Routing In WSNs Research Articles

A novel fractional rat hawk optimization–enabled routing with deep learning–based energy prediction in wireless sensor networks

SummaryWireless sensor networks (WSNs) contain different sensors, which collect various data in the monitoring area. In general, one of the significant resources in WSNs is energy, which prolongs the network's lifetime. The energy‐efficient routing algorithms reduce energy consumption and enhance the survival cycle of WSNs. Thus, this work developed the optimization‐based WSN routing and deep learning (DL)–enabled energy prediction scheme for efficient routing in WSNs. Initially, the WSN simulation is carried out, and then, the node with minimum energy consumption is chosen as the cluster head (CH). Here, the proposed rat hawk optimization (RHO) algorithm is established for finding the best CH, and the RHO is the integration of rat swarm optimization (RSO) and fire hawk optimization (FHO). Furthermore, the routing is accomplished by the developed fractional rat hawk optimization (FRHO) using the fitness function includes delay, distance, link lifetime, and predicted energy of a network for predicting the finest route. Here, the fractional calculus (FC) is incorporated with the RHO to form the FRHO. The energy prediction is achieved by deep recurrent neural network (DRNN). The energy, delay, and throughput evaluation metrics are considered for revealing the efficiency of the proposed system, and the proposed system achieves the best results of 0.246 J, 0.190 s, and 67.13 Mbps, respectively.

Trust-based clustering and routing in WSNs using DST-WOA

Trust-based clustering and routing in WSNs using DST-WOA

Markov chain‐based analysis and fault tolerance technique for enhancing chain‐based routing inWSNs

SummaryWireless sensor networks (WSNs) are faced with the challenge of energy conservation, which makes efficient routing protocols crucial for prolonging network lifetime. In addition, delay time from sensors to the base station is critical in applications such as military, medical, and security monitoring systems. Chain‐based protocols like PEGASIS, CCBRP, and CCM have been developed to address routing in WSNs, with the aim of reducing energy consumption and delay. However, node failures are inevitable due to energy reduction and node mobility. Therefore, fault tolerance techniques must be integrated into routing protocols. A new fault tolerance method has been proposed to prevent early chain failures in WSNs by formulating network availability and reliability using Markov chain analysis. The results indicate that chain‐based routing protocols with one spare node are more reliable than those with two spare nodes.

Mathematical Modeling and Statistical Analysis of Leach Algorithm Based Cluster Head Selection Approach for Wireless Sensor Networks

In this paper, we present a comprehensive design and analysis of our proposed improved fuzzy logic-based algorithm. The algorithm utilizes a fuzzy logic system to assess node attributes such as residual energy, distance to the base station, and connectivity. By considering these parameters, the algorithm dynamically evaluates the most suitable candidates for cluster head roles, effectively distributing the energy load and promoting equitable cluster formation. An extensive performance evaluation of proposed algorithm has been conducted through simulations and comparisons with the original LEACH protocol. Our results reveal that the improved fuzzy logic-based algorithm outperforms the conventional LEACH in terms of network lifetime, energy consumption, and overall network stability. In this study, we delve into the mathematical modeling and statistical analysis of the proposed algorithm, focusing on its impact on energy efficiency, network stability, and data routing in WSNs. The Improved Fuzzy Logic-Based Cluster Head Selection Algorithm employs fuzzy logic to intelligently select cluster heads, considering parameters like residual energy, distance to the base station, and historical data. We develop mathematical models to describe the algorithm's behavior and analyze its performance through extensive simulations and statistical evaluations. The algorithm demonstrates enhanced adaptability to varying network conditions and node heterogeneity, showcasing its potential to significantly extend the operational duration of WSNs in diverse deployment scenarios. In conclusion, this paper contributes a novel perspective to the domain of WSNs by introducing an advanced fuzzy logic-based cluster head selection algorithm. The algorithm enhances the foundation of the LEACH protocol, effectively addressing energy optimization concerns and promoting prolonged network lifetime. The presented design and analysis substantiate the algorithm's superiority, offering valuable insights for researchers and practitioners working on energy-efficient routing protocols and wireless sensor network management.

