Routing Protocol For Wireless Sensor Networks Research Articles

Blockchain Enabled Metaheuristic Cluster Based Routing Model for Wireless Networks

With recent advancements made in wireless communication techniques, wireless sensors have become an essential component in both data collection as well as tracking applications. Wireless Sensor Network (WSN) is an integral part of Internet of Things (IoT) and it encounters different kinds of security issues. Blockchain is designed as a game changer for highly secure and effective digital society. So, the current research paper focuses on the design of Metaheuristic-based Clustering with Routing Protocol for Blockchain-enabled WSN abbreviated as MCRP-BWSN. The proposed MCRP-BWSN technique aims at deriving a shared memory scheme using blockchain technology and determine the optimal paths to reach the destination in clustered WSN. In MCRP-BWSN technique, Chimp Optimization Algorithm (COA)-based clustering technique is designed to elect a proper set of Cluster Heads (CHs) and organize the selected clusters. In addition, Horse Optimization Algorithm (HOA)-based routing technique is also presented to optimally select the routes based on fitness function. Besides, HOA-based routing technique utilizes blockchain technology to avail the shared memory among nodes in the network. Sensor nodes are treated as coins whereas the ownership handles the sensor nodes and Base Station (BS). In order to validate the enhanced performance of the proposed MCRP-BWSN technique, a wide range of simulations was conducted and the results were examined under different measures. Based on the performance exhibited in simulation outcomes, the proposed MCRP-BWSN technique has been established as a promising candidate over other existing techniques.

Improved Rat Swarm Based Multihop Routing Protocol for Wireless Sensor Networks

Wireless sensor networks (WSNs) encompass a massive set of sensor nodes, which are self-configurable, inexpensive, and compact. The sensor nodes undergo random deployment in the target area and transmit data to base station using inbuilt transceiver. For reducing energy consumption and lengthen lifetime of WSN, multihop routing protocols can be designed. This study develops an improved rat swarm optimization based energy aware multi-hop routing (IRSO-EAMHR) protocol for WSN. An important intention of the IRSO-EAMHR method is for determining optimal routes to base station (BS) in the clustered WSN. Primarily, a weighted clustering process is performed to group the nodes into clusters and select cluster heads (CHs). Next, the IRSO-EAMHR approach derives a fitness function containing three input parameters (residual energy, distance, and node degree) for routing process. The IRSO technique was designed by the integration of Levy movement concepts into the traditional RSO algorithm. The experimental result analysis of the IRSO-EAMHR technique is carried out and the outcomes are examined in various aspects. The simulation outcomes demonstrate the promising performance of the IRSO-EAMHR technique over the recent state of art approaches.

Fuzzy Rule-Based Clustering Algorithm for Energy Efficiency in WSN

Abstract: Wireless Sensor Networks (WSNs) have gained much attention in public and research communities due to their incredible capabilities and ever-growing range of applications. The WSN is equipped with a specialized transducer that adds sensing services to IoT. This equipment is limited to battery and resource capacity, which introduces many challenges to academia and industry. Many recent wireless sensor networks (WSN) routing protocols are enhancements to address specific issues with the low-energy adaptive clustering hierarchy (LEACH) protocol. Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm compensates for the energy flow in CH by probabilistically rotating the position between nodes with energy above the specified threshold. The selection of CH in WSN is NP-Hard as the optimal data aggregation with efficient energy efficiency cannot be resolved in polynomial time. Since the performance of LEACH deteriorates sharply with increasing network size, the challenge for new WSN protocols is to extend the network lifespan while maintaining high scalability. This paper introduces a fuzzy logic-based energy-efficient scalable routing algorithm (F-EESRA). The goal of the proposed algorithm is to extend the network lifespan despite an increase in network size. This paper compares F-EESRA against EESRA WSN routing protocol in terms of network performance. EESRA uses multi-hop transmissions for intra-cluster communications to implement the proposed work. The simulation results show that F-EESRA outperforms the fuzzy protocol in terms of energy efficiency on large-scale WSNs.

