement in Wireless Sensor Network (WSN)

During several decades, there has been a meteoric rise in the development and use of cutting-edge technology. The Wireless Sensor Network (WSN) is a groundbreaking innovation that relies on a vast network of individual sensor nodes. The sensor nodes in the network are responsible for collecting data and uploading it to the cloud. When networks with little resources are deployed harshly and without regulation, security risks occur. Since the rate at which new information is being generated is increasing at an exponential rate, WSN communication has become the most challenging and complex aspect of the field. Therefore, WSNs are insecure because of this. With so much riding on WSN applications, accuracy in replies is paramount. Technology that can swiftly and continually analyse internet data streams is essential for spotting breaches and assaults. Without categorization, it is hard to simultaneously reduce processing time while maintaining a high level of detection accuracy. This paper proposed using a Multi-Layer Perceptron (MLP) to enhance the classification accuracy of a system. The proposed method utilises a feed-forward ANN model to generate a mapping for the training and testing datasets using backpropagation. Experiments are performed to determine how well the proposed MLP works. Then, the results are compared to those obtained by using the Hoeffding adaptive tree method and the Restricted Boltzmann Machine-based Clustered-Introduction Detection System. The proposed MLP achieves 98% accuracy, which is higher than the 96.33% achieved by the RBMC-IDS and the 97% accuracy achieved by the Hoeffding adaptive tree.

An Adaptive QoS and Trust-Based Lightweight Secure Routing Algorithm for WSNs

The limited resources and low computational power of wireless sensor networks (WSNs) make them vulnerable to various security attacks. Conventional security mechanisms require too many resources to allow the reliable operation of WSNs due to their resource-constrained nature. In addition, multihop communication in WSNs creates a requirement for guaranteed Quality of Service (QoS). Therefore, providing security while maintaining QoS and energy efficiency in WSNs are important design considerations. To further increase the performance of WSNs, there is a need to overcome the energy-hole problem, which leads to poor coverage of the field of interest. An energy-hole problem is created because of using poor deployment strategies. In this article, we define a multiobjective WSN optimization problem and present a novel algorithm known as lightweight secure routing (LSR) to manage WSNs that directly addresses the multiobjective WSN optimization problem. Our LSR algorithm uses ant colony optimization (ACO), an adaptive security model based on direct and indirect trust calculations, an adaptive QoS model, a hybrid deployment model based on 2-D Gaussian and uniform distributions, and an adaptive connectivity model that uses an appropriate communicational radius to ensure high connectivity between sensor nodes to solve the multiobjective WSN optimization problem. We divide our simulation results into three analyses, namely, trust model analysis, network scalability analysis, and security risk analysis to show that LSR outperforms the existing techniques in terms of energy consumed to calculate trust values, trust values convergence, network lifetime, average routing delay, and packet delivery ratio.

Energy-Efficient Network Protocols and Resilient Data Transmission Schemes for Wireless Sensor Networks—An Experimental Survey

Wireless sensor networks (WSNs) are considerably used for various environmental sensing applications. The architecture and internal specifications of WSNs have been chosen based on the requirements of particular applications. On this basis, WSNs consist of resource (energy and memory)-limited wireless sensor nodes. WSNs initiate data communication from source to destination via physical layer management principles, channel slot scheduling principles (time division multiple access), wireless medium access control (WMAC) protocols, wireless routing protocols and application protocols. In this environment, the development of WMAC principles, routing protocols and channel allotment schemes play crucial roles in network communication phases. Consequently, these layering functions consume more energy at each sensor node, which leads to minimal network lifetime. Even though the channel management schemes, medium control protocols and routing protocols are functionally suitable, the excessive energy consumption affects the overall network performance. In this situation, energy optimization algorithms are advised to minimize the resource wastage of WSNs during regular operations (medium control and routing process). Many research works struggle to identify the optimal energy-efficient load balancing strategies to improve WSN functions. With this in mind, the proposed article has conducted a detailed literature review and notable experimental comparisons on energy-efficient MAC protocols, channel scheduling policies and energy-efficient routing protocols. To an extent, the detailed analysis over these wireless network operations helps to understand the benefits and limitations of recent research works. In the experimental section of this article, eight existing techniques are evaluated under energy optimization strategies (WMAC, channel allocation, sleep/wake protocols, integrated routing and WMAC policies, balanced routing and cooperative routing). The proposed review and the classified technical observations collected from notable recent works have been recognized as crucial contributions. The results infer the suggestions for feasible WSN communication strategies with optimal channel management policies and routing policies. Notably, the simulation results show that cross-layer or multi-layer energy optimization policies perform better than homogeneous energy optimization models.

