Routing Protocol For Sensor Networks Research Articles

Cluster-based energy-efficient routing protocol in next generation sensor networks

Cluster-based energy-efficient routing protocol in next generation sensor networks

Node utilization index-based data routing and aggregation protocol for energy-efficient wireless sensor networks

Node utilization index-based data routing and aggregation protocol for energy-efficient wireless sensor networks

A Novel Particle Swarm Optimization-Based Clustering and Routing Protocol for Wireless Sensor Networks

A Novel Particle Swarm Optimization-Based Clustering and Routing Protocol for Wireless Sensor Networks

A HSEERP—Hierarchical secured energy efficient routing protocol for wireless sensor networks

A HSEERP—Hierarchical secured energy efficient routing protocol for wireless sensor networks

An Adaptive Routing Protocol for Underwater Acoustic Sensor Networks With Ocean Current

An Adaptive Routing Protocol for Underwater Acoustic Sensor Networks With Ocean Current

Computational intelligence techniques for energy efficient routing protocols in wireless sensor networks: A critique

AbstractWireless Sensor Networks (WSNs) play a pivotal role in modern data acquisition systems, but their energy‐efficient operation remains a significant challenge. This work provides a concise overview of the key challenges and proposed solutions discussed in the context of energy‐efficient routing protocols for WSNs based on a systematic literature review. The need for fault tolerance to ensure network resilience is vital, given the limited resources and environmental challenges faced by sensor nodes. This work emphasizes the importance of addressing several open research questions, including the integration of diverse topologies, cross‐layer routing, and the use of multiple mobile sinks. Additionally, it highlights the need for QoS‐aware routing for real‐time applications, mathematical modeling for protocol evaluation, and the challenges of testing routing protocols on real hardware. Furthermore, this article suggests leveraging the RPL routing protocol with the Node‐based Metric RNE for enhanced energy efficiency and explores the promising field of hierarchical routing protocols, exemplified by the LEACH protocol and its variants. This work serves as a roadmap for researchers and practitioners, identifying critical challenges and proposing directions for future research to achieve energy‐efficient routing protocols in WSNs, ultimately enabling effective communication in resource‐constrained environments.

Self-Configuration and Self-Healing Framework Using Extreme Gradient Boosting (XGBoost) Classifier for IoT-WSN

In most Internet of Things (IoT) systems, Quality of service (QoS) must be confirmed with respect to the requirement of implementation domain. The dynamic nature of the IoT surroundings shapes it to complicate the fulfilment of these commitments. A wide range of unpredictable events endanger the quality of service. While execution the self-adaptive schemes handle with system’s unpredictable. In IoT-based Wireless Sensor Networks (WSNs), the significant self-management objectives are self-configuration (SC) and self-healing (SH). In this paper, Self-Configuration and Self-healing Framework using an extreme gradient boosting (XGBoost) Classifier are proposed. In this framework, the IoT traffic classes are categorized as several types under XGBoost classifier. In SC phase, the IoT devices are self-configured by allocating various transmission slots, contention access period (CAPs) on the basis of its categories with priorities. In SH phase, the source node cardinally establishes a confined route retrieval method if the residual power in-between node is truncated or the node has displaced far away. The proposed framework is executed in NS-2 and the results exhibit that the proposed framework has higher packet delivery ratio with reduced packet drops and computational cost. Therefore, the proposed approach has attained 24.7%, 28.9%, 12.75% higher PDR, and 16.8%, 19.87%, and 13.7% higher residual energy than the existing methods like Self-Healing and Seamless Connectivity using Kalman Filter among IoT Networks (SH-SC-KF-IoT), Provenance aware run-time verification mechanism for self-healing IoT (PA-RVM-SH-IoT), and Fully Anonymous Routing Protocol and Self-healing Capacity in Unbalanced Sensor Networks (FARP-SC-USN) methods, respectively.