Predictive Model Techniques with Energy Efficiency for IoT-Based Data Transmission in Wireless Sensor Networks

Wireless sensor networks are limited by the vast majority of goods with limited resources. Power consumption, network longevity, throughput, routing, and network security are only a few of the research issues that have not yet been addressed in sensor networks based on the Internet of Things. Prior to becoming widely deployed, sensor networks built on the Internet of Things must overcome a variety of technological obstacles as well as general and specific hazards. In order to address the aforementioned problems, this research sought to improve rogue node detection, reduce packet latency/packet loss, increase throughput, and lengthen network lifetime. Wireless energy harvesting is suggested in the proposed three-layer cluster-based wireless sensor network routing protocol to extend the energy lifespan of the network. For the purpose of recognising and blacklisting risky sensor node behaviour, a three-tier clustering architecture with an integrated security mechanism is suggested. This clustering approach is cost-based, and the sink node selects the cluster and grid heads based on the cost function’s value. With its seemingly endless potential across a wide range of industries, including intelligent transportation, the Internet of Things (IoT) has gained prominence recently. To analyse the nodes and clustering strategies in IoT, the suggested method PSO is applied. A plethora of new services, programmes, electrical devices with integrated sensors, and protocols have been produced as a result of the Internet of Things’ explosive growth in popularity.

Secure Routing Protocol for WSNs Using Bacterial Foraging Optimization and Improved RC4

Wireless sensor networks (WSNs) have recently received important sponsorship in various fields, such as medical treatment, emergency response, environmental monitoring, military monitoring, outer space research, etc. Sensor nodes are usually limited in capabilities, including batteries. These networks can handle critical data in hostile and uncontrolled environments. Sensor nodes are deployed in harsh, hazardous, or hard-to-reach environments, making it difficult to replace or recharge these batteries, so it is important to consider the security and energy consumption issues when designing such networks. Therefore, this paper proposed a new secure and energy-efficient routing protocol called Improved RC4 with Bacterial Foraging Optimization Routing Protocol (IRC4-BFORP) for WSNs. IRC4 has represented the improvement of RC4 to make the original algorithm safer and faster. The IRC4 is used to secure the sensing data sensed by the sensors before sending it to the sink. To demonstrate the effectiveness of IRC4 over the original algorithm, some numerical analyses are achieved. The results have shown that IRC4 is more secure than the original algorithm. Also, the BFORP has proposed to send the secure sensing data to the sink by selecting the preferred nodes in the transmission paths. The simulation results prove the effectiveness of the BFORP in reducing energy use and reducing delays on the one hand, compared with the well-known protocols that are used in routing.

Impact of Evaporation on the Performance of Ant Colony Optimization-Based Routing Protocols on the Wireless Sensor Network

Wireless Sensor Network (WSN) has the characteristics limited computing, memory and energy, so a routing protocol that supports WSN network performance is needed. Routing protocols based Ant Colony Optimization (ACO) are very suitable for use in WSN for routing data packets. In this report, we will try out several kinds of parameter values that bear on the pheromone evaporation (ρ) on the ACO algorithms applied to the WSN routing protocol with grid topology on the number of nodes variables in the WSN network. Where this can increase the number of delivery packets on a busy WSN network and each node transmits a packet continuously. From the results, the value of ρ 0.75 makes WSN performance on the grid topology with the number of nodes 12 and 30 very good in terms of the delivery packet, but with the number of nodes 70 the value of ρ 0.70 makes WSN performance better than the delivery packet side.

A Systematic Review on the Energy Efficiency of Dynamic Clustering in a Heterogeneous Environment of Wireless Sensor Networks (WSNs)

There are a variety of applications for wireless sensor networks (WSNs), such as military, health monitoring systems, natural disasters, smartphones, and other surveillance systems. While the primary purpose of sensor nodes is to collect unattended data in hostile environments, many are placed in large numbers and operate independently. Due to limited capabilities, power is often limited. Therefore, these nodes are grouped into clusters to increase communication efficiency. In WSNs, two different routing protocols are possible: apartment and hierarchical or clustering protocols. Due to their significant role in minimizing energy consumption, hierarchical methods have become very popular in clustering. In cluster-based methods, nodes are organized into clusters, and the sensor node with the most resources is appointed as the cluster head (CH). In this paper, we present a Systematic Literature Review (SLR) explaining the difficulties in developing cluster-based methods, critical factors for clustering, and hierarchical clustering protocols. The most important factor of a routing protocol for WSN is the energy consumption and lifetime of a network. Focusing on energy consumption, different cluster-based methods were analyzed to determine which technology should be deployed by analyzing specific criteria to support the selection process. Additionally, the pros and cons of different protocols are listed with their relevance in specific scenarios. To identify these protocols, a systematic literature review was conducted using research studies published from 2010 to 2021, with 30 papers analyzed in the final phase. Based on the results of this SLR, several issues need to be further investigated with respect to the interaction of the potential technology with the Internet of Things (IoT) and Vehicular Ad-Hoc Networks (VANETs).