A fuzzy based approach to enhance the lifespan of sensor network

The use of wireless sensor networks (WSNs) for data collection is widespread. The resource constraint is an important factor in WSN communications design. The issue arises naturally in WSNs as a result of uneven energy consumption caused by multi-hop routing and dynamic network models, which substantially affects network lifetime. The nodes are dispersed over distant sensing areas and are powered by finite or limited energy batteries that are difficult to replace. The energy of nodes is reduced as a result of changes in network topology or the network’s lifespan and the main intention of this research is to figure out how to make sensor networks last longer. The suggested study work focuses on a specific routing strategy for WSNs that employs the AO-star algorithm with a Fuzzy approach and link stability for extending the network lifetime. The technique chooses the optimum routing path by the sensing point to the receiving node based on how much energy is consumed, the smallest number of nodes with the shortest latency, and lower transmission loads with higher throughput. To compare the proposed strategy’s efficiency in energy consumption balancing and network lifespan enhancement, the proposed technique may achieve a 30% longer average network lifetime than the A-star algorithm.

TADR-EAODV: A trust-aware dynamic routing algorithm based on extended AODV protocol for secure communications in wireless sensor networks

Compliance with security requirements in Wireless Sensor Networks (WSNs) is known as an important phenomenon in conserving energy consumption due to its dynamic topology. Energy consumption management in WSN can be achieved through secure routing protocols. Authentication, firewall and intrusion detection, and trust management are common ways to provide security on the WSNs. Meanwhile, trust management provides better performance due to ensuring distributed security through collaboration. In this paper, a Trust-Aware Dynamic Routing algorithm based on Extended AODV protocol for secure communications in the WSN (TADR-EAODV) is proposed. TADR-EAODV considers factors such as direct trust, recommended trust, connectivity strength, energy rate and worthiness score to measure the distributed safety level of nodes in routing. We use the AODV protocol for routing work, which is extended through a multi-route routing approach. In addition, a centralized ensemble clustering for node grouping is included in TADR-EAODV, which enables clustering-based routing to enhance WSN performance. Extensive experiments have been performed in the presence of denial-of-service attacks to verify our claims. The experimental results prove that high-performance TADR-EAODV has been able to identify attackers by detecting their anomalous behavior. Besides, TADR-EAODV has improved the average packet transfer rate by 6% to 17% compared to existing state-of-the-art algorithms such as LEACH-TM, TAAO-SDTIM and TAOSC-MHR.

A Secure LEACH Protocol for Efficient CH Selection and Secure Data Communication in WSNs

Due to the applications of wireless sensor networks (WSNs) in distinct fields, like civilian and military, environmental monitoring, and target tracking, etc., it became the important research area for researchers. Therefore, an efficient organization of network topology is needed for multi-hop data aggregation based on the energy constrained WSNs with large scale deployment for making the routing task simpler, balancing the load efficiently, and enhancing the network lifetime. The low-energy adaptive clustering hierarchy (LEACH) is an architecture of application-specific protocol, which is used for WSNs. However, this LEACH protocol suffered from more energy consumption in network without considering the cluster heads (CHs) distribution on a rotation basis. In addition, the complex security mechanisms are not sufficient due to limited bandwidth and other restrictions that the sensor nodes have. Thus, it is essential to improve the energy efficiency, CH stability and secure data transmission in WSN’s, which is the main objective of this work. Motivated from these three challenges, this article proposes a stable and secure LEACH (SS-LEACH), in which a new and improved protocol of LEACH is proposed for enhancing the stability of CH and energy efficiency as it considers the nodes’ consumed energy ratio (CER) for CH selection and random number generation, here after the proposed LEACH is named as CER-LEACH. In addition, it aims to prevent the previously elected CH node and it will get another chance in the current round. This method correlates the threshold used in traditional LEACH with the energy consumption ratio of each node. Further, it also introduces a hybrid reputation-based data transmission (HRDT) scheme for secure data transmission. With the proposed CER-LEACH protocol, WSNs achieves better performance in terms of secured communication, network lifetime, and energy consumption based on the analysis of simulation results as compared to state-of-art approaches.

A Novel Optimization based Energy Efficient and Secured Routing Scheme using SRFIS-CWOSRR for Wireless Sensor Networks

Ensuring the reliable and energy efficient data routing in Wireless Sensor Networks (WSNs) is still remains one of the challenging and demanding tasks due to its dynamic architecture. For this purpose, the different types of routing methodologies and security schemes have been developed in the conventional works. However, it faced the problems related to increased network overhead, high cost consumption, reduced Quality of Service (QoS), and inefficient bandwidth utilization. The main contribution of this work is to implement an optimization based secured routing methodology for establishing an energy efficient data communication in WSNs. For clustering the nodes, the parameters such as residual energy, trust score, and mobility have been considered, which also helps to simplify the networking operations. Moreover, the outliers in the network are detected with the help of Spatial Temporal Fuzzy Inference System technique, which generates the set of inference rules based on the distance, energy, and mobility measures. Also, the Crow-Whale Optimized Secured Robin Routing (CWOSRR) is used to enable the data transmission in the network through the optimized path, which avoids the loss of information. During the simulation analysis, the results of the proposed technique is validated and compared by using various performance measures.