scholarly journals Wireless Sensor Network routing for Life Time Maximization Using ANFIS Based Decision with Low Power Consumption

2021 ◽  
Vol 12 (2) ◽  
pp. 2893-2900
Author(s):  
N. Srinivas Rao, Et. al.
Keyword(s):  
Sensor Network ◽  
Network Performance ◽  
Cluster Head ◽  
Data Communication ◽  
Life Time ◽  
Network Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Micro Sensor ◽  
Routing Methods

Wireless sensor networks (WSNs) allocate thousands of cheap micro-sensor nodes to a hundreds to more than thousands of nodes in the reserved areas. In the WSN, sensor nodes control storage resources, calculating energy of nodes, power resources of nodes, and additional resources information on a sensor network. These micro-sensor nodes are key components of the Internet of Things (). WSNs are pre-arranged in clusters or groups to protect the ability for efficient data communication. Strong routing methods are required to maintain long network life and achieve high power usage. In this work, the new energy efficient ANFIS-based routing system for WSN enabled  to improve network performance. The proposed ANFIS-based routing involves a novel distributed clustering mechanism that activates the local configuration of local node energy equally across all sensors. A new technique for replacing clusters and rotating nodes with a centroid-based cluster head (CH) to distribute loads. The simulation results show that the proposed program will surpass conventional methods with 78% improvement over the lifetime of the network and 26% improvement in performance.

scholarly journals A Modified LEACH Protocol for Increasing Lifetime of the Wireless Sensor Network

2016 ◽  
Vol 16 (3) ◽  
pp. 154-164 ◽  
Author(s):  
S. Ananda Kumar ◽  
P. Ilango ◽  
Grover Harsh Dinesh
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Performance ◽  
Clustering Algorithm ◽  
High Reliability ◽  
Cluster Head ◽  
Life Time ◽  
Wireless Sensor ◽  
Average Value ◽  
Adaptive Clustering

Abstract Many studies have been proposed on clustering protocols for various applications in Wireless Sensor Network (WSN). The main objective of the clustering algorithm is to minimize the energy consumption, deployment of nodes, latency, and fault tolerance in network. In short high reliability, robustness and scalability can be achieved. Clustering techniques are mainly used to extend the lifetime of wireless sensor network. The first and foremost clustering algorithm for wireless sensor network was Low Energy Adaptive Clustering Hierarchy (LEACH). As per LEACH, some Cluster Head (CH) may have more nodes, some other may have less nodes, which affects the network performance. The proposed method MaximuM-LEACH provides a solution by load balancing the number of nodes equally by fixing the average value N, so the life time of the network is increased.

scholarly journals Enhancing the Performance of Wireless Sensor Networks thorugh Clustering and Joint Routing with Mobile Sink

2019 ◽  
Vol 8 (6) ◽  
pp. 323-327
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Optimal Solution ◽  
Life Time ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Traffic Characteristics ◽  
Routing Methods

In wireless sensor network, randomly deployed nodes are formed as a clusters of varying size for each area depending upon the numbers of users. This paper deals with the cluster based joint routing with mobile sink and with static sink in cognitive based wireless sensor network. The Joint Routing (JR) is designed to overcome the problems, due to data gatherings of the sensor nodes for any application. Channel resources usually may vary among the different routing methods based on the traffic characteristics and application they require, which poses a great challenge to guarantee time delivery services. These problems poses a great challenge for cognitive radio based WSN. The resource allocation technique overcomes the problems like spatial priority, time delay, transmission delay and energy loss and here the channel resources are allocated with the help of TDMA technique. The static sink in networks consumes more energy which results the early die out of the nodes. Hence throughput of the networks declines which badly affect the network life time. To overcome these issues, static sink is replaced by mobile sink, which consumes less energy, before each transmission in a sensor networks. The networks with mobile sink provide us optimal solution and performance as well, while comparing with network with static sink. It is shown that the proposed system achieves 15% of improved throughput, 20% of less packet loss and 35% of less delay when compare with the system having centralized sink.