Energy-efficient routing protocol for wireless sensor networks based on progressive and concentric clusters

Smart parking is common in contemporary cities. These smart parking lots are outfitted mostly with wireless sensor networks (WSNs), which are used to detect, monitor, and collect data on the availability status of all existing parking spaces in a given area. Sensors make up WSN, which may gather, process, and transmit informations to the sink. However, the power and communication limitations of the sensors have an effect on the performance and quality of the WSNs. The decrease in the battery and the energy of the nodes causes a decrease in the life of the nodes and also of the entire WSN network. In this article, we present a routing protocol that implements an efficient and robust algorithm allowing the creation of clusters so that the base station can receive data from the entire WSN network. This protocol adopts a reliable and efficient algorithm allowing to minimize the energy dissipation of the sensors and to increase the lifetime of the WSN. In comparison to alternative parking lot management protocols already in use, the simulation results of the proposed protocol are effective and robust in terms of power consumption, data transmission reliability, and WSN network longevity.

An optimized multi-hop routing protocol for wireless sensor network using improved honey badger optimization algorithm for efficient and secure QoS

A wireless sensor network (WSN) is a significant technology that might contribute in the industrial revolution. Sensor Nodes (SNs) in WSNs are equipped with a battery as a power source. Energy is the most critical resource for WSNs since the battery cannot be replaced or refilled. Several solutions have been devised and implemented over the years to preserve WSNs, which are a scarce resource. This study suggested a model to solves the energy issue as well as security issue and presents an optimized multi-hop routing in WSNs based on improved Honey Badger Algorithm (I-HBA). This method for multi-hop routing involves two steps: selecting a Cluster Head (CH) and routing the data packets. The I-HBA is used to pick energy-efficient CHs for efficient data transfer. The SNs then send their data through the chosen CH, which forwards it to the base station (BS) using the most efficient number of hops. The suggested I-HBA is used to select the finest hops. The proposed model employs the multi-objective fitness function including eight parameters for effective routing in the WSNs. Furthermore, security conscious multihop routing is carried out by employing a trust model that includes direct and indirect trust, data, integrity and forwarding rate factor. Additionally, the proposed I-HBA based routing protocol compared with the existing protocol such as LEACH, HEED, and PSO; and the proposed protocol outperforms the existing models. The findings show that for the same number of iterations, the whole quantity of data packets receives by the WSN using the proposed I-HBA based multihop routing protocol is substantially larger than for the PSO, LEACH, and HEED-based models.

CERP: Cooperative and Efficient Routing Protocol for Wireless Sensor Networks.

Wireless sensor networks (WSNs), constrained by limited resources, demand routing strategies that prioritize energy efficiency. The tactic of cooperative routing, which leverages the broadcast nature of wireless channels, has garnered attention for its capability to amplify routing efficacy. This manuscript introduces a power-conscious routing approach, tailored for resource-restricted WSNs. By exploiting cooperative communications, we introduce an innovative relay node selection technique within clustered networks, aiming to curtail energy usage while safeguarding data dependability. This inventive methodology has been amalgamated into the Routing Protocol for Low-Power and Lossy Networks (RPL), giving rise to the cooperative and efficient routing protocol (CERP). The devised CERP protocol pinpoints and selects the most efficacious relay node, ensuring that packet transmission is both energy-minimal and reliable. Performance evaluations were executed to substantiate the proposed strategy, and its practicality was examined using an Arduino-based sensor node and the Contiki operating system in real-world scenarios. The outcomes affirm the efficacy of the proposed strategy, outshining the standard RPL concerning reliability and energy conservation, enhancing RPL reliability by 10% and energy savings by 18%. This paper is posited to contribute to the evolution of power-conscious routing strategies for WSNs, crucial for prolonging sensor node battery longevity while sustaining dependable communication.