SPEED-UP, and energy-efficient GPSR protocol for WSNs using IOT

The development of new applications for intelligent cities, medicine, agriculture and energy harvesting would be a promising concept using wireless sensor networks based on the Internet of Things (IoT-WSNs). At the moment, the research was aimed at reducing the limited energy supply of IoT devices, which has a serious impact on their architecture. To ensure rapid and stable connection, new and efficient methods of energy systems must be designed. To handle data transfer in WSNs and to handle the problem of detector energy supply, the authors presented an improved Speed Up-Greedy Perimeter Stateless Routing Protocol for Wireless Sensor Networks (SU-GPSR) and Energy Harvest Greedy Perimeters Stateless Routing Protocol (EH-GPSR). SU-GPSR, unlike other variations of GPSR algorithms, provides complete energy consumption while assessing the next jump for local nodes and mobile nodes in an integrated framework. Additionally, established measurements are recorded using the SU-GPSR skip selection method. To calculate the amount of energy collected, EH-GPSR uses an EH rate that is generated by Mobilized Minimum Path Recovery Time (MMRT) method, as it improves the method of greedy routing. To incrementally choose the next hop, it particularly uses a weighted method that merges the node's data cost with the EH rate. In both packed and systems, the simulation study infers that SU-GPSR performs better than EH-GPSR and FA-GPSR, whereas EH-GPSR increases the node life with a speed by 20% when contrasted to the other GPSR method.

Node Injection Control Logic Design for Intelligent Home System Based on Wireless Sensor Network

Smart home is a building, network, communication, automation, set management, and service, as one of the efficient, comfortable, safe, and environmental protection of the living environment, and can provide personalized living space according to the needs of different users. Due to the advantages of wireless sensor network (WSN), such as strong expansion ability, strong communication ability, and strong self-organization ability, the smart home system based on WSN has become the main development direction in the field of smart home. This paper analyzes the different functions and features of wireless sensor network routing protocol and use scope, aiming at the application layer, using the MQ queue enhance server concurrent processing capacity and system scalability and design based on application layer gateway and terminal node “data matching list,” which are introduced in the design of smart home system based on geographic information location energy-efficient routing protocols. The solution of routing void problem is improved by using information feedback mechanism and alternate nodes. Simulation results show that this method can improve the energy saving of energy-efficient routing protocol. Finally, the intelligent home system experiment platform was built to verify the overall function of the system, and the communication function of the WiFi network and ZigBee network was tested. Based on the analysis of the interference between ZigBee and WiFi network, frequency agility algorithm is used to solve the problem of the same frequency interference, so as to ensure the performance of the system to meet the needs of the smart home system.

Application-specific clustering in wireless sensor networks using combined fuzzy firefly algorithm and random forest

Clustering in wireless sensor networks (WSNs) has proved to be one of the most efficient ways to hierarchically organize the network topology for the purposes of load-balancing and elongating the network lifetime. However, achieving optimal clustering in WSNs is an NP-hard problem, and consequently, heuristics and metaheuristics have been widely adopted. In this paper, a combined clustering technique based on a fuzzy-firefly algorithm (FFA) and random forest (RF), shortly named as: FFA-RF, is presented as an application-specific routing protocol for WSNs. Our FFA-RF protocol entails offline tuning and online routing phases: the offline phase consists of data collection using FFA, training and test of the RF, while the online phase is the actual application of the FFA-RF model to new network instances. In the offline phase, we construct an optimized fuzzy inference system based on FFA and apply it on different network topologies, to collect a comprehensive dataset. We then divide the resulting dataset into training and test sets to train and test the RF model. In the online phase, the trained RF model is used as an online clustering algorithm to estimate the fuzzy priority factor of the nodes for being cluster heads (CHs) in new network instances. To increase the generalizability of the RF for different configurations, node features as well as application features are used as inputs of the RF model. Simulation results for different network topologies demonstrate the superiority of the proposed FFA-RF protocol in prolonging the application-specific lifetime when compared against existing crisp heuristic, fuzzy heuristic, metaheuristic, and combined fuzzy-metaheuristic protocols.

