Communication In Wireless Sensor Networks Research Articles

DAR Model: A Novel Symmetric Key Enabled Security architecture for reliable data transfer in Wireless Sensor Networks

Security is an indispensable aspect in every transaction happening in the network transmissions. Wireless Sensor Networks are pretty vulnerable to the security attacks. Hence a highly efficient architectural model is very much essential in designing the sensor networks. Cryptographic algorithms play a vital role in providing encryption and decryption to the data being transmitted consequently with which security is offered in an elegant manner. In this paper, a reliable design comprising three pioneering algorithms enabled with symmetric key is architected for secure communication in wireless sensor networks from a node to the base station. The design involves two phases. In the former phase two algorithms which are effective in all perspectives are used for data transmission from node to cluster head and in the latter phase another proficient algorithm is used for communication between cluster head to base station. The three algorithms used are Data Encryption Standard (DES), Advanced Encryption Standard (AES) and RC4. Both block and stream cipher algorithms are used to fine tune the performance; and in addition, the data has been compressed with unprecedented techniques to reduce the burden on encryption. This led to an amazing performance in terms of security parameters.

FuzDeMa: A portable fuzzy-based decision-making tool for reliable communication in wireless underground sensor networks

The deployment and the exploitation of a Wireless Underground Sensor Network (WUSN) remain challenging because of signal attenuation in the soil and the limited battery that powers the sensor nodes. Due to the attenuation of the signal in the ground, the reception or loss of the sent data depends on the ground conditions, which can change dynamically. However, in existing WUSNs, each node sends the data collected in each round regardless of the signal attenuation. It is well demonstrated that sensor nodes consume the most energy during transmission. Obviously, transmission without receiving any data significantly reduces the lifetime of a sensor node useless. This paper presents a novel fuzzy-based decision-making solution called FuzDeMa that reduces energy consumption by anticipating data losses before transmission. To do so, FuzDeMa assesses in real time the loss or the reception of a packet according to the in-situ node's environments before its transmission and decides whether to send or not the packet based on the computed reliability. To validate the proposed approach, we embed it into a dedicated underground node called the MoleNet and realized real experimentations firstly with an existing dataset and secondly, with precision-measuring equipment to estimate the energy consumption. The results revealed the possibility of prolonging the lifetime of the sensor node by saving up to 81.7876 microjoules in a single round. Additionally, FuzDeMa shows the ability to save energy for up to 46 of additional revolutions, thus extending the life of the sensor node to 32.85% for 140 real transmission cycles. An analytical generalization of FuzDeMa is provided regardless of a specific dataset or sensor node. Thus, we provided the conditions for a random dataset to save the energy with any sensor node that implements FuzDeMa during transmissions.

Optical Communication and Positioning Convergence for Flexible Underwater Wireless Sensor Network

This paper presents a novel scheme based on underwater optical wireless communication and positioning (UOWC-UOWP) for an underwater wireless sensor network (UWSN). A dual-hop system is adopted to extend the limited coverage area of the UWSN with mobile nodes, consisting of a grade-index plastic optical fiber (GI-POF) link and a wireless link. Specifically, the mini-LED offers high-speed and flexible uplink transmission and the high-power LED enables both downlink transmission and positioning. The time frame design and code division multiplexing access (CDMA) support multi-user signal transmission. Proof-of-concept experiments with GI-POF and wireless link demonstrate the feasibility of the proposed scheme, which offers full-duplex communication, high-precise positioning and extended distance. To the best of our knowledge, the UOWC-UOWP convergent system is proposed for the first time. It has great potential to support high-capacity transmission between mobile nodes for future underwater transmission scenarios.

An Overview and Comparison of Wireless Technologies and Standards for Industrial Wireless Sensor Networks

The tremendous research and development has provided a number of wireless technologies and standards used for communication in Industrial Wireless Sensor Networks. The primary reason for writing this article is to study all available Wireless technologies and standards and to identify their area of usage, study different parameters like power consumption, functionality, communication range, transmission speed, data type etc. Another important and main reason of this article is to select best suitable technology for our next research. Various parameters of established technologies like Wireless HART, Zigbee, ISA 100.11a and Dash7 have been compared using a comparison table.