3R: A reliable multi agent reinforcement learning based routing protocol for wireless medical sensor networks

Interest in the Wireless Medical Sensor Network (WMSN) is rapidly gaining attention thanks to recent advances in semiconductors and wireless communication. However, by virtue of the sensitive medical applications and the stringent resource constraints, there is a need to develop a routing protocol to fulfill WMSN requirements in terms of delivery reliability, attack resiliency, computational overhead, and energy efficiency. This paper proposes 3R, a reliable multi agent reinforcement learning routing protocol for WMSN. 3R uses a novel resource-conservative Reinforcement Learning (RL) model to reduce the computational overhead, along with two updating methods to speed up the algorithm convergence. The reward function is re-defined as a punishment, combining the proposed trust management system to defend against well-known dropping attacks. Furthermore, an energy model is integrated with the reward function to enhance the network lifetime and balance energy consumption across the network. The proposed energy model only uses local information to avoid the resource burdens and the security concerns of exchanging energy information. Experimental results prove the lightweightness, attacks resiliency and energy efficiency of 3R, making it a potential routing candidate for WMSN.

MO-CBACORP: A new energy-efficient secure routing protocol for underwater monitoring wireless sensor network

With the rapid progress of sensor technology, underwater monitoring wireless sensor network (UMWSN) equipped with water resource monitoring capabilities have surfaced. UMWSN is currently emerging as a popular research and application area, with a wide range of applications in various fields, including but not limited to disaster warning, pollutant monitoring and hydrological data monitoring. However, due to the limited size and computing power of wireless sensors, UMWSN are exceedingly susceptible to network security attacks by contaminating entities. In order to tackle the problems of inadequate security, elevated network energy consumption, and high system latency in existing QoS routing research, this paper puts forward an innovative multi-objective routing protocol named multi-objective chaotic Boltzmann ant colony optimization routing protocol (MO-CBACORP). MO-CBACORP can minimize the energy consumption of sensor nodes in UMWSN routing, thereby effectively diminishing system latency and significantly enhancing routing security. During the routing optimization process, MO-CBACORP proposed an innovative design of the chaos operator and Boltzmann selection strategy, which effectively avoids the issue of being stuck in local optimal solutions and greatly enhances the convergence speed of the algorithm. Additionally, a novel experiment for underwater monitoring environments is presented that precisely replicates underwater monitoring conditions and attack scenarios. According to the experimental results, MO-CBACORP exhibits superior performance compared to the latest state-of-the-art research including THOA-MHR, ACO-MCMC, and MAP-ACO, with a minimum improvement of 7.25%, 9.31%, and 7.68% in terms of route security, network energy consumption, and delay, respectively. All in all, MO-CBACORP exhibits superior performance compared to the three latest research algorithms.

LSLPR: A Layering and Source-Location-Privacy-Based Routing Protocol for Underwater Acoustic Sensor Networks

LSLPR: A Layering and Source-Location-Privacy-Based Routing Protocol for Underwater Acoustic Sensor Networks

Secure and Energy-Based STEERA Routing Protocol for Wireless Sensor Networks

In wireless sensor networks (WSN), the multifunctional low-power sensor nodes are linked to base stations and are highly responsible for sensing various information. However, maintaining the network’s lifespan is a major issue because of limited battery capacity and node failures. Thus, the proposed study introduced a new Scalable Trust-based Energy Efficient Routing Algorithm (STEERA) with Adaptive Grasshopper Algorithm (AGA) to enhance the network lifespan. At first, the trust values (Tv) are generated for each node to eliminate the malicious node with the help of penalty factor and volatilization. To make efficient routing process, the nodes are formed into cluster groups. A suitable cluster head is selected for each cluster to mitigate the energy consumption problem through the AGA approach by optimizing the parameters like Tv, distance and residual energy. Finally, the data packets are effectively transmitted through a multi-hop routing process by selecting an appropriate path and satisfying certain parameters through Fire Hawks Optimization (FHO). To simulate the proposed techniques, NS2 software is employed, and the performance is measured over various metrics like energy consumption, residual energy, the lifespan of a network, packet loss ratio and average end-to-end delay. The performance analysis shows that the proposed protocol design has obtained higher results than conventional routing protocols.