Dynamic framework towards sustainable and energy-efficient routing in delay tolerant IoT-based WSNs

Dynamic framework towards sustainable and energy-efficient routing in delay tolerant IoT-based WSNs

Dynamic framework towards sustainable and energy-efficient routing in delay tolerant IoT-based WSNs

Dynamic framework towards sustainable and energy-efficient routing in delay tolerant IoT-based WSNs

SBLDAR: A Link Score Based Delay Aware Routing for WSNs

SBLDAR: A Link Score Based Delay Aware Routing for WSNs

Trust aware clustering based secure routing techniques in wireless sensor network

Wireless Sensor Networks are becoming increasingly popular in everyday life since they offer a variety of network structures for developing cutting-edge real-time applications. Wireless sensor devices have high energy consumption limitations, so it is necessary to handle excessive energy consumption by malicious nodes properly to improve network performance. Even though numerous studies have been conducted to increase the dependability of routing in WSNs, the existing routing strategies do not meet the required security constraints by using intelligent methods to protect the sensor nodes from malicious attack. To overcome this challenge a novel Trust Aware Clustering based Secure Routing Techniques (TAC-SRT) has been proposed to minimize the overall energy consumption, improved security to nodes and to maximize the network lifetime. The proposed method is carried out in three phases. In the first phase, the cluster head is selected by using K mean clustering. In the second phase, the trust value of each node is evaluated by using Mamdani fuzzy inference rule. In the third phase, the Tversky similarity index is used to find the normal or malicious node and establishes the shortest route. The Fully Homomorphic Elliptic Curve Cryptography technique is then used to perform secure data transmission. The effectiveness of the proposed strategy is examined using several parameters, such as the lifetime of the network, data confidentiality, active nodes, and energy consumption. The proposed technique improves the network lifetime by 23.01%, 17.4%, and 13.2% better than MOSFA, SecDL, and CAR-MOSOA respectively. Finally, the proposed method demonstrated superior performance in terms of delay, throughput, encryption time, network lifetime, and packet delivery ratio compared with existing techniques.

A Novel Hybrid Protocol in Achieving QoS Regarding Data Aggregation and Dynamic Traffic Routing in IoT WSNs

A Novel Hybrid Protocol in Achieving QoS Regarding Data Aggregation and Dynamic Traffic Routing in IoT WSNs

A Reliable Protocol for Data Aggregation and Optimized Routing in IoT WSNs based on Machine Learning

A Reliable Protocol for Data Aggregation and Optimized Routing in IoT WSNs based on Machine Learning

Multi‐objective‐derived energy efficient routing in wireless sensor networks using hybrid African vultures‐cuckoo search optimization

SummaryWireless Sensor Network (WSN) plays an essential role in consumer electronics, remote monitoring, an electromagnetic signal, and so forth. The functional capacity of WSN gets enhanced everyday with different technologies. The rapid development of wireless communication, as well as digital electronics, provides automatic sensor networks with low cost and power in various functions, but the challenge faced in WSN is to forward a huge amount of data between the nodes, which is a highly complex task to provide superior delay and energy loss. To overcome these issues, the development of a routing protocol is used for the optimal selection of multipath to perform efficient routing in WSN. This paper developed an energy‐efficient routing in WSNs utilizing the hybrid meta‐heuristic algorithm with the help of Hybrid African Vultures‐Cuckoo Search Optimization (HAV‐CSO). Here, the designed method is utilized for choosing the optimal cluster heads for progressing the routing. The developed HAV‐CSO method is used to enhance the network lifetime in WSN. Hence, the hybrid algorithm also helps select the cluster heads by solving the multi‐objective function in terms of distance, intra‐cluster distance, delay, inter‐cluster distance, throughput, path loss, energy, transmission load, temperature, and fault tolerance. The developed model achieved 7.8% higher than C‐SSA, 25.45% better than BSO‐MTLBO, 23.21% enhanced than AVOA, and 1.29% improved than CSO. The performance of the suggested model is validated, and the efficacy of the developed work is proved over other existing works.