An intelligent routing algorithm for energy prediction of 6G-powered wireless sensor networks

With the rapid development of the Internet and computers, large-scale network applications have become a research hotspot in the communication industry, engineering and other fields. Building a new wireless sensor network and intelligent communication transmission system can promote the further upgrading and improvement of the capability industry, which is also a subject that the current network academia and communication academia are trying to explore. Based on the above background environment, this paper proposes the research on energy prediction and intelligent routing algorithm of wireless sensor networks in the development of sixth generation (6G) networks. A node coverage and scheduling algorithm based on energy prediction is proposed for the overlap and non-uniformity of regions in network transmission. Secondly, the problem of energy efficient utilization in wireless sensor networks is solved, and the clustering algorithm is used to predict the use process. The working state model of network sensor is established, and the energy parameters are added to the actual prediction calculation as influencing factors. Finally, in the intelligent routing mechanism, clustering mechanism and particle swarm optimization algorithm are used to improve the path selection, so as to improve the fault tolerance of wireless network transmission in the face of large amounts of dynamic data. The research results show that the optimization and intelligent routing algorithm based on energy prediction for wireless sensor networks can prolong the service life cycle and ensure the network transmission efficiency and coverage in a long work cycle. It can ensure the energy supply of the sensor and prolong the service time through the balanced node scheduling.

Energy-Aware Reliable Medium Access Control Protocol for Energy-Efficient and Reliable Data Communication in Wireless Sensor Networks

Energy-Aware Reliable Medium Access Control Protocol for Energy-Efficient and Reliable Data Communication in Wireless Sensor Networks

Lightweight key distribution for secured and energy efficient communication in wireless sensor network: An optimization assisted model

Lightweight key distribution for secured and energy efficient communication in wireless sensor network: An optimization assisted model

A multipath routing protocol for secure energy efficient communication in Wireless Sensor Networks

A Wireless Sensor Network (WSN) is comprised of a number of sensor nodes (SNs) that are randomly placed in an open, harsh environment for many applications. Due to the resource-constrained nature of SNs and hostile deployment environments, energy efficiency and security are considered two key factors in designing WSN routing protocols. This paper proposes an Energy Efficient Secure Multipath (EESM) routing protocol to securely construct efficient routes and transmit data packets between SNs and the base station (BS). EESM achieves energy efficiency through minimal task allocation among SNs whereas all computation-intensive tasks such as network information collection, routing table generation, and network maintenance are performed by the BS. The proposed protocol incorporates lightweight security mechanisms including a one-way hash chain, message authentication code, encryption, and clique-based coordinator selection and monitoring schemes to defend against numerous security attacks. Simulation results show that EESM can successfully detect and protect the network against various security attacks such as replay attacks, sybil attacks, sinkhole attacks, spoofing attacks, compromised node attacks, and so on. In terms of energy efficiency, the proposed protocol achieves an up to 37% increase in network lifetime and a 6% increase in throughput over Secure and Energy Efficient Multipath (SEEM) routing, Secure and Reliable Multipath Routing (SRMR), and Reliable and Multipath Encounter Routing (RMER) protocols. The paper implements the protocol in a real environment using Arduino motes to analyze security overheads and network setup time.

A novel chain‐based clustering for green communication in wireless sensor network

SummaryThe rapid growth of the Internet of Things (IoT) creates a high requirement for data collected through wireless sensor networks (WSNs), resulting in a lot of emphasis on WSN data collecting in recent decades. However, the resource‐constrained nature of sensor devices exerts heavy constraints for acquiring the optimal network performance. To resolve this concern, this paper proposes the Chain‐based Energy‐Efficient Clustering (CBEEC) Routing Protocol that considers nodes of two heterogeneous levels of energy (normal level and advanced level). The number of advanced nodes in CBEEC is analytically determined and hence are analytically allocated. However, normal nodes are stochastically deployed in the vicinity of advanced nodes. The data transmission is performed among the advanced nodes in the form of chain and from there it is forwarded to base station (BS). Consequently, it preserves immense amount of energy for the network. The performance of CBEEC is empirically investigated with benchmarks of different performance metrics and simulation outcomes showing that the CBEEC outperforms state‐of‐the‐art routing protocols.

