Communication In Sensor Networks Research Articles

Intelligent multi-agent model for energy-efficient communication in wireless sensor networks

The research addresses energy consumption, latency, and network reliability challenges in wireless sensor network communication, especially in military security applications. A multi-agent context-aware model employing the belief-desire-intention (BDI) reasoning mechanism is proposed. This model utilizes a semantic knowledge-based intelligent reasoning network to monitor suspicious activities within a prohibited zone, generating alerts. Additionally, a BDI intelligent multi-level data transmission routing algorithm is proposed to optimize energy consumption constraints and enhance energy-awareness among nodes. The energy optimization analysis involves the Energy Percent Dataset, showcasing the efficiency of four wireless sensor network techniques (E-FEERP, GTEB, HHO-UCRA, EEIMWSN) in maintaining high energy levels. E-FEERP consistently exhibits superior energy efficiency (93 to 98%), emphasizing its effectiveness. The Energy Consumption Dataset provides insights into the joule measurements of energy consumption for each technique, highlighting their diverse energy efficiency characteristics. Latency measurements are presented for four techniques within a fixed transmission range of 5000 m. E-FEERP demonstrates latency ranging from 3.0 to 4.0 s, while multi-hop latency values range from 2.7 to 2.9 s. These values provide valuable insights into the performance characteristics of each technique under specified conditions. The Packet Delivery Ratio (PDR) dataset reveals the consistent performance of the techniques in maintaining successful packet delivery within the specified transmission range. E-FEERP achieves PDR values between 89.5 and 92.3%, demonstrating its reliability. The Packet Received Data further illustrates the efficiency of each technique in receiving transmitted packets. Moreover the network lifetime results show E-FEERP consistently improving from 2550 s to round 925. GTEB and HHO-UCRA exhibit fluctuations around 3100 and 3600 s, indicating variable performance. In contrast, EEIMWSN consistently improves from round 1250 to 4500 s.

Efficient key distribution for secure and energy-optimized communication in wireless sensor network using bioinspired algorithms

Wireless Sensor Networks (WSNs) play a major part in numerous applications such as smart agriculture, healthcare, and environmental monitoring. Safeguarding protected communication in this network is dominant. Securing data transmission in WSNs needs a strong key distribution device to defend against malicious attacks as well as illegal access. Traditional techniques like pre-shared or centralized key management are often unreasonable owing to resource limitations, particularly in large-scale sensor systems. To overcome this challenge, a lightweight key distribution technique is employed for safeguarding the security and privacy of data transmission streamlining processes decreasing computational overhead as well as energy consumption. By optimizing and simplifying key distribution devices, we propose to improve the complete efficacy and trustworthiness of WSNs that aid safe communication while preserving valuable energy resources. Therefore, this article designs an Efficient Key Distribution for Secure and Energy-Optimized Communication using Bioinspired Algorithms (EKD-SOCBA) for WSN. The purpose of the EKD-SOCBA technique is to accomplish security and energy efficiency in WSNs. Initially, the EKD-SOCBA technique applies a golden jackal optimization (GJO) based clustering approach to cluster the nodes and select cluster heads (CHs). Also, a lightweight Dynamic Step-wise Tiny Encryption Algorithm (DS-TEA) is applied to secure data transmission in the network. Finally, a lightweight key management phase is employed to protect the encryption key and decrease energy utilization and overhead costs. To exhibit the enhanced act of the EKD-SOCBA model, a comprehensive set of imitations was involved. Extensive results stated enhanced presentation of EKD-SOCBA methodology over other models on WSN.

The Evolution of Wireless Sensor Networks through Smart Radios for Energy Efficiency

This article investigates the significant influence of smart radios on the energy efficiency of Wireless Sensor Networks (WSNs). It explores the incorporation of intelligent radios as a crucial element to enhance WSNs’ sustainability, providing a novel approach to tackle energy-related challenges. Smart radios are essential for prolonging the lifespan of sensor devices and reducing the environmental effect of WSNs by autonomously adjusting communication protocols and optimizing energy consumption. This paper also highlights the differences between 5G and 6G technologies within the WSNs framework. While 5G brought improvements in data speed and connectivity, 6G represents a significant progress by prioritizing energy efficiency as a fundamental goal. This shift represents a fundamental change, with a primary focus on achieving extremely low energy consumption and ensuring the sustainable operation of WSNs. The paper examines crucial technological factors enabling 6G to outperform its predecessor, establishing it as a revolutionary force in the field of wireless communication for sensor networks. This research illuminates the crucial function performed by smart radios in connecting the desire for energy efficiency with the changing environment of wireless sensor networks.