CRLM: A cooperative model based on reinforcement learning and metaheuristic algorithms of routing protocols in wireless sensor networks

In wireless sensor networks, reasonable clustering and routing are keys to efficient energy utilization. However, the selection of cluster heads and routes is NP-hard. Most of the existing routing protocols use heuristic or metaheuristic optimization algorithms to solve this problem. Most protocols regard the selection of the cluster head and routing as two independent problems. However, the selection of cluster heads will affect the selection of routes, and there is a certain relationship between the two stages. Therefore, considering these two problems independently, the solution obtained is not necessarily the optimal solution in the network. In addition, most of the existing routing protocols are still subject to conventional clustering and conventional multi-hop communication in the network, which is extremely unfavorable for reducing the energy consumption of nodes. In this paper, we propose a cooperative model based on reinforcement learning and metaheuristic algorithms called CRLM, in which we use reinforcement learning to enhance the merit-seeking capability of the metaheuristic algorithm and use the algorithm to solve network communication schemes (clustering and routing are considered as one phase). The communication scheme also achieves load balancing of clusters within the network through pruning and employs a novel multi-hop model to reduce network energy waste. Compared to E-ALWO, ChOA-HGS, GATERP, GWO, IPSO-GWO, and LEACH, CRLM has 56%, 95%, 34.5%, 85.7%, 116.7%, and 140.7% improvements in network lifetime.

Navigating Routing Challenges in Internet of Things (IoT): A Focus on Routing Protocols and Wireless Sensor Networks

This paper states the routing issues in the Internet of Things (IoT). The main point of focus is especially on routing protocols in IoT and wireless sensor networks (WSN). “Everything which is connected to the internet is alive”, is going to be the new rule for the future. The future is the Internet of Things (IoT), the world is changing every day with new technologies and inventions. The Internet of Things (IoT) has known as a future scenario of technology in human life. IoT expands the concept of the Internet from a network of rather homogenous devices such as computers to a network of heterogeneous devices such as home appliances and the conventional network is mostly replaced with IoT. Devices are the main users of the IoT framework an important part is IEEE 802.15.4, a standard that operates at the PHY layer and MAC layer of IoT devices. The IoT Ecosystem includes a large number of integrated heterogeneous low-power, low-cost devices, and secure connections are needed between them [15]. They communicate with each other to gather, share and forward the information in a multi-hop manner, this requires a complex routing between them. WSN, new technology in the IoT system comprised of a large collection of sensors, a mesh network can be used to individually gather data and send data through a router to the internet in an IoT system [6]. an enormous number of sensors are used and its growth is also fast, they are collecting inexperienced data and transforming it into meaningful and useful information. considering the full usability of these devices and a huge number of them, produce routing challenges [16]. Routing in IoT is the most critical part because we are working with devices that have restricted device resources. the optimum goal is to have enhanced routing protocols and efficient performance with such limited resource devices [15, 18].

Adaptive Power-Controlled Depth-Based Routing Protocol for Underwater Wireless Sensor Networks

Low energy consumption has always been one of the core issues in the routing design of underwater sensor networks. Due to the high cost and difficulty of deployment and replacement of current underwater nodes, many underwater applications require the routing protocol design to consider the network lifetime extension problem. Based on this, we designed a new routing protocol that takes into account both low energy consumption and balanced energy consumption, and achieves effective extension of the network lifetime, called adaptive power-controlled depth-based routing protocol for underwater wireless sensor networks (APCDBRP). The protocol consists of two phases: (1) the route establishment phase and (2) the data transmission phase. In the route establishment phase, the initial path is established by the sink node broadcasting beacon packets at the maximum transmission power. The receiving nodes update their routing tables based on the beacon information and forward the beacon packets. In the data transmission phase, APCDBRP introduces a novel forwarding factor that considers both energy efficiency and energy balance. It selects the optimal next hop based on high energy efficiency and relatively abundant energy, thus extending the network’s lifetime. Additionally, APCDBRP proposes a new data protection and route reconstruction mechanism to address issues such as network topology changes due to node mobility and data transmission failures. Our simulation is based on AquaSim–Next Generation, which is a specialized tool built on the NS3 platform for researching underwater networks. Simulation results demonstrate that, compared to other typical routing protocols, APCDBRP exhibits superior performance in reducing network energy consumption and extending the network’s lifetime. It also achieves a high packet delivery rate with lower energy consumption.