Combination of improved Harris’s hawk optimization with fuzzy to improve clustering in wireless sensor network

2021 ◽  
pp. 1-16
Author(s):  
V. Nivedhitha ◽  
P. Thirumurugan ◽  
A. Gopi Saminathan ◽  
V. Eswaramoorthy
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Fuzzy Inference ◽  
Cluster Head ◽  
Data Communication ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Distance

A Wireless Sensor Network (WSN) is divided into groups of sensor nodes for efficient transmission of data from the point of measuring to sink. By performing clustering, the network remains energy-efficient and stable. An intelligent mechanism is needed to cluster the sensors and find an organizer node, the cluster head. The organizer node assembles data from its constituent nodes called member nodes, finds an optimal route to the sink of the network, and transfers the same. The nomination of cluster head is crucial since energy utilization is a major challenge of sensor nodes deployed over a hostile environment. In this paper, a fuzzy-based Improved Harris’s Hawk Optimization Algorithm (IHHO) is proposed to select an able cluster head for data communication. The fuzzy inference model ponders balance energy, distance from self to sink node, and vicinity of nodes from cluster head as input factors and decides if a candidate node is eligible for becoming a cluster head. The IHHO tunes the logic into an energy-efficient network with less complexity and more ease. The novelty of the paper lies in applying the hawk-pack technique based on fuzzy rules. Simulations show that the combination of Fuzzy based IHHO reduces the death of nodes through which network lifetime is enhanced.

scholarly journals Routing Algorithm using Fuzzy Logic Based Clustering with Mobile Sink for Wireless Sensor Network

2019 ◽  
Vol 8 (4) ◽  
pp. 4000-4005
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Life Time ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Node Degree

Minimization of the energy consumption in Wireless Sensor Network (WSN) is one of the most important area which has been explored by researchers through different methods. The use of non-stationary mobile sink has undoubtedly decreased the energy consumption within the sensor nodes and hence the life time of the system. Applying the Fuzzy Logic could effectively optimize the selection of Cluster Head. In this paper, Fuzzy Logic has been implemented for Cluster Head selection along with a mobile sink. The energy remaining in the sensor node, distance between the sink and the node, and the node degree are considered as the fuzzy inference variables. The life time of the node has been compared with the LEACH and Fuzzy logic based Clustering Combined with Mobile Sink (FCCMS) with mobile sink.

Performance Analysis of RNC Clustering Protocol in Wireless Sensor Network

2019 ◽  
Vol 10 ◽  
Author(s):  
Piyush Rawat ◽  
Siddhartha Chauhan
Keyword(s):  
Energy Consumption ◽  
Network Performance ◽  
Energy Levels ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Threshold Function ◽  
Efficient Manner ◽  
Clustering Protocol

Background and Objective: The functionalities of wireless sensor networks (WSN) are growing in various areas, so to handle the energy consumption of network in an efficient manner is a challenging task. The sensor nodes in the WSN are equipped with limited battery power, so there is a need to utilize the sensor power in an efficient way. The clustering of nodes in the network is one of the ways to handle the limited energy of nodes to enhance the lifetime of the network for its longer working without failure. Methods: The proposed approach is based on forming a cluster of various sensor nodes and then selecting a sensor as cluster head (CH). The heterogeneous sensor nodes are used in the proposed approach in which sensors are provided with different energy levels. The selection of an efficient node as CH can help in enhancing the network lifetime. The threshold function and random function are used for selecting the cluster head among various sensors for selecting the efficient node as CH. Various performance parameters such as network lifespan, packets transferred to the base station (BS) and energy consumption are used to perform the comparison between the proposed technique and previous approaches. Results and Discussion: To validate the working of the proposed technique the simulation is performed in MATLAB simulator. The proposed approach has enhanced the lifetime of the network as compared to the existing approaches. The proposed algorithm is compared with various existing techniques to measure its performance and effectiveness. The sensor nodes are randomly deployed in a 100m*100m area. Conclusion: The simulation results showed that the proposed technique has enhanced the lifespan of the network by utilizing the node’s energy in an efficient manner and reduced the consumption of energy for better network performance.

SE: A Simple and Efficient Strategy for Clustering and Routing in WSN

2014 ◽  
Vol 701-702 ◽  
pp. 1025-1028
Author(s):  
Yu Zhu Liang ◽  
Meng Jiao Wang ◽  
Yong Zhen Li
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocols ◽  
Information Needs ◽  
Network Performance ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Clustering Method ◽  
Position Information ◽  
Two Parameters

Clustering the sensor nodes and choosing the way for routing the data are two key elements that would affect the performance of a wireless sensor network (WSN). In this paper, a novel clustering method is proposed and a simple two-hop routing model is adopted for optimizing the network layer of the WSN. New protocol is characterized by simplicity and efficiency (SE). During the clustering stage, no information needs to be shared among the nodes and the position information is not required. Through adjustment of two parameters in SE, the network on any scale (varies from the area and the number of nodes) could obtain decent performance. This work also puts forward a new standard for the evaluation of the network performance—the uniformity of the nodes' death—which is a complement to merely taking the system lifetime into consideration. The combination of these two aspects provides a more comprehensive guideline for designing the clustering or routing protocols in WSN.

scholarly journals An Enhanced Clustering Method for Extending Sensing Lifetime of Wireless Sensor Network

