Protocol For Wireless Sensor Networks Research Articles

A Review on Energy and Latency Efficient Routing Protocol Design for Wireless Sensor Networks

Wireless sensor networks (WSNs) have been utilized by various industries, such as disaster management, the chemical and heavy industries, marine research, and space exploration. One of the primary challenges faced by wireless sensor networks is their limited network lifetime. Several techniques have been devised to extend the duration of network operation. This proposed method introduces a threshold-based algorithm to minimize the amount of data that needs to be transferred. In this approach, the selection of cluster heads and their sizes is not fixed. Instead, they are dynamically determined at the beginning of each iteration. The design of routing algorithms for wireless sensor networks faces three main challenges: lowering the rate at which the average node energy declines, minimizing the number of dead nodes, and eventually prolonging the network's lifetime. This paper provides a thorough examination of efficient routing protocols for wireless sensor networks with the goal of improving network longevity. Keywords: Efficient Routing, WSN Clustering, Network Latency, Network Lifetime.

Elliptic curve encryption-based energy-efficient secured ACO routing protocol for wireless sensor networks

Elliptic curve encryption-based energy-efficient secured ACO routing protocol for wireless sensor networks

Energy efficient data dissemination in wireless sensor network enabled IoT using domain‐adaptive message passing graph neural network

SummaryIn the past few years, restricted wireless sensor networks (WSNs) enabled the Internet of Things (IoT) have attracted significant attention and expansion to enhance service delivery and resource efficiency. Dissemination is a service offered by WSN that uses radio transmission and over‐the‐air programming for updating the deployed sensor nodes through online. The centralized data dissemination methods are replaced by the distributed approaches because they affect the drawbacks of a single point of failure, no scalability, and insecurity. Therefore, an Energy Efficient Protocol for Data Dissemination in Wireless Sensor network‐enabled IoT using Domain‐Adaptive Message Passing Graph Neural Network (EEP‐WSN‐IoT‐DMPGNN) is proposed in this paper. The nodes are formed as clusters utilizing the Deep Fuzzy Curriculum Clustering (DFCC) technique that rewards nodes belonging to a given cluster. By using the Crayfish Optimization Algorithm (COA), the Cluster Head (CH) selection optimally chose the ideal CH and satisfies the multiple objective functions, such as energy, delay, traffic density, and distance. Afterward, domain‐adaptive Message Passing Graph Neural Network (DMPGNN) based routing protocol is developed, the input given to the routing protocol includes a sink, action history, future node, and maximum‐distance node, which attains enhanced data transfer in the chosen path. The proposed technique attains a lower no. of dead nodes, lower energy consumption, and higher Network Lifetime while analyzed with existing techniques, such as routing technique depending on deep learning for effectual data transmission in 5G WSN communication (DL‐RPDT‐WSN), Reinforcement‐Learning base energy effectual optimized routing protocol in WSN (RL‐EERP‐WSN), and Energy‐efficient intellectual routing method for IoT‐enabled WSN (EIR‐IoT‐WSN), respectively.

Design and Development of a Hybrid Cooperative- Based Routing Protocol avoiding the void nodes in WSNs using the Concepts of Minimum Energy Consumption with good Data Security features

This paper presents a novel cooperative-based routing protocol designed for underwater Wireless Sensor Network Cloud Applications (uWSNCA). The protocol aims to minimize energy consumption by avoiding void nodes, which are areas without sensor coverage. The proposed approach consists of two main steps: first, avoiding void nodes using an adaptive hop-by-hop vector method, and second, applying a cooperative rule-based adaptive hop-by-hop vector method to create a hybrid algorithm that is more efficient than existing approaches, such as the watch-dog protocol. The research focuses on developing an energy-efficient distributed cooperative routing protocol for wireless sensor networks, specifically tailored for cooperation-based uWSNCA. This is achieved by preventing data packets from being forwarded through void nodes. The proposed routing protocol utilizes cooperation-based adaptive hop-by-hop vector-based forwarding concepts, where sensor nodes forward data packets in a multi-hop fashion within a virtual pipeline. In the developed algorithm for the underwater WSN cloud application, data packets are forwarded in a multi-hop manner using a virtual pipelining mechanism.Nodes outside the virtual pipeline do not forward data packets, thereby reducing flooding in the cooperative WSN. To prevent data packets from being forwarded towards void areas in the WSN, 2-hop information is used at each hop. This approach improves the performance of the wireless sensor network in terms of various performance criteria compared to existing routing protocols. The simulation tool NS2 is used to observe the simulation results of the energy packets being transferred from the source to the sink. The simulation results demonstrate the effectiveness of the proposed methodology. Overall, this paper contributes to the field of underwater WSNs by introducing a novel routing protocol that improves energy efficiency and performance for cloud applications.