A new Asymmetric Link Quality Routing protocol (ALQR) for heterogeneous WSNs

Wireless sensor networks (WSNs) have received a lot of attention due to numerous advancements, especially in smartphones, smart watches, smart homes, and even smart cities. Aside from WSNs progression, they are affected by a combination of factors, including network efficiency, link asymmetry, and energy loopholes. This paper introduces a novel approach, particularly useful for challenging receiver-initiated asynchronous heterogeneous networks, which are competitive due to low energy consumption. In WSNs, inefficient energy consumption is a widespread issue that drastically decreases the lifetime of each deployment network. To overcome these challenges, we proposed an intelligent Asymmetry link Quality Routing (ALQR) protocol for WSNs with a low energy consumption clustering protocol. Additionally, If there is no cross-channel traffic, ALQR provides adequate connection control at a low cost, making it more advantageous to WSN applications. We investigated the effectiveness of our proposed protocol compare to multiple state-of-the-art clustering-based protocols. According to the findings, ALQR outperforms in terms of region and lifetime, while ALQR ensures overall throughput.

A Cluster-Based Routing Protocol for WSN Based on Mahalanobis Distance and AODV Protocol

Wireless Sensor Network (WSN) has huge amount of sensor nodes that randomly deployed in the interested region to monitor the environment. In WSN, the energy efficiency is considered as a challenging task during data transmission. The mahalanobis distance based cluster head selection is proposed to solve the issues related to the energy constraint. Next, ad hoc on-demand distance vector routing protocol is used to find the optimal path between the source to base station via cluster heads. The performance of this mahalanobis method is analyzed in terms of energy consumption, throughput, packet loss ratio, End to End Delay (EED) and average delay ratio. The mahalanobis method is compared with Weighted Energy-efficient Clustering with Robust Routing (WECRR), improved Artificial Bee Colony (iABC), Adaptive Energy aware Cluster-based Routing (AECR), Evolutionary Multipath Energy-Efficient Routing (EMEER), K-means algorithm and Energy-aware Cluster-based Routing Protocol (ECRP). The energy consumption of the mahalanobis method is 0.641 J for 75 nodes, it is lesser than the existing methods.

An Energy Efficient Routing Protocol based on Reinforcement Learning for WSN

Wireless Sensor Network (WSN) seems to be critical because they are responsible for maintaining network routes, packet forwarding, and higher multi-hop connectivity. Clustering nodes is still a powerful technique for modelling routing protocol for WSNs, as it increases the range of communication services with energy efficiency. This paper focuses on the energy efficiency and improved lifetime of the network based on the reinforcement learning protocols. The system can adapt to network changes, such as energy efficiency, mobility and make better routing decisions attributable to Reinforcement Learning (RL). The legal restrictions on sensor nodes are taken into consideration and an energy-balancing routing model based upon reinforcement learning has been provided. The results show that the enhanced protocol outperforms the state of energy savings and network lifetime when compared to Q-learning and LARCMS energy-efficient routing protocols. The proposed protocol's effectiveness is analysed by end to end delivery and packet delivery.

ESCVAD: An Energy-Saving Routing Protocol Based on Voronoi Adaptive Clustering for Wireless Sensor Networks

An excellent routing protocol is important for wireless sensor network (WSN) construction and efficient data transmission. With the continuous expansion of the application scenarios and scopes of the Internet of Things, the existing WSN routing protocols are no longer suitable for the complex network structure and the huge demands of communications. Aiming at these issues of existing routing protocols, such as short network lifetime caused by high energy consumption and uneven distribution of surviving nodes, this article proposes an energy-saving clustering protocol based on adaptive Voronoi dividing, named energy-saving clustering by Voronoi adaptive dividing (ESCVAD) protocol. The innovation of ESCVAD protocol lies in the adaptive clustering algorithm based on Voronoi dividing and cluster head election optimization algorithm based on distance and energy comprehensive weighting. The advantage of proposed algorithms is effectively to balance the energy consumption between cluster head nodes and cluster member nodes. The simulation results show that, compared with the traditional routing protocols, such as low energy adaptive clustering hierarchy (LEACH) protocol and stable energy protocol (SEP), the proposed ESCVAD protocol can effectively reduce the clustering frequency and cluster head electing frequency, so as to reduce signaling interaction frequency, finally result in the energy consumption down and the network lifetime up. Among the six protocols for comparation, ESCVAD has the best network lifetime and energy efficiency.