2021 ◽  
pp. 67-82
Author(s):  
Yakubu Abdul-Wahab Nawusu ◽  
Alhassan Abdul-Barik ◽  
Salifu Abdul-Mumin
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Performance ◽  
Rank Order ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Heterogeneous Wireless Sensor Network

Extending the lifetime of a wireless sensor network is vital in ensuring continuous monitoring functions in a target environment. Many techniques have appeared that seek to achieve such prolonged sensing gains. Clustering and improved selection of cluster heads play essential roles in the performance of sensor network functions. Cluster head in a hierarchical arrangement is responsible for transmitting aggregated data from member nodes to a base station for further user-specific data processing and analysis. Minimising the quick dissipation of cluster heads energy requires a careful choice of network factors when selecting a cluster head to prolong the lifetime of a wireless sensor network. In this work, we propose a multi-criteria cluster head selection technique to extend the sensing lifetime of a heterogeneous wireless sensor network. The proposed protocol incorporates residual energy, distance, and node density in selecting a cluster head. Each factor is assigned a weight using the Rank Order Centroid based on its relative importance. Several simulation tests using MATLAB 7.5.0 (R2007b) reveal improved network lifetime and other network performance indicators, including stability and throughput, compared with popular protocols such as LEACH and the SEP. The proposed scheme will be beneficial in applications requiring reliable and stable data sensing and transmission functions.

Energy Efficient Image Compression and Transmission in WSN

2016 ◽  
pp. 67-78
Author(s):  
Wajeeha Aslam ◽  
Muazzam A. Khan ◽  
M. Usman Akram ◽  
Nazar Abbas Saqib ◽  
Seungmin Rho
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Image Compression ◽  
Sensor Network ◽  
Image Data ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life

Wireless sensor networks are greatly habituated in widespread applications but still yet step behind human intelligence and vision. The main reason is constraints of processing, energy consumptions and communication of image data over the sensor nodes. Wireless sensor network is a cooperative network of nodes called motes. Image compression and transmission over a wide ranged sensor network is an emerging challenge with respect to battery, life time constraints. It reduces communication latency and makes sensor network efficient with respect to energy consumption. In this paper we will have an analysis and comparative look on different image compression techniques in order to reduce computational load, memory requirements and enhance coding speed and image quality. Along with compression, different transmission methods will be discussed and analyzed with respect to energy consumption for better performance in wireless sensor networks.

The Design of WinCE Driver of WSN Nodes Based on ARM

2014 ◽  
Vol 556-562 ◽  
pp. 6058-6062 ◽  
Author(s):  
Jin Wu Ju
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Basic Structure ◽  
Network Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Node ◽  
Intelligent Sensor ◽  
Hardware Interface

Wireless sensor network (WSN) is the network which is composed of a large number of intelligent sensor nodes, it has the ability of self-organizing network routing, therefore, it has been widely used. Building wireless sensor networks is the key to WSN nodes. This paper introduces the basic structure of wireless sensor network node based on ARM, and it delivers a detailed analysis on the operating features and the CC2480 hardware interface of the ZigBee processor, what’s more, it specifically talks about the implementation of the Wince driver of WSN nodes.

scholarly journals Lifetime centric load balancing mechanism in wireless sensor network based IoT environment

2021 ◽  
Vol 11 (5) ◽  
pp. 4183
Author(s):  
Veerabadrappa Veerabadrappa ◽  
Booma Poolan Marikannan
Keyword(s):  
Wireless Sensor Network ◽  
Load Balancing ◽  
Sensor Network ◽  
Clustering Algorithms ◽  
Research Work ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Communication Overhead ◽  
Physical Parameters

Wireless sensor network (WSN) is a vital form of the underlying technology of the internet of things (IoT); WSN comprises several energy-constrained sensor nodes to monitor various physical parameters. Moreover, due to the energy constraint, load balancing plays a vital role considering the wireless sensor network as battery power. Although several clustering algorithms have been proposed for providing energy efficiency, there are chances of uneven load balancing and this causes the reduction in network lifetime as there exists inequality within the network. These scenarios occur due to the short lifetime of the cluster head. These cluster head (CH) are prime responsible for all the activity as it is also responsible for intra-cluster and inter-cluster communications. In this research work, a mechanism named lifetime centric load balancing mechanism (LCLBM) is developed that focuses on CH-selection, network design, and optimal CH distribution. Furthermore, under LCLBM, assistant cluster head (ACH) for balancing the load is developed. LCLBM is evaluated by considering the important metrics, such as energy consumption, communication overhead, number of failed nodes, and one-way delay. Further, evaluation is carried out by comparing with ES-Leach method, through the comparative analysis it is observed that the proposed model outperforms the existing model.

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