Fuzzy logic with honey badger algorithm for cluster‐based multi‐hop routing protocol for wireless sensor networks

SummaryIn the last decades, wireless sensor networks (WSNs) have appeared as an active research area owing to their high applicability in different application areas like healthcare, automation, and the military. Several issues have been encountered in the WSNs, including energy consumption, deployment of sensor nodes, routing algorithms, energy efficiency, cluster head (CH) selection, and robustness. Cluster‐based routing is one of the energy‐efficient solutions in the WSN. At the same time, the hot spot problem remains a challenging problem, which needs to be addressed in the design of energy‐efficient solutions for WSNs. Motivated by the abovementioned discussion, c The comprehensive comparison study pointed out the betterment of the FLHBA‐CMHR technique in terms of different measures. The FLHBA‐CMHR technique obtains a maximum half‐node die (HND) of 1629 nodes, while the LEACH, FUCA, URBD, DEFL, and E‐FUCA techniques attain decreased HND of 793, 1085, 1092, 1139, and 1344 nodes correspondingly.

Enhanced reliability in hazardous event detection: A resilient multipath routing protocol for wireless sensor networks

AbstractWith the advance of climate change and the local effects of human activity, it has become of utmost importance to sense spatially extended natural and artificial physical phenomena to predict, monitor, and mitigate hazardous events. Wireless sensor networks are suitable for observing such phenomena, for example, wildfires, floods or landslides, without human supervision. This is due to affordable devices, independent power sources, wireless communication, and a broad range of sensors. During normal operation a few, while during the occurrence of an event a multitude of devices can fail. This leads to further disconnected devices, degrading the network's sensing capabilities. The communication requirements of such applications are difficult to fulfil with general routing protocols. The monitored event is rare compared to the network's lifetime, while its occurrence results in multiple, gradual node failures, still demanding the network to perform reliably. Available routing protocols fail to address every aspect of such application, thus the authors propose the Reliable Resilient Multipath Routing Protocol, designed to construct multiple disjoint paths from each device to a distinguished one, called the sink. The protocol employs proactive and reactive network management techniques to increase connection redundancy and maintain connectivity during failures. To verify the proposed protocol end‐to‐end, we evaluated the supported parameters, performed comparative simulations with routing algorithms known from the literature, and provided estimates of a realistic deployment.

Distributed Backlog-Aware Protocol for Heterogeneous D2D Communication-Assisted Wireless Sensor Networks

Distributed Backlog-Aware Protocol for Heterogeneous D2D Communication-Assisted Wireless Sensor Networks

“Clustering Protocol Based on Territorial Energy for Random Deployment of Wireless Sensor Networks"

Wireless Sensor Networks (WSNs) have become increasingly essential for monitoring and gathering data in diverse environments. The efficient utilization of energy resources is crucial for prolonging the network lifetime in WSNs. This paper presents a comparative analysis of three prominent clustering protocols: Low Energy Adaptive Clustering Hierarchy (LEACH), Residual Energy Aware Clustering (REAC), and Territorial Energy-Driven Clustering Protocol (TEDC). TEDC introduces a novel approach where cluster heads are elected based on territorial dominance and energy levels, aiming to enhance energy efficiency and prolong network lifetime. The performance of LEACH, REAC, and TEDC is evaluated under various scenarios, including node density, network size, and communication range. Key performance metrics such as energy consumption, network lifetime, and packet delivery ratio are analyzed to assess the effectiveness of each protocol. The results provide valuable insights into the comparative strengths and weaknesses of these protocols, aiding network designers and researchers in selecting the most suitable protocol for specific WSN deployments. Additionally, the paper discusses potential optimizations and future research directions to further enhance the performance of clustering protocols in WSNs.