Energy Balance Routing Protocol for Wireless Sensor Networks Based on Fuzzy Control Strategy

The existing routing protocols for wireless sensor networks were not reasonable in design, which limited their application. Most of the existing studies did not take into account the energy consumption of the network and the balanced use of the energy of sensor nodes, which led to the unsatisfactory application effect of wireless sensor networks in some fields. Therefore, from the perspective of energy balance in wireless sensor networks, this paper proposed a construction method of an energy balance routing protocol in wireless sensor networks based on a fuzzy control strategy. Firstly, based on the analysis of the basic composition of wireless sensor networks and the structure of sensor nodes, this paper expounded the basic process of wireless data transmission and summarized the classification and characteristics of routing protocols in wireless sensor networks from different angles. Secondly, according to the node data transmission characteristics of wireless sensor networks, the energy balance use model of sensor nodes was established, and the design method of the energy balance routing protocol based on fuzzy control strategy was proposed, and the data transmission link was optimized. Finally, through experimental comparative analysis, the results showed that the energy balanced routing protocol proposed in this paper can effectively realize the energy balanced use of the network data transmission process. Compared with other common routing protocols, the wireless sensor network routing protocol proposed in this paper can not only improve the data transmission efficiency and reduce the data redundancy but also save energy consumption and prolong the network running time. The design method of routing protocol proposed in this paper will be conducive to the optimization and application of routing protocol in wireless sensor networks and provide a theoretical basis for the related research of wireless sensor networks.

Swarm Intelligence with Adaptive Neuro-Fuzzy Inference System-Based Routing Protocol for Clustered Wireless Sensor Networks.

Wireless sensor network (WSN) comprises numerous compact-sized sensor nodes which are linked to one another. Lifetime maximization of WSN is considered a challenging problem in the design of WSN since its energy-limited capacity of the inbuilt batteries exists in the sensor nodes. Earlier works have focused on the design of clustering and routing techniques to accomplish energy efficiency and thereby result in an increased lifetime of the network. The multihop route selection process can be treated as an NP-hard problem and can be solved by the use of computational intelligence techniques such as fuzzy logic and swarm intelligence (SI) algorithms. With this motivation, this article aims to focus on the design of swarm intelligence with an adaptive neuro-fuzzy inference system-based routing (SI-ANFISR) protocol for clustered WSN. The proposed SI-ANFISR technique aims to determine the cluster heads (CHs) and optimal routes for multihop communication in the network. To accomplish this, the SI-ANFISR technique primarily employs a weighted clustering algorithm to elect CHs and construct clusters. Besides, the SI-ANFISR technique involves the design of an ANFIS model for the selection process, which make use of three input parameters, namely, residual energy, node degree, and node history. In order to optimally adjust the membership function (MF) of the ANFIS model, the squirrel search algorithm (SSA) is utilized. None of the earlier works have used ANFIS with SSA for the routing process. The design of SSA to tune the MFs of the ANFIS model for optimal routing process in WSN shows the novelty of the study. The experimental validation of the SI-ANFISR technique takes place, and the results are inspected under different aspects. The simulation results highlighted the significant performance of the SI-ANFISR technique compared to the recent techniques with a maximum throughput of 43838 kbps and residual energy of 0.4800J, respectively.

