WSN Routing Protocols Research Articles

An Energy Efficient Cross-Layer Cluster based Multipath Routing Protocol for WSN

Wireless sensor networks are the most widely used technologies with a wide range of applications and data collection processes. WSN is the major component for real-time data collection at various places where human intervention is difficult. With so many features, advantages, and impact WSN have some major challenges and hurdles, and these challenges the performance of the WSN is reducing and affecting the application part. This paper discusses the impact of WSN, and why WSN is gaining so much impact in recent days from a business perspective. A detailed survey and analysis made on the major challenges of WSN are carried out to identify the major performance factor of WSN. This paper aims to solve the major performance factor of WSN - power optimization, using novel cluster-based multipath routing. The proposed routing ensures the energy efficiency of the WSN for the data transfer process. Finally, the proposed method will be compared over some standard algorithms to analyze the performance in terms of the lifetime of the network and packet transmission by the sensor.

A Two-level clustering chain energy heterogeneous routing protocol for WSN

In view of the disadvantages of high energy consumption, short life cycle, low throughput and no application correlation in heterogeneous WSN, a two-level clustering chain routing protocol is proposed under the heterogeneous WSN of intelligent water-saving irrigation system of ecological agriculture in Hexi Gobi. The irrigation subnets are divides into clusters according to the actual layout in the wireless network and the nodes in the cluster form the chain on the basis of the minimum distance. The two-level cluster headers in reserve are selected by rate of the remaining energy of terminal nodes in cluster vs. average energy in local region. Eventually the level clusters heads and the two-level cluster headers are chosen according to the largest ratio of the remaining energy to the distance between the terminal nodes and the base station. Results in simulation show that the proposed algorithm is superior to PEGASIS and SEP in energy consumption, life cycle and throughput.

Congestion avoidance with source location privacy using octopus-based dynamic routing protocol in WSN

Congestion avoidance with source location privacy using octopus-based dynamic routing protocol in WSN

A Secure Trust Aware ACO-Based WSN Routing Protocol for IoT

A Secure Trust Aware ACO-Based WSN Routing Protocol for IoT

A new routing protocol for WSN using limit-based Jaya sail fish optimization-based multi-objective LEACH protocol: an energy-efficient clustering strategy

A new routing protocol for WSN using limit-based Jaya sail fish optimization-based multi-objective LEACH protocol: an energy-efficient clustering strategy

Design and Analysis of Soft Computing Based Improved Routing Protocol in WSN for Energy Efficiency and Lifetime Enhancement

Mobile wireless sensor networks have been developed as a result of recent advancements in wireless technologies. Sensors in the network are low-cost and have a short battery life, in addition to their mobility. They are more applicable in terms of the essential properties of these networks. These networks have a variety of uses, including search and rescue operations, health and environmental monitoring, and intelligent traffic management systems, among others. According to the application requirements, mobile wireless sensor nodes are energy limited equipment, so energy conservation is one of the most significant considerations in the design of these networks. Aside from the issues posed by sensor node mobility, we should also consider routing and dynamic clustering. According to studies, cluster models with configurable parameters have a substantial impact on reducing energy usage and extending the network's lifetime. As a result, the primary goal of this study is to describe and select a smart method for clustering in mobile wireless sensor networks utilizing evolutionary algorithms in order to extend the network's lifetime and ensure packet delivery accuracy. For grouping sensor nodes in this work, the Genetic Algorithm is applied initially, followed by Bacterial Conjugation. The simulation's results show a significant increase in clustering speed acceleration. The speed of the nodes is taken into account in the suggested approach for calibrating mobile wireless sensor nodes.

Reinforcement-Learning based energy efficient optimized routing protocol for WSN

Reinforcement-Learning based energy efficient optimized routing protocol for WSN

Energy Efficient Cluster Based Routing Protocol for WSN Using Firefly Algorithm and Ant Colony Optimization

Energy Efficient Cluster Based Routing Protocol for WSN Using Firefly Algorithm and Ant Colony Optimization

On an improved clustering algorithm based on node density for WSN routing protocol

On an improved clustering algorithm based on node density for WSN routing protocol

Markov model based dynamic chain routing protocol for grid WSN

Markov model based dynamic chain routing protocol for grid WSN

Machine Monitoring Protocols Based on Quality of Service (QoS) to Improve Performance of Real-Time Industrial Applications