A Taxonomy and Survey on Grid-Based Routing Protocols Designed for Wireless Sensor Networks

Minimization of energy consumption is the main attention of researchers while developing a routing protocol for wireless sensor networks, as sensor nodes are equipped with limited power supply. Virtual topology is an integral part of routing, and grid-based routing protocols are quite popular due to their simplified and efficient virtual grid topology construction. Although a list of surveys exists that either focus on routing protocols in a broader way or on other virtual topologies, none of these surveys are concerned about grid topology and grid-based routing protocols. Having this motivation in mind and considering the impact of these routing protocols on controlling and managing the energy consumption of wireless sensor networks, this article provides an expansive assessment of grid-based routing protocols based on their methodology. In this survey, the existing grid-based routing protocols are classified into two categories from the perspective of sink mobility: static sink and mobile sink. A phase-wise comprehensive overview of these routing protocols is provided in chronological order, along with their comparative analysis. Furthermore, the characteristics, design issues, and challenges of grid-based routing protocols are also provided.

EVRP: A novel geometrical based energy efficient eye vision routing protocol for wireless sensor networks based on the k-means algorithm

The limited energy source used in wireless sensor networks (WSNs) is a crucial aspect when designing a routing protocol. Developing a routing protocol that tries to maximize energy utilization can significantly improve the system's lifetime and balance energy consumption. A novel geometrical-based energy-efficient routing protocol called "EVRP" is presented in this paper. The Cluster generation process is based on the k-means algorithm for nodes grouping. To choose a cluster head (CH) for each cluster, a cost function is calculated for each node considering factors such as remaining energy level for the node, and the mean distance between the node and its neighbors. In the inter-cluster routing phase, a novel geometrical-based routing protocol is introduced considering factors such as the distance to a base station (BS), remaining energy level, and distance between CHs to find the optimal path between BS and CH. The cluster structure is integrated with direct communication in addition to a dynamic clustering mechanism based on the optimum number of CHs and a load balancing mechanism to reduce the load on CHs near BS. The simulation results demonstrate that in different scenarios, the proposed protocol can significantly increase the network lifetime, network throughput, and network stability by 52 %, 45 %, and 30 % respectively compared with the EECRAIFA protocol and by 100 %, 97.6 %, 64.3 % respectively compared with D2CRP protocol.

A Clustering Election Game-Based and Two-Level Management Protocol for Wireless Sensor Networks

A Clustering Election Game-Based and Two-Level Management Protocol for Wireless Sensor Networks

A novel energy-efficient dynamic programming routing protocol in wireless multimedia sensor networks

Wireless multimedia sensor networks (WMSNs) have characteristics that may influence the routing decisions, such as limited energy resources, storage and computing capacity. Therefore, a routing optimization needs to be done to match the characteristics of the WMSNs. Existing routing protocols only consider energy efficiency regardless of energy threshold, maximum energy, and link cost collectively as the primary basis of routing. In this work, the energy-efficient dynamic programming (EEDP) protocol is proposed to optimize routing decisions that take into account the energy threshold, the maximum energy, and the link cost. Then, the protocol is compared with the dynamic programming (DP), and the ant colony optimization (ACO) protocol. The simulation results show that the EEDP protocol can improve energy efficiency of nodes and network lifetime of the WMSNs. Then, the EEDP protocol is also implemented into a network topology of 10 NodeMCU ESP32 devices. As a result, the EEDP protocol can work very well by selecting routes based on nodes that have the remaining energy above 50 and has the shortest distance. The average delay in sending data for the entire route for the 10 iterations of sending data is 3.99 seconds.

GTFR: A Game Theory-Based Fuzzy Routing Protocol for WSNs

Clustering is an approach exploited in Wireless Sensor Networks (WSNs) to enhance their performance and energy efficiency. Therefore, cluster formation and proper cluster head (CH) selection are of utmost importance in such scenarios. The proposed method, game theory-based fuzzy routing (GTFR) protocol, optimizes both of these phases of network operation in WSN. In the proposed work, fuzzy clustering is utilized for forming clusters with the desired quality of having low intra-cluster communication distance (IACD). In addition, CH selection is based on game theory and a fitness function that ensures optimal CH selection during two sub-phases of CH selection (tentative CH selection and final CH selection). In conjunction with using a penalty function for the clustering game, the proposed work also considers the nodes’ history of acting as a CH as a fitness criterion to enhance performance by impartially rotating the role among all the nodes. The proposed protocol outperforms LEACH, HSCR LEACH, FCM, and CT-RPL protocols in terms of stability by 238.27%, 183.94%, 432.04%, and 47.31%, respectively. Rigorous simulations prove that the proposed protocol outperforms LEACH, HSCR LEACH, FCM, and CT-RPL in all three considered network scenarios.

