E2MR-HOA: Conservation of Energy through Multi-Hop Routing Protocol for WSN'S Using Hybrid Optimization Algorithm

2020 ◽  
pp. 2150041
Author(s):  
G. Kumaran ◽  
C. Yaashuwanth
Keyword(s):  
Energy Efficiency ◽  
Routing Protocol ◽  
Optimization Algorithm ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Hybrid Optimization ◽  
Conservation Of Energy ◽  
Hybrid Optimization Algorithm ◽  
Reaction Optimization ◽  
Border Surveillance

Consuming energy at the maximal level is a major concern in wireless sensor networks (WSNs). Many researchers focus on reducing and preserving the energy. The duration of active network of WSNs is affected by energy consumption of sensor nodes. For typical applications such as structure monitoring, border surveillance, integrated into the external surface of a pipeline, and clambered along the sustaining structure of a bridge, sensor node energy efficiency is an important issue. The paper proposed an energy-efficient multi-hop routing protocol using hybrid optimization algorithm (E2MR-HOA) for WSNs. The proposed routing protocol consists of two algorithms, i.e., hybrid optimization algorithm. We present modified chemical reaction optimization (MCRO) algorithm to form clusters and select cluster head (CH) among the cluster members. Then the modified bacterial forging search (MBFS) algorithm is used to compute reliable route between source to destination. The proposed E2MR-HOA protocol is evaluated using NS2 simulations. The simulation result shows that the proposed routing protocol provides significant energy efficiency with network lifetime over the existing routing protocols.

Adaptive neural network with hybrid optimization oriented localization in wireless sensor network: A multi-objective model

2020 ◽  
pp. 2050064
Author(s):  
P. Purusothaman ◽  
M. Gunasekaran
Keyword(s):  
Neural Network ◽  
Optimization Algorithm ◽  
Sensor Node ◽  
Optimization Algorithms ◽  
Sensor Nodes ◽  
Hybrid Optimization ◽  
Wireless Sensor ◽  
Hybrid Optimization Algorithm ◽  
Localization Model ◽  
Anchor Nodes

The localization strategy is broadly utilized in Wireless Sensor Networks (WSNs) to detect the present location of the sensor nodes. A WSN comprises of multiple sensor nodes, which makes the employment of GPS on each sensor node costly, and GPS does not give accurate localization outcomes in an indoor environment. The process of configuring location reference on each sensor node manually is also not feasible in the case of a large dense network. Hence, this proposal plans to develop an intelligent model for developing localization pattern in WSN with a group of anchor nodes, rest nodes, and target nodes. The initial step of the proposed node localization model is the selection of the optimal location of anchor nodes towards the target nodes using the hybrid optimization algorithm by concerning the constraints like the distance between the nodes. The second step is to optimally determine the location of the rest node by reference to the anchor nodes using the same hybrid optimization algorithm. Here, the weight has to be determined for each anchor sensor node based on its Received Signal Strength (RSS), and RSS threshold value with the assistance of Neural Network. The hybrid optimization algorithms check the direction to where the concerned node has to be moved by merging the beneficial concepts of two renowned optimization algorithms named as Rider Optimization Algorithm (ROA), and Chicken Swarm Optimization Algorithm (CSO) to solve the localization problem in WSN. The newly developed hybrid algorithm is termed as Rooster Updated Attacker-based ROA (RUA-ROA). Finally, the comparative evaluation indicates a significant improvement in the proposed localization model by evaluating the convergence and statistical analysis.

scholarly journals Energy Threshold-based Cluster Head Rotation for Routing Protocol in Wireless Sensor Networks

2018 ◽  
Vol 26 (7) ◽  
pp. 92-106
Author(s):  
Hadi Raheem Ali ◽  
Hussein Attia Lafta
Keyword(s):  
Energy Efficiency ◽  
Routing Protocol ◽  
Cluster Head ◽  
Head Rotation ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Energy Distance ◽  
Cluster Head Rotation

Energy efficiency represents a fundamental issue in WSNs, since the network lifetime period entirely depends on the energy of sensor nodes, which are usually battery-operated. In this article, an unequal clustering-based routing protocol has been suggested, where parameters of energy, distance, and density are involved in the cluster head election. Besides, the sizes of clusters are unequal according to distance, energy, and density. Furthermore, the cluster heads are not changed every round unless the residual energy reaches a specific threshold of energy. The outcomes of the conducted simulation confirmed that the performance of the suggested protocol achieves improvement in energy efficiency.