A major factor in the optimization of real-time industrial applications is Quality of Service (QoS). There is also a quality-of-service parameter (QoS). Normally, dynamic networks require QoS settings for real-time applications. The industrial production environment is changing due to rapid advances in ICT. Industries have increased output due to improved manufacturing chain efficiency, flexibility, and security. Establishing a secure, reliable, and fast network in the sector is therefore critical. In industrial applications, data collection is an important factor to consider. Various routing methods exist for collecting data from industrial environments and sending it to processing. In this situation, the energy consumption of device nodes and data transmission delay are important factors to consider. This research proposes to construct an energy-efficient delay-aware WSN routing (EDR) protocol for defect detection. The clustering group optimal approach is used to identify which clusters should be selected. A modified task selection method is proposed to calculate the most efficient path between industrial areas and data centres (monitoring rooms). The node selection approach is used to find the network’s aggregate node. The Network Simulator (NS2) programmed is used to model the projected IEM-EDR system. The proposed Industrial Energy Monitoring-Energy-Efficient Delay-Aware Routing (IEM-EDR) system’s performance is compared to that of existing techniques in hop count, latency, energy consumption, throughput, and delivery rate.

EACR-LEACH: Energy-Aware Cluster-based Routing Protocol for WSN Based IoT

Internet of Things (IoT) is a recent paradigm to improve human lifestyle. Nowadays, number devices are connected to the Internet drastically. Thus, the people can control and monitor the physical things in real-time without delay. The IoT plays a vital role in all kind of fields in our world such as agriculture, livestock, transport, and healthcare, grid system, connected home, elderly people carrying system, cypher physical system, retail, and intelligent systems. In IoT energy conservation is a challenging task, as the devices are made up of low-cost and low-power sensing devices and local processing. IoT networks have significant challenges in two areas: network lifespan and energy usage. Therefore, the clustering is a right choice to prolong the energy in the network. In LEACH clustering protocol, sometimes the same node acts as CH again and again probabilistically. To overcome these issues, this paper proposes the Energy-Aware Cluster-based Routing (EACR-LEACH) protocol in WSN based IoT. The Cluster Head (CH) selection is a crucial task in clustering protocol in WSN based IoT. In EACR-LEACH, the CH is selected by using the routing metrics, Residual Energy (RER), Number of Neighbors (NoN), Distance between Sensor Node and Sink (Distance) and Number of Time Node Act as CH (NTNACH). An extensive simulation is conducted on MATLAB 2019a. The accomplishment of EACR-LEACH is compared to LEACH and SE-LEACH. The proposed EACR-LEACH protocol extends the network's lifetime by 4%–8% and boosts throughput by 16%–24%.

HELP-WSN-A Novel Adaptive Multi-Tier Hybrid Intelligent Framework for QoS Aware WSN-IoT Networks

Wireless Sensor Network is considered as the intermediate layer in the paradigm of Internet of things (IoT) and its effectiveness depends on the mode of deployment without sacrificing the performance and energy efficiency. WSN provides ubiquitous access to location, the status of different entities of the environment and data acquisition for long term IoT monitoring. Achieving the high performance of the WSN-IoT network remains to be a real challenge since the deployment of these networks in the large area consumes more power which in turn degrades the performance of the networks. So, developing the robust and QoS (quality of services) aware energy-efficient routing protocol for WSN assisted IoT devices needs its brighter light of research to enhance the network lifetime. This paper proposed a Hybrid Energy Efficient Learning Protocol (HELP). The proposed protocol leverages the multi-tier adaptive framework to minimize energy consumption. HELP works in a two-tier mechanism in which it integrates the powerful Extreme Learning Machines for clustering framework and employs the zonal based optimization technique which works on hybrid Whale-dragonfly algorithms to achieve high QoS parameters. The proposed framework uses the sub-area division algorithm to divide the network area into different zones. Extreme learning machines (ELM) which are employed in this framework categories the Zone's Cluster Head (ZCH) based on distance and energy. After categorizing the zone's cluster head, the optimal routing path for an energy-efficient data transfer will be selected based on the new hybrid whale-swarm algorithms. The extensive simulations were carried out using OMNET++-Python user-defined plugins by injecting the dynamic mobility models in networks to make it a more realistic environment. Furthermore, the effectiveness of the proposed HELP is examined against the existing protocols such as LEACH, M-LEACH, SEP, EACRP and SEEP and results show the proposed framework has outperformed other techniques in terms of QoS parameters such as network lifetime, energy, latency.