Review study about Hierarchical Routing Protocol in wireless sensor networks

Wireless Sensor Networks (WSNs) are crucial in various applications, including smart homes, military surveillance, health monitoring, and environmental sensing. These networks consist of distributed sensor nodes that collect and transmit environmental data to a central location for processing. However, WSNs face challenges such as limited energy resources, scalability, complexity, security, fault tolerance, and quality of service. Researchers have proposed different routing protocols tailored to WSN characteristics to address these issues. This article comprehensively overviews WSN design issues, focusing on routing protocol classification and comparative analysis. Among the hierarchical protocols, LEACH (Low-Energy Adaptive Clustering Hierarchy) is highlighted as a prominent clustering-based protocol that reduces energy consumption by forming clusters and utilizing cluster heads for data aggregation. Each addresses specific challenges and enhances network performance. The comparative analysis evaluates the protocols based on energy efficiency, network lifetime, data delivery, scalability, and security. The findings help researchers, practitioners, and network designers select appropriate routing protocols for their specific WSN applications. This article offers valuable insights into WSN design issues and presents a comprehensive classification and comparison of routing protocols. By understanding the strengths and limitations of different protocols.

A novel routing protocol for underwater wireless sensor networks based on shifted energy efficiency and priority

Underwater Wireless Sensor Networks (UWSNs) are among the most promising research areas these days due to their unique characteristics and diverse underwater applications. Though a number of routing protocols have been designed and implemented for UWSNs over the past few years, the researchers face several challenges, e.g., low speed of propagation, small bandwidth, limited battery power, etc., while designing routing protocols for communication in UWSNs. Acoustic sensor nodes are equipped with batteries with limited power and it is quite costly to replace or recharge them. The network will not survive for the desired period of time if the power of node batteries is not efficiently used. To effectively resolve this issue, this paper proposes a Shifted Energy Efficiency and Priority (SHEEP) routing protocol for UWSNs. The proposed protocol aims to enhance the efficiency of the state-of-the-art Energy Balanced Efficient and Reliable Routing (EBER2) protocol for UWSNs. SHEEP is built upon the depth and energy of the current forwarding node, the depth of the expected next forwarding node, and the average energy difference among the expected forwarders. Simulation results demonstrate that SHEEP improves the energy efficiency and packet delivery ratio in comparison to EBER2 by 7.4% and 13% respectively.

HCPFRP: Heterogeneous cluster prediction and formation routing protocol for wireless sensor network

Wireless sensor network (WSN) is composed of multiple sensors that are connected through a communication channel and communicate with each other. As these sensor nodes are battery-operated, therefore, as a consequence, battery life or energy is always an issue of concern. Therefore, researchers focus their work on optimizing the routing strategies to save energy wastage in WSNs. Among all routing strategies, cluster-based techniques proved to be quite able to successfully manage propagation from sender to receiver. Because it must gather all data and send it to the base station, each cluster's elected head is responsible for bearing the complete load. A cluster-based routing mechanism is established under this paper and termed a Heterogeneous Cluster Prediction and Formation Routing Protocol (HCPFR) in which the algorithm first creates the cluster and predicts the energy utilization or network lifetime, and then provides energy-efficient optimized clustering. In this method, the proposed HCPFR model is compared with different methods; LEACH PSO, LEACH-GWO, LEACH-EEGWO, and FZR, and the performance is compared with different parameters mainly First Dead Node (FDN), Network Longevity (NL) and throughput (THP) in term of packet delivered and residual energy. The result shows that the HCPFR model outperforms better over these approaches. The FDN, NL, and THP of the proposed HCPFR are nearly 8000,10000, and 30000. Also, the suggested model shows that as the number of rounds increases the residual energy drops to 0.1 from 3.8 as the rounds increases to 10000 from 2000.