Secure Routing Optimization in Hierarchical Cluster-Based Wireless Sensor Networks

Popularity of wireless sensor networks (WSNs) is increasing continuously in different domains of daily life, as they provide efficient method of collecting valuable data from the surroundings for use in different applications. Routing in WSNs is the vital functionality that allows the flow of information generated by sensor nodes to the base station, while considering the severe energy constraint and the limitations of computational and storage resources. Indeed, this functionality may be vulnerable and must be in itself secured, since conventional routing protocols in WSNs provide efficient routing techniques with low power consumption, but they do not take into account the possible attacks. As sensor nodes may be easily captured and compromised, the classical cryptographic solutions become insufficient to provide optimal routing security, especially, for cluster-based WSNs, where cluster heads can be still among the compromised nodes. In this work, we propose a hierarchical, robust and well-adapted intrusion detection system, named THIDS, which is intended to be integrated into the secure hierarchical cluster-based routing protocols. We have chosen the protocol RLEACH to be equipped with the proposed IDS. The results of simulation performed under NS2 simulator show that the resulting protocol ORLEACH is much more resistant to compromised nodes exercising the most dangerous attacks.

Impact of queue buffer size awareness on single and multi service real-time routing protocols for WSNs

Wireless Sensor Networks (WSNs) are increasingly used and will certainly be part of our everyday lives. Many routing protocols were designed with respect to WSNs capacities to allow the achievement of numerous applications. One of the not well investigated areas in WSNs is the queue management issue. The purpose of this paper is to present an analysis of the impact of queue buffer size awareness on the Quality of Service (QoS) of real-time (RT) routing protocols in WSNs. The studied protocols are SPEED and its extension Multipath Multi-speed (MMSPEED). SPEED protocol yields RT routing for only one class of traffic, by maintaining a desired packet’s progression speed (PS) across the WSN. On the other hand, MMSPEED protocol extends SPEED by offering multiple types of service to packets according to their class of traffic. The main contribution is that the routing decision is made on neighbors’ available queue buffer size at each level in addition to PS metric. Simulations have proved that the two metrics are compatible, the routing decision is efficient in case of single service protocol and multiservice one and improves two QoS domains namely timeliness and reliability.

Enhanced Clustering Routing Protocol for Power-Efficient Gathering in Wireless Sensor Network

Wireless sensor network (WSN) is a new and fast advancing technology, which is opening up many opportunities in the field of remote sensing and data monitoring. In spite of the numerous applications of WSN, issues related to determining a suitable and accurate radio model that will foster energy conservation in the network limit the performance of WSN routing protocols. A number of radio models have been proposed to address this issue. However, the underlying assumptions and inaccurate configuration of these radio models make them impractical and often lead to mismanagement of scarce energy and computational resources. This paper addresses this problem by proposing an enhanced radio model that adapts to the frequent changes in the location of the sensor nodes and is robust enough to report reliable data to the base station despite fluctuations due to interference. The impact of incorporating stepwise energy level and specialized data transmission schemes in the proposed radio model is also investigated in this paper. The performance of the proposed radio model is evaluated using OMNET++ and MATLAB and the results obtained is benchmarked against PEGASIS. It is shown by simulation that the novel LEACH-IMP performs better with respect to energy consumption, number of links faults, number of packets received, signal attenuation, and network lifetime.

An improved evaporation rate water cycle algorithm for energy-efficient routing protocol in WSNs

PurposeThe paper aims to introduce an efficient routing algorithm for wireless sensor networks (WSNs). It proposes an improved evaporation rate water cycle (improved ER-WC) algorithm and outlining the systems performance in improving the energy efficiency of WSNs. The proposed technique mainly analyzes the clustering problem of WSNs when huge tasks are performed.Design/methodology/approachThis proposed improved ER-WC algorithm is used for analyzing various factors such as network cluster-head (CH) energy, CH location and CH density in improved ER-WCA. The proposed study will solve the energy efficiency and improve network throughput in WSNs.FindingsThis proposed work provides optimal clustering method for Fuzzy C-means (FCM) where efficiency is improved in WSNs. Empirical evaluations are conducted to find network lifespan, network throughput, total network residual energy and network stabilization.Research limitations/implicationsThe proposed improved ER-WC algorithm has some implications when different energy levels of node are used in WSNs.Practical implicationsThis research work analyzes the nodes’ energy and throughput by selecting correct CHs in intra-cluster communication. It can possibly analyze the factors such as CH location, network CH energy and CH density.Originality/valueThis proposed research work proves to be performing better for improving the network throughput and increases energy efficiency for WSNs.