Energy efficient cluster routing protocol for wireless sensor networks using hybrid metaheuristic approache’s

The development of wireless sensor networks (WSNs) has been particularly notable in the context of smart computing, where various application areas have been identified. These networks consist of self-configured, small sensor nodes with battery power. However, sensors have limited energy and resources at their disposal. When unbalanced nodes exist within the network, it adversely affects the network’s lifetime due to increased power consumption. Designing efficient routing for wireless sensor networks remains a challenging task, particularly in terms of energy efficiency. Optimal solutions to address these challenges involve reducing node energy consumption through the implementation of clustering techniques. The current clustering schemes do not take into account node energy balancing, node density, and scalability when selecting low-energy nodes as cluster heads. The existing system is limited to exploring global opportunities within specified search zones. To enhance the performance of WSNs, a hybrid approach combining artificial bee colony (ABC) and ant colony optimization (ACO) has been developed. This approach helps in selecting an ideal cluster head from a group of terminals. Several factors are considered in the cluster head election, including residual energy at the nodes, distance to neighbors, distance to the base station, node degree, and node centrality. ACO determines the path between the cluster leader and the base station (BS) by selecting the most efficient route in terms of distance, remaining power, and node degrees. The performance of this proposed methodology has been analyzed in terms of energy consumption, network lifetime, and data packets at the base station. A comparison has been made between the outputs of the proposed methods and traditional benchmarking methods. The results reveal a substantial improvement in the average network lifetime, showcasing an increase of 40.50%, 33.17%, 25.00%, and 15.49% when compared to LEACH, Beecluster, iABC, and BeeSensor, respectively. In terms of alive nodes, our solution surpasses LEACH, Beecluster, iABC, and BeeSensor by 28.7%, 22.51%, 20.95%, and 12.47%, respectively. Additionally, the energy consumption of our approach proves to be significantly lower than LEACH, Beecluster, iABC, and BeeSensor, recording reductions of 47.25%, 32.40%, 27.38%, and 22.20%, respectively.

Adaptive Data Transmission Protocols for Energy Harvesting WSNs Used in Agriculture

Energy consumption is a major concern in wireless sensor networks (WSNs) as it affects the lifespan of sensor nodes. Battery-based WSNs have a short operating period, which makes them impractical for real-time applications, for instance in agriculture. Energy harvesting and suitable medium access control (MAC) protocols have been used to extend the lifetime of nodes. Receiver-initiated protocols have been proved to be the best solution for energy harvesting WSNs. However, they suffer from a key disadvantage, i.e. an increase in collision rate. These collisions need to be reduced using a multi-layer protocol structure. In such a context, a new solar-based hybrid MAC (SHMAC) protocol relying on receiver-initiation and characterized by a multi-layer structure is proposed. It is an adaptive protocol capable of adapting to changing weather conditions. The nodes with a high energy harvesting rate have a higher level of residual energy and are active for longer time periods compared with those with low energy harvesting characteristics. The proposed work has shown improvements in two major MAC layer parameters, i.e. collision rate and energy neutrality operation ratio (ENO).

OEE-WCRD: Optimizing Energy Efficiency in Wireless Sensor Networks through Cluster Head Selection Using Residual Energy and Distance Metrics

Wireless Sensor Networks (WSNs) play a pivotal role in various applications, including environmental monitoring, industrial automation, and healthcare. However, the limited energy resources of sensor nodes pose a significant challenge to the longevity and performance of WSNs. To address this challenge, this paper presents an Optimized Energy Efficient Protocol in Wireless Sensor Networks through Cluster Head Selection Using Residual Energy and Distance Metrics (OEE-WCRD). This research paper presents a novel approach to cluster head selection in WSNs by harnessing a combination of residual energy and distance metrics. The proposed method aims to significantly enhance the energy efficiency of WSNs by prioritizing nodes with ample residual energy and proximity to their neighbors as cluster heads. Through extensive simulations and evaluations, we demonstrate the effectiveness of this approach in prolonging network lifetime, optimizing data aggregation, and ultimately advancing the energy efficiency of WSNs, making it a valuable contribution to the field of WSNs protocols.