Fuzzy Butterfly Optimization Algorithm for Ring Cluster-based Routing Protocol for WSN

Fuzzy Butterfly Optimization Algorithm for Ring Cluster-based Routing Protocol for WSN

The DEEC And EDEEC Heterogeneous WSN Routing Protocols

The DEEC And EDEEC Heterogeneous WSN Routing Protocols

Enhancing Wireless Sensor Networks Routing Protocols based on Cross Layer Interaction

Wireless sensor networks aim to develop a smart city based on sensing environment. The routing protocols of wireless sensor networks is important to transfer the data in smart cities since sensor nodes have limited power and transmission range. The aim of this research is to enhance wireless sensor networks routing protocols based on proposed cross-layer interaction between physical layer and network layer also a proposed routing table information of wireless sensor nodes is developed to consider the transmission power of neighbor’s nodes to determine the next hop. Cross-layer interaction provides a useful information and effective adaptation for WSN routing protocols. As a result, the proposed routing protocol shows an improvement in network performance when number of intermediate nodes are minimized.

Enhanced WSN Routing Protocol for Internet of Things to Process Multimedia Big Data

Due to the massive use of wireless Internet of Things (IoT), the advent of multimedia-big-data in recent decades poses numerous obstacles for successful contact with the virtual era. Mobile Adhoc Network-based IoT (MANET IoT) framework is increasingly common in this regard owing to its increased communication protocols and economic efficiency. MANET comprises arbitrary, battery-driven, roaming nodes that do not have architecture that can handle the traffic and control the IoT network. In MANET-IoT, energy usage and traffic management for the handling of MBD information are significant issues. For rapid and precise response, it is essential to route or forward information like the locations of happenings and defected in a disaster. However, it is difficult to transfer this information to the Wireless Sensor Network in disaster areas because the current networks are a disaster that has been removed. In these situations, the transmission of opportunistic knowledge may play a vital role. Current opportunistic protocols need large messages for the restoration of the cluster that leads to more energy consumption and packet loss. To overcome these issues, this work proposes the reliable, energy-efficient opportunistic protocol known as Opportunistic Density Clustering Routing Protocol. This method sends information opportunistically in emergencies and disasters through a density-clustering protocol. Results from simulations demonstrate that the designed protocol exceeds several well-known current routing mechanisms for network energy usage and dissemination of information.

Performance evaluation of hierarchical clustering protocols with fuzzy C-means

The longevity of the network and the lack of resources are the main problems within the WSN. Minimizing energy dissipation and optimizing the lifespan of the WSN network are real challenges in the design of WSN routing protocols. Load balanced clustering increases the reliability of the system and enhances coordination between different nodes within the network. WSN is one of the main technologies dedicated to the detection, sensing, and monitoring of physical phenomena of the environment. For illustration, detection, and measurement of vibration, pressure, temperature, and sound. The WSN can be integrated into many domains, like street parking systems, smart roads, and industrial. This paper examines the efficiency of our two proposed clustering algorithms: Fuzzy C-means based hierarchical routing approach for homogeneous WSN (F-LEACH) and fuzzy distributed energy efficient clustering algorithm (F-DEEC) through a detailed comparison of WSN performance parameters such as the instability and stability duration, lifetime of the network, number of cluster heads per round and the number of alive nodes. The fuzzy C-means based on hierarchical routing approach is based on fuzzy C-means and low-energy adaptive clustering hierarchy (LEACH) protocol. The fuzzy distributed energy efficient clustering algorithm is based on fuzzy C-means and design of a distributed energy efficient clustering (DEEC) protocol. The technical capability of each protocol is measured according to the studied parameters.

Design Of Energy Efficient and Secure Routing Protocol for Wsn in Iot


 
 
 
 Abstract
 This paper proposes an energy-efficient and secure routing system for wireless sensor networks (WSNs) in the Internet of Things (IoT). The proposed routing protocol improves packet delivery ratio, end-to-end latency, and network lifetime over existing protocols. The protocol under consideration reduces node energy consumption, increasing the network's lifetime, while ensuring data security. Simulation studies using several metrics evaluate the proposed procedure. The recommended protocol outperforms existing protocols in energy efficiency and security. The protocol under discussion has several IoT applications, including smart agriculture, healthcare monitoring, and environmental monitoring. It ensures reliable and secure data transfer. This paper introduces a novel routing system that addresses energy saving and security in wireless sensor networks and the Internet of Things (IoT).
 
 
 

Comparative Study of Existing Hierarchical Based Routing Protocols for WSN

Comparative Study of Existing Hierarchical Based Routing Protocols for WSN