Age Prediction for Energy-Aware Communication in WSN Using Hybrid Optimization-Enabled Deep Belief Network

To perceive the data utilizing sensor nodes, wireless sensor network (WSN) consists of several nodes connected to a wireless channel. However, the sink node, also known as a base station (BS), provides power to the WSN and acts as an access node for a number of the network’s sensor devices. Weather monitoring, field surveillance, and the collection of meteorological data are just a few of the various uses for WSN. The energy of each node directly affects how long a wireless network will last. So, to increase the lifespan of WSN, effective routing is required. Using the suggested Taylor sea lion optimization-based deep belief network (TSLnO-based DBN), the ultimate purpose of this research is to build a method for energy-aware communication in WSN. In the setup stage, cluster head (CH) is chosen using a hybrid optimization technique called ant lion whale optimization (ALWO), which is created by fusing the whale optimization algorithm (WOA) and ant lion optimizer (ALO). It is important to note that CH’s selection criteria are solely based on fitness factors such as energy and distance. The second phase, known as the steady state step, is when the updating of energy and trust takes place. In the prediction phase, the network classifier is trained using a newly created optimization method called TSLnO, and the age of neighbor nodes is predicted by estimating the energy of neighbors using DBN. By combining the Taylor Series and the sea lion optimization (SLnO) method, the proposed TSLnO is produced. The communication/route discovery phase, which occurs in the fourth phase, is where the path through nearby nodes is chosen. The maintenance phase of the route is the fifth phase.

A Deep MARL-Based Power-Management Strategy for Improving the Fair Reuse of UWSNs

Providing qualified and fair communications for underwater wireless sensor networks (UWSNs) has garnered considerable interest in light of scarce resources and dynamic channel conditions. Fairness is critical in various situations, including emergency communications in resource-constrained underwater networks that balance load and energy amongst nodes to optimize network performance. Existing solutions for fair communications, on the other hand, frequently come at the expense of network capacity. This paper focuses on the power management strategy that jointly optimizes the reuse, fairness, and capacity of UWSNs while also proposing a new metric for fair spatial reuse in networks: the fair reuse index. We observe that the fair reuse index for UWSNs is strongly reliant on the network density, channel conditions, and application requirements. As a result, UWSNs commonly exhibit load imbalance and struggle to meet required network lifetimes. Towards this end, we propose DMPM, a Deep Multi-agent reinforcement learning-based Power Management strategy for increasing the fair reuse of UWSNs. DMPM strives to maximize the network’s fair reuse while allowing for gentle network capacity decrease. In two representative communication scenarios, numerical results demonstrate that DMPM achieves a significantly better trade-off between network capacity and fair reuse than baseline techniques. We also construct three reward functions for DMPM and discuss how different reward functions affect node behaviors. Delivery delays of different models are discussed. We hope that the work provided in this study will prove to be invaluable in the design and optimization of UWSNs.

Terminal Access Method of Power Equipment Based on eSIM in WSN Environment

To ensure the integration of wireless sensor network and broadband wireless communication network, we establish a new generation of power IoTs information communication system for smart grid, and propose a distribution automation terminal solution based on eSIM card. An adaptive access algorithm based on multi logic eSIM priority, and a WSN based power acquisition system architecture, are also put forward. Then, according to the statistical analysis results of service arrival, the dialing and location information are integrated into one module. Through terminal classification and mobile modeling, a remote management mechanism based on EUICC is finally established. The system simulation test results show that the strategy adopted in this article can reduce the terminal access blocking rate in heterogeneous network environment, and the support of eSIM in WSN environment increases the integration of power equipment.

Security In Wireless Sensor Networks Based On Lightweight Algorithms : An Effective Survey

At the level of both individuals and companies, Wireless Sensor Networks (WSNs) get a wide range of applications and uses. Sensors are used in a wide range of industries, including agriculture, transportation, health, and many more. Many technologies, such as wireless communication protocols, the Internet of Things, cloud computing, mobile computing, and other emerging technologies, are connected to the usage of sensors. In many circumstances, this contact necessitates the transmission of crucial data, necessitating the need to protect that data from potential threats. However, as the WSN components often have constrained computation and power capabilities, protecting the communication in WSNs comes at a significant performance penalty. Due to the massive calculations required by conventional public-key and secret encryption methods, information security in this limited context calls for light encryption techniques. In many applications involving sensor networks, security is a crucial concern. On the basis of traditional cryptography, a number of security procedures are created for wireless sensor networks. Some symmetric-key encryption techniques used in sensor network setups include AES, RC5, SkipJack, and XXTEA. These algorithms do, however, have several flaws of their own, including being susceptible to chosen-plaintext assault, brute force attack, and computational complexity.

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.