A Hybrid Optimization Algorithm on Cluster Head Selection to Extend Network Lifetime in WSN

2020 ◽  
pp. 7-18
Author(s):  
Sim Sze Yin ◽  
Yoni Danieli
Keyword(s):  
Network Lifetime ◽  
Optimization Algorithm ◽  
Data Dissemination ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Cluster Head Selection ◽  
Energy Aware ◽  
Hybrid Optimization Algorithm ◽  
Energy Sensor

Wireless Sensor Networks (WSNs) comprise of a number of sensor nodes that are capable of sensing and aggregating the data from the monitoring environment. However, the process of recharging the limited energy sensor node batteries are highly difficult during adverse situations. This limitation of sensor nodes greatly crumbles the network lifetime to a maximum degree and degrades the level of reliable data dissemination. In this paper, a Novel Individual Updating Strategies-based Hybrid Elephant Herding Optimization Algorithm (NIUS-HEHOA) is planned for facilitating energy balanced cluster head selection for the objective of extending the network lifetime. It included energy-aware optimization process during the clustering schemes, since it is considered as a solution to the significant NP complete optimization problem. It is propounded as a swarm intelligent algorithms are identified to be the most applicable candidate for energy optimization that leads to significant improvement in network lifetime. It is contributed to maintain the deviation between exploitation and exploration such that least potential sensor nodes are prevented from being chosen as cluster heads. The simulation experiments confirmed that the proposed NIUSHEHOA scheme is better than the benchmarked schemes in terms of alive nodes, dead nodes, residual energy, network lifetime and throughput.

Minimizing Energy Consumption in Wireless Sensor Networks by Partition

2016 ◽  
Vol 850 ◽  
pp. 23-29
Author(s):  
Wen Zhi Zhu ◽  
Feng Xu
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Clustering Methods ◽  
Improve Energy Efficiency

In wireless sensor networks, clustering class routing protocol is an important protocol type. Different clustering methods, and cluster head selection method directly affects the energy consumption of the entire network communication. This paper studies the effect of different partition methods of the network energy consumption, and to study the partitioning methods under the conditions of uneven distribution of nodes. We believe that energy efficiency clustering method should adapt the distributed of sensor nodes in order to improve energy efficiency. And according to the partition method we propose a low-power adaptive clustering routing protocol based on node distribution to partition. The protocol can effectively extend the lifetime of a wireless sensor network. Simulation results show that the proposed protocol can effectively prolong the network lifetime.

scholarly journals An energy efficient optimized cluster establishment methodology for sensor nodes in WSN

2021 ◽  
Vol 21 (3) ◽  
pp. 1548
Author(s):  
Shivshanker Biradar ◽  
T. S. Vishwanath
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Cluster Head ◽  
Average Energy ◽  
Optimal Solution ◽  
Sensor Nodes ◽  
Battery Life ◽  
Direct Transmission ◽  
Conservation Of Energy ◽  
Selection Of

<span>The compatibility of WSN is with various applications such as; healthcare and environmental monitoring. Whereas nodes present in that network have limited ‘battery-life’ that cause difficulty to replace and recharge those batteries after deployment. Energy efficiency is a major problem in the present situation. In present, many algorithms based on energy efficiency have been introduced to improvise the conservation of energy in WSN. The LEACH algorithm improvises the network lifetime in comparison to direct transmission and multi-hop, but it has several limitations. The selection of CHs can be randomly done that doesn’t confirm the optimal solution, proper distribution and it lacks during complete network management. The centralized EE optimized cluster establishment approach (OCEA) for sensor nodes is proposed to decrease the average energy dissipation and provide significant improvement. The proposed EE WSN model with the sensor nodes is examined under a real-time scenario and it is compared with state-of-art techniques where it balances the energy consumption of the network and decreasing the cluster head number.</span>

scholarly journals Data Transmission Direction Based Routing Algorithm for Improving Network Performance of IoT Systems

2020 ◽  
Vol 10 (11) ◽  
pp. 3784
Author(s):  
Kyeong Mi Noh ◽  
Jong Hyuk Park ◽  
Ji Su Park
Keyword(s):  
Energy Efficiency ◽  
Routing Protocol ◽  
Data Transmission ◽  
Sensor Node ◽  
Network Performance ◽  
Cluster Head ◽  
Sensor Nodes ◽  
The Internet ◽  
Leach Protocol ◽  
Transmission Direction