Energy Efficient Spiking Deep Residual Network and Binary Horse Herd Optimization Espoused clustering Protocol for Wireless Sensor Networks

Nowadays, Wireless Sensor Networks (WSNs) plays several important application fields, specially monitoring events without any human interference. The sensor nodes (SNs) have lesser life time in wireless sensor network owing to its continual sensing with battery drains very rapidly. As a result of the heavy traffic, sensors nearby quickly expire and energy hole issues start to appear. To overcome these issues, an Energy Efficient Spiking Deep Residual Network and Binary Horse Herd Optimization Espoused Clustering Protocol for Wireless Sensor Networks (EE-SDRN-BHHO-CP-WSN) is proposed in this manuscript for sustaining the energy efficiency in the wireless sensor network. One of the main issues in wireless sensor network assisted applications is making use of the available energy. An optimum path selection is a key process of saving energy from sensor nodes to the sink. Spiking Deep Residual Network (SDRN) and Binary Horse Herd Optimization (BHHO) optimize energy efficiency in WSN. The cluster head (CH) is designated by effectual fitness function generated by multi-objectives. It benefits in low power consuming and decreases a count of idle sensor nodes. After CH selection, Binary horse herd optimization algorithm is considered for optimal route selection and data transmission by sink node. The EE-SDRN-BHHO-CP-WSN method is implemented in MATLAB and the efficiency of the proposed method is analyzed with different metrics, like network lifetime, number of alive nodes, number of dead nodes, throughput, energy consumption, packet delivery ratio (PDR). The proposed EE-SDRN-BHHO-CP-WSN method attains 32.35 %, 42.34 %, 49.27 % higher network lifetime, 26.34 %, 31.94 % and 39.35 % higher number of alive nodes and 46.26 %, 38.64 % and 27.83 % lower number of dead nodes compared with other existing models, such as Multi-objective CH based Energy-aware Optimized Routing Algorithm in WSN (MCH-EOR-WSN), Energy efficient CH selection utilizing improved Sparrow Search Algorithm in WSN (EECH-ISSA-WSN), and New Energy Aware CH Selection Algorithm for WSN (NEA-CHSA-WSN respectively).

An energy efficient fusing data gathering protocol in wireless sensor networks

The Internet of Things (IoT) is rapidly developing as a promising technology for today’s digital world. Wireless sensor networks (WSN) are a crucial component of IoT, and one of the major problems faced is energy constraints. The clustering protocol is an effective energy saving solution. In this paper, we propose an energy efficient fusing data gathering protocol via distributed second level clustering and deep learning-based data fusion (EEFDG) for WSN. EEFDG divides the WSN into several second-level clusters by a novel distributed cluster algorithm. The transmission distance and the number of neighbors are jointly considered to select an energy-efficient parent node in each second-level cluster. A new cluster head weight function is proposed for intra-cluster parent node rotation. To minimize redundant data transmission, a multivariate convolutional neural network and long short-term memory network (MVCLNet) are designed for data fusion. MVCLNet is deployed hierarchically into the second-level clustered structure to extract features of the multi-sensor data. The EEFDG is an effective solution to the energy limitation problem of WSN. The proposed second-level clustering and data fusion algorithm based on MVCLNet typically decreases communication distances and the amount of data, thereby minimizing communication overhead and energy consumption. Simulation results show that EEFDG significantly prolongs the network lifetime in terms of the first node dead, compared to existing protocols including MR-LEACH, BPDA, CNNDA, FDEAM, DCNN, and LPLL-LEACH, achieving improvements of 181.3%, 42.2%, 48.2%, 19.6%, 62.0%, and 30.2%, respectively. The EEFDG enables highly accurate data fusion and has superior performance in terms of remaining energy, network lifetime, and data collection.

Comparative Analysis of LEACH Network Routing Protocol in Wireless Sensor Networks: A Survey

Comparative Analysis of LEACH Network Routing Protocol in Wireless Sensor Networks: A Survey

Yellow Saddle Goatfish Optimization Algorithm based Energy Aware Multihop Routing Protocol for Wireless Sensor Networks

Yellow Saddle Goatfish Optimization Algorithm based Energy Aware Multihop Routing Protocol for Wireless Sensor Networks