A rapidly-exploring random tree-based intelligent congestion control through an alternate routing for WSNs

A rapidly-exploring random tree-based intelligent congestion control through an alternate routing for WSNs

Routing Protocol for Wireless Sensor Networks Based on Archimedes Optimization Algorithm

One of the key design problems of wireless sensor networks is to reduce energy consumption and improve node survival. Because the battery in sensor nodes is difficult to replace and the energy is limited, the design of energy-saving routing protocol becomes very important. Aiming at the problems of limiting node energy and shortening network lifetime in wireless sensor networks, a WSNs routing protocol based on improved archimedes optimization algorithm (IAOAR) is proposed in this paper. Firstly, in the cluster establishment phase, the protocol defines different fitness functions according to the energy, number and distance of sensor nodes to select the appropriate initial cluster. Then the fitness value of the node is calculated, and the weight is dynamically updated according to the number of iterations to improve the optimization ability of AOA algorithm. Virtual force is introduced to adjust the selected cluster head position to ensure the selection of optimal cluster heads, reduce the transmission energy consumption of common sensor nodes. In the data transmission stage, combined with the improved ant colony algorithm, the shortest transmission path to the sink node is constructed to reduce the energy consumption of long-distance data transmission at the cluster head. The simulation results showed that compared with LEACH, E-LEACH, LEACH-ANT and MAXLEACH protocols, the network life cycle of the protocol proposed in this paper was improved by 140.55%, 107.09%, 99.24% and 96.76% respectively. It effectively reduced the speed of node death, balances the network energy consumption and prolonged the network lifetime.

An analysis of architecture, framework, security and challenging aspects for data aggregation and routing techniques in IoT WSNs

Internet has evolved into a promising technology after going through various transitional phases in the past decades. It was invented in the early nineties, with the web being static, public and shared. The final transitional phase is the internet of services, where the content, web services, Extensible Markup Language (XML), productivity and commerce tools were created by the user bringing improved websites and services. Later on, with affordable mobile broadband, Android phones and tablets, people could access the internet and be in touch with the world through social media platforms and mobile applications. IoT is a network of physical components, vehicles, household appliances and other items embedded with devices, software, sensor systems, actuators and connectivity, connecting and transferring data. The process of gathering data from heterogeneous sensors for preventing recurrent transmissions simultaneously offering quality aggregated information at the sink node is collectively called as data aggregation and routing process. There is a transmission of only most complex information to the sink node. The continuous use of data aggregation and routing technique increases the energy, bandwidth and memory requirements. The challenging aspects in IoT WSN are energy consumption, bandwidth and memory utilized for data aggregation and routing process. So, it is very much important to focus on these parameters so that the network has a greater lifetime and Quality of service. The tradeoff between energy saving, precision of data and latency can be achieved only by utilizing data redundancy, data similarity, data aggregation and routing algorithms. The aim of the research is to do the analysis of the IoT WSNs on the basis of the architecture, framework, and challenges related to security, data aggregation and routing techniques. This research work motivates the researchers to know about the challenges in data aggregation and routing in IoT WSNs. An efficient data aggregation and routing technique in IoT WSNs help to improve the QoS parameters namely, throughput, end to end delay, routing overhead, packet delivery ratio and energy consumption. Data aggregation technique in IoT WSNs help in saving the energy of the nodes in the network. Thus makes the network efficient in terms of energy and other QoS parameters. Because of the high density of nodes in IoT WSNs, same data is sensed by a lot of nodes, which results in redundancy. Using data aggregation technique, the redundancy can be eliminated while routing packets from source nodes to base station.

Bio-Inspired Multilevel Security Protocol for Data Aggregation and Routing in IoT WSNs

Bio-Inspired Multilevel Security Protocol for Data Aggregation and Routing in IoT WSNs

Energy Efficient Hop-by-Hop Retransmission and Congestion Mitigation of an Optimum Routing and Clustering Protocol for WSNs

In the past few decades, wireless sensor networks, which take a growing number of applications in the surroundings further than the human reach, have risen in popularity. Various routing pseudo codes have been suggested for network optimization, emphasizing energy efficiency, network longevity, and clustering processes. To the existing load balancing energy-efficient sleep awake, aware smart sensor network routing protocol, the modified load-balancing efficient-energy sleep active alert smart routing system for wireless sensor networks is presented in this paper, which takes network homogeneity into account. The modified protocol is the optimum clustering and routing protocol in wireless sensor networks (OCRSN), which simulates an enhanced network coupled node pair model. Our suggested modified approach studies and enhances factors such as network stability, network lifetime, and cluster monitor mechanism choice. The significance of typically combining sensor endpoints is applied to maximize energy efficiency. The proposed protocol significantly improved network parameters in simulations, showing that it could be a valuable option for WSNs. In wireless sensor networks, in addition to memory considerations and dependable transportation, this paper presents a hop-by-hop re-transmission strategy and congestion mitigation, which is the major contribution of this paper. It is a very consistent method based on a pipe flow model. After performing additional optimized overhead to improve the network lifespan of wireless sensors networks, the current algorithm can be paralleled to the less energy adaptive clustering hierarchy protocol. The optimal clustering in multipath and multihop technique intends to minimize the energy consumption highlighted for a circular area enclosed by a sink by replacing one-hop communication with efficient multihop communication. The optimum quantity of clusters is determined, and the energy consumption is reduced by splitting the network into clusters of nearly equal size. The obtained simulation results will demonstrate the increase in the network lifetime compared to previous clustering strategies such as Low Energy Adaptive Clustering Hierarchy.

A Rapidly-exploring random tree-based intelligent congestion control through an alternate routing for WSNs

A Rapidly-exploring random tree-based intelligent congestion control through an alternate routing for WSNs

Enhanced Ant Colony Optimization for Routing in WSNs An Energy Aware Approach

Enhanced Ant Colony Optimization for Routing in WSNs An Energy Aware Approach

Impact of Network Topology on Energy Efficiency in WSN

<p class="0abstractCxSpFirst"><span lang="EN-US">Wireless communication network has a significant success in scientific and industrial communities. Due to its various advantages, this technology is considered as a key element in current network architectures. It represents the architecture that allows to group a large number of sensors to collect information about a physical process in different environments. The gathered data is transmitted to base station which communicates the information to the end user.</span></p><p class="0abstractCxSpFirst">Several protocols are proposed for WSNs routing, by considering the limited capacities of sensor nodes according to a specific topology that allows to organize the nodes within the network. However, the performance of each routing protocol mainly depends on the application requirements and its results in terms of the lifetime of WSN and satisfaction of objectives defined.</p><p class="0abstractCxSpLast"><span lang="EN-US">According of the structure of WSN, the routing techniques can be divided in three types hierarchical, location-based flat routing. This paper, present the different routing techniques in WSN, based on the organization of nodes in sensor area. We focus specially to study the three types, cluster-based, chain-based and location-based routing techniques. These techniques will be simulated in order to compared their performances with our protocol Location-Based LEACH (LOC-LEACH).</span></p>

PSSPR: A source location privacy protection scheme based on sector phantom routing in WSNs

Source location privacy (SLP) protection is an emerging research topic in wireless sensor networks. Because the source location represents the valuable information of the target being monitored and tracked, it is of great practical significance to achieve a high degree of privacy of the source location. Although many studies based on phantom nodes have alleviates the protection of SLP to some extent. It is urgent to solve the problems, such as complicate the ac path between nodes, improve the centralized distribution of phantom nodes near the source nodes and reduce the network communication overhead. In this paper, protection scheme based on sector phantom routing (PSSPR) routing is proposed as a visible approach to address SLP issues. We use the coordinates of the center node V to divide sector domain, which act an important role in generating a new phantom node. The phantom nodes perform specified routing policies to ensure that they can choose various locations. In addition, the directed random route can ensure that data packets avoid the visible range when they move to the sink node hop by hop. Thus, the source location is protected. Theoretical analysis and simulation experiments show that this protocol achieves higher security of source node location with less communication overhead.