With the continuous development of wireless communication technology, the Internet of Things (IoT) is being used in a wide range of fields. The IoT collects and exchanges large amounts of data with objects, either tangible or intangible, such as sensors or physical devices, connected to the Internet. Wireless sensor networks (WSNs) are components of IoT systems. WSNs are used in various IoT systems, such as monitoring, tracking, and detection systems, to extract relevant information and deliver it to users. WSNs consist of sensor nodes with low power, low cost, and multiple functions. Because sensor nodes have limited resources, such as power and memory, a reduction in the energy efficiency of the sensor nodes in WSNs will lead to a decrease in wireless network performance and an increase in packet loss, which affects IoT system performance. Therefore, this study aimed to find an energy-efficient routing method that extends the lifetime of WSNs by minimizing the battery use of sensor nodes to improve the network performance of IoT systems. Conserving energy from sensor nodes and increasing network throughput in WSNs involves having protocols. The low-energy adaptive clustering hierarchy (LEACH ) protocol is a well-known hierarchical routing protocol in WSNs that constructs clusters and transmits data. LEACH increases energy efficiency by transmitting data from sensor nodes to the base station (BS) through the cluster head. It is widely adopted in the WSN network field, and many protocols are being studied to improve cluster header selection and data transmission to increase the energy efficiency of sensor nodes. In this study, we attempted to improve energy efficiency by removing unnecessary energy from LEACH. In LEACH, when the sensor node is located between the BS and the cluster head, the sensor node transmits data to the cluster head in the opposite direction of the BS. The data sent to the cluster head are transmitted in the direction of the BS. Thus, transmission in the opposite direction consumes unnecessary energy and affects the WSN performance of IoT systems. In this study, we propose a D-LEACH (direction-based LEACH) protocol based on the received signal strength indicator (RSSI) that improves the efficiency of transmission energy considering the data transmission direction of sensor nodes. D-LEACH aims to balance the energy of the sensor nodes and improve the performance of WSNs in the IoT system by reducing unnecessary energy consumption caused by reverse transmission considering the data transmission direction of the sensor nodes. In the course of the paper, we refer to the routing protocol of WSNs to improve network performance and describe LEACH. We also explain the D-LEACH protocol proposed in this paper and confirm the performance improvement of WSNs in an IoT system through simulation.

An energy-efficient and novel populated cluster aware routing protocol (PCRP) for wireless sensor networks (WSN)

2020 ◽  
Vol 39 (6) ◽  
pp. 8529-8542
Author(s):  
M. Martinaa ◽  
B. Santhi ◽  
A. Raghunathan
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Level ◽  
Routing Protocol ◽  
Cluster Formation ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor

Wireless Sensor Networks (WSNs) is created, stemming from their applications in distinct areas. Huge sensor nodes are deployed in geographically isolated regions in WSN. As a result of uninterrupted transmission, the energy level of the nodes gets rapidly depleted. Sensor node batteries cannot be replaced or recharged often and maintaining the energy level is a crucial issue. Thus energy efficiency is the significant factor to be consider in WSN. This paper focuses to implement an efficient clustering and routing protocols for maximized network lifetime. Clustering has been confirmed as a successful approach in network organization. The fundamental responsibilities of the clustering mechanism include improved energy efficiency and extended network lifespan. In this work, energy efficiency is improved to maximize lifespan of the WSN by proposing a novel method known as the Populated Cluster aware Routing Protocol (PCRP). The proposed method comprises three different steps: cluster formation, cluster head selection, and multi-hop data transmission. All sensor nodes are joined to a Cluster Head in a single hop in the cluster formation phase. Node distance is calculated and from which cluster head is selected. Then, cluster head aggregates the data from sensor nodes and transfer to the Base Station (BS). The shortest pathway is estimated by the Energy Route Request Adhoc On-demand Distance Vector (ERRAODV) algorithm. The proposed method considers the residual energy involved to attain high energy efficiency and network stability. The experimental analysis is demonstrated to validate the proposed method with existing, which improves the network lifespan. Vital parameters are validated using Network Simulator (NS2).

Sign in / Sign up

Export Citation Format

Share Document