Retracted: Optimization Distribution Method of Computer Sensor Network Communication Based on the Linear Planning Model

Retracted: Optimization Distribution Method of Computer Sensor Network Communication Based on the Linear Planning Model

Develop the ubiquitous computing wearable IoT devices using IoT-distributed framework

Body Area Sensor Network (BASN) communication methods meet clients' multi-level requirements through Wearable Internet of Things (WIoT) systems. Transparency at management levels, heterogeneous support, and distributed communication to users are requirements of the PCS. Providing essential functions is a serious problem. A flexible Ubiquitous Computing (UC) architecture presented in this study is used to improve the reliability of end-user communication in the WIoT-based health sensor approach. According to this method, demand and sharing variables provide the foundation for the evaluation of resource allocation through recurrent learning. A proposed method could be used to implement end-user mobility management on WIoT healthcare sensors for data transmission, resource allocation and sharing. To show the integrity of the approach, some parameters were used in the actual evaluation and performance predictions. In the ubiquitous ecosystem, the uninterrupted flow was guaranteed to reduce the likelihood of a request being blocked. Memory control to density assignment at the framework level through storage management helps reduce backlogs and failures when allocating resources. The proposed approach enhances storage utilization, bandwidth, and request management besides lowering connection speed, backlogs, and request failure compared to the existing systems.

Enhanced Authentication Scheme for Mobility Model in Medical Wireless Sensor Networks

The advent of wireless sensor networks has brought significant advancements in healthcare, enabling remote interactions between medical professionals and patients. However, ensuring the security of communication in Medical Wireless Sensor Networks (WSNs) poses different challenges. To address this, this paper introduces a novel authentication framework designed for doctors and patients. The proposed mechanism incorporates essential features such as mutual authentication, anonymity, and data integrity, safeguarding the Medical Wireless Sensor Networks (MWSN). Symmetric encryption techniques are employed to maintain the overall security of the system.

AQND: An asymmetric quorum-based neighbor discovery protocol for reducing delay in sensor based systems

Neighbor discovery is basic for Wireless Sensor Networks (WSNs) communication, which is the key to network performance. Since sensor nodes were powered by battery, sleep/active rotation was widely adopted to save energy, which led to the neighbor discovery problem. Many timely neighbor discovery protocols are proposed for wake-up scheduling to expedite the discovery and data routing while saving energy. In this paper, an asymmetric quorum-based neighbor discovery (AQND) protocol is proposed to reduce the delay of neighbor discovery and data routing while improving the energy utilization and maintaining a high lifetime. According to our theoretical analysis, the proposed AQND protocol outperforms previous strategies in main performance indicators such as reducing the average relative error of duty cycle, the maximum neighbor discovery delay and the end-to-end discovery delay while improving the energy utilization ratio. In addition, using the proposed AQND protocol to improve the above network performances doesn’t reduce lifetime. Maintaining the end-to-end delay consistent with the previous strategies, the lifetime of network can be improved.

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.

Distributed observers for LTV systems: A distributed constructibility gramian based approach

The paper addresses the problem of designing distributed observers for discrete linear time-varying (LTV) systems with distributed sensor nodes. It is shown, under the conditions of collective observability, strong connectivity of the sensor communication network, and invertibility of the state transition matrix, that the resulting observer yields exponential stability of the estimation errors with a pre-defined convergence rate and, in certain situations, requires the exchange of fewer data than other methods. It is shown that for linear time-invariant (LTI) systems this method yields fixed gains that can be computed in a few steps of a distributed algorithm with the underlying communication network. A design example is given where the asymptotic performance of the proposed observer is shown to be similar to that obtained using a distributed Kalman filtering approach.

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 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.

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.

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.

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.

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.