CAM

2013 ◽  
Vol 2 (4) ◽  
pp. 47-67
Author(s):  
Fady Medhat ◽  
Rabie A. Ramadan ◽  
Ihab Talkhan
Keyword(s):  
Solar Cell ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Clustering Algorithms ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fuzzy C Means ◽  
Power Resources ◽  
Research Areas ◽  
Limited Power

Sensor nodes of Wireless Sensor Network (WSN) possess very limited power resources normally a battery and a solar cell could exist in some cases, which requires efficient usage of these resources to extend the network's lifetime. Accordingly, several research areas have been investigated to prolong the network longevity, Clustering was proposed to WSN as one of these areas that could help in decreasing the amount of consumed energy. A number of clustering algorithms were devised but to the authors' knowledge, this is the first work to consider clustering in Multimodal WSN, where a node can report more than one feature e.g. temperature and humidity. We compared the two general clustering algorithms K-Mean and Fuzzy C-Means to LEACH-C and LEACH, which are two clustering algorithms specially designed for WSN. Fuzzy C-Means and K-Means showed better performance using the techniques proposed in this work over LEACH-C and LEACH.

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.

A Hybrid Approach of Fuzzy C-means Clustering and Neural network to make Energy-Efficient heterogeneous Wireless Sensor network

2016 ◽  
Vol 6 (2) ◽  
pp. 674 ◽  
Author(s):  
Amit Kumar Kaushik
Keyword(s):  
Neural Network ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Hybrid Approach ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fuzzy C Means ◽  
Heterogeneous Wireless Sensor Network ◽  
Fuzzy C Means Clustering

<span>The Wireless sensor network has been highly focused research area in recent times due to its wide applications and adaptability to different environments. The energy-constrained sensor nodes are always under consideration to increase their lifetime. In this paper we have used the advantages of two approaches i.e. fuzzy c-means clustering and neural network to make an energy efficient network by prolonging the lifetime of network. The cluster formation is done using FCM to form equally sized clusters in network and the decision of choosing cluster head is done using neural network having input distance from basestation, heterogeneity and energy of the node. Our Approach has successfully increased the lifetime and data capacity of the network and outperformed different approaches applied to the network present in literature. </span>

scholarly journals Zone-Based Routing Protocol for Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Muni Venkateswarlu Kumaramangalam ◽  
Kandasamy Adiyapatham ◽  
Chandrasekaran Kandasamy
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Hot Spot ◽  
Clustering Algorithms ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Unequal Clustering

Extensive research happening across the globe witnessed the importance of Wireless Sensor Network in the present day application world. In the recent past, various routing algorithms have been proposed to elevate WSN network lifetime. Clustering mechanism is highly successful in conserving energy resources for network activities and has become promising field for researches. However, the problem of unbalanced energy consumption is still open because the cluster head activities are tightly coupled with role and location of a particular node in the network. Several unequal clustering algorithms are proposed to solve this wireless sensor network multihop hot spot problem. Current unequal clustering mechanisms consider only intra- and intercluster communication cost. Proper organization of wireless sensor network into clusters enables efficient utilization of limited resources and enhances lifetime of deployed sensor nodes. This paper considers a novel network organization scheme, energy-efficient edge-based network partitioning scheme, to organize sensor nodes into clusters of equal size. Also, it proposes a cluster-based routing algorithm, called zone-based routing protocol (ZBRP), for elevating sensor network lifetime. Experimental results show that ZBRP out-performs interims of network lifetime and energy conservation with its uniform energy consumption among the cluster heads.

scholarly journals A Hybrid Approach of Fuzzy C-means Clustering and Neural network to make Energy-Efficient heterogeneous Wireless Sensor network

2016 ◽  
Vol 6 (2) ◽  
pp. 674
Author(s):  
Amit Kumar Kaushik
Keyword(s):  
Neural Network ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Hybrid Approach ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fuzzy C Means ◽  
Heterogeneous Wireless Sensor Network ◽  
Fuzzy C Means Clustering

<span>The Wireless sensor network has been highly focused research area in recent times due to its wide applications and adaptability to different environments. The energy-constrained sensor nodes are always under consideration to increase their lifetime. In this paper we have used the advantages of two approaches i.e. fuzzy c-means clustering and neural network to make an energy efficient network by prolonging the lifetime of network. The cluster formation is done using FCM to form equally sized clusters in network and the decision of choosing cluster head is done using neural network having input distance from basestation, heterogeneity and energy of the node. Our Approach has successfully increased the lifetime and data capacity of the network and outperformed different approaches applied to the network present in literature. </span>

scholarly journals System Lifetime and Performance Improvement in Wireless Sensor Networks by having Improved Energy Distributed Unequal Clustering Protocol

2021 ◽  
Author(s):  
Ashok T ◽  
Prabakaran R
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Clustering Algorithms ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Cluster Heads

Abstract Wireless Sensor Network (WSN) is becoming a very important area of research in today’s world and contributes a lot in the field of technology. Reducing energy consumption and improving the network lifetime is the key factor to be considered.Clustering provides an effective way for prolonging the lifetime of a wireless sensor network. Current clustering algorithms usually utilize two techniques, selecting cluster heads with more residual energy and rotating cluster heads periodically, to distribute the energy consumption among nodes in each cluster and extend the network lifetime. Also, it comprises various sensor nodes to detect different parameters. Among those non-replaceable batteries plays a greater part. Hence the system with such networks is essential that the sensor nodes consume as little energy as possible.To address the problem, we propose anovel model namely enhanced energy distributed unequal clustering which is mainly utilized for tackling energy consumption issues in multi-hop remote sensor systems. In the proposed method with an area of base station and energy are given significance as clustering parameters. Because of these parameters, diverse nodes are assigned. Here, another methodology has been proposed to enhance the working of EDUC, by electing cluster heads considering several nodes in the neighborhood. The incorporation of the area data for calculation of the opposition radii gives better adjusting of energy in correlation with the current methodology. The technique utilized is of holding similar bunches for a couple of rounds and is successful in decreasing the clustering overhead. The execution of the proposed convention has been assessed under three distinct scenarios and contrasted and existing conventions through reenactments. The outcomes demonstrate that the proposed plan beats the current conventions regarding system lifetime and performances in all the scenarios in terms of delay, energy consumption, packet loss ratio, and packet received ratio.

scholarly journals Relay Node Employment for Performance Enhancement of MEDC in Wireless Sensor Network

2020 ◽  
Vol 9 (6) ◽  
pp. 835-839
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Power Resources ◽  
Clustering Protocols

Wireless Sensor Network (WSN) is a combination of various small size processing units called sensors. Sensors are deployed over a region to monitor the environment and other happenings. Sensors sense the environmental situations and communicate the sensor data to nearby nodes or base stations. Sensor’s energy keeps on depleting due to their multiple functionalities like sensing, aggregating of received data and communication with neighbor nodes. Energy constraint is one of the vital challenges for sensor nodes as they are majorly operational in unreachable locations with non-replaceable power resources. Various techniques have been implemented to overcome the challenge of limited power resources. Clustering is one of the techniques that facilitate to prolong the network lifetime through effective utilization of energy resources. Numerous clustering protocols have been implemented based on various parameters. Mutual Exclusive Distributive Clustering (MEDC) is one of the distributed clustering protocols that elect the cluster head based on residual energy. Selected cluster head performs the dual functionality i.e. combining the collected data and sending the same to the base station. This paper present the proposed algorithm which employed relay nodes in MEDC to distribute the load of cluster head and the distribution would lead to further enhance the network lifetime of WSN.

An Effective Congestion Control Algorithm based on Traffic Assignment and Reassignment in Wireless Sensor Network

2020 ◽  
Vol 13 (8) ◽  
pp. 1166-1174
Author(s):  
Chao Wang
Keyword(s):  
Wireless Sensor Network ◽  
Congestion Control ◽  
Sensor Network ◽  
Traffic Assignment ◽  
Transmission Rate ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Detection ◽  
Detection Technology ◽  
Average Transmission

Background: It is important to improve the quality of service by using congestion detection technology to find the potential congestion as early as possible in wireless sensor network. Methods: So an improved congestion control scheme based on traffic assignment and reassignment algorithm is proposed for congestion avoidance, detection and mitigation. The congestion area of the network is detected by predicting and setting threshold. When the congestion occurs, sensor nodes can be recovery quickly from congestion by adopting reasonable method of traffic reassignment. And the method can ensure the data in the congestion areas can be transferred to noncongestion areas as soon as possible. Results: The simulation results indicate that the proposed scheme can reduce the number of loss packets, improve the throughput, stabilize the average transmission rate of source node and reduce the end-to-end delay. Conclusion: : So the proposed scheme can enhance the overall performance of the network. Keywords: wireless sensor network; congestion control; congestion detection; congestion mitigation; traffic assignment; traffic reassignment.

scholarly journals A Remote Monitoring System of Logistics Carrier Based on Wireless Sensor Network

2018 ◽  
Vol 14 (01) ◽  
pp. 4
Author(s):  
Wang Weidong
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Monitoring Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Remote Monitoring System ◽  
Monitoring Center

To improve the efficiency of the remote monitoring system for logistics transportation, we proposed a remote monitoring system based on wireless sensor network and GPRS communication. The system can collect information from the wireless sensor network and transmit the information to the ZigBee interpreter. The monitoring system mainly includes the following parts: Car terminal, GPRS transmission network and monitoring center. Car terminal mainly consists by the Zigbee microcontroller and peripherals, wireless sensor nodes, RFID reader, GPRS wireless communication module composed of a micro-wireless monitoring network. The information collected by the sensor communicates through the GPRS and the monitoring center on the network coordinator, sends the collected information to the monitoring center, and the monitoring center realizes the information of the logistics vehicle in real time. The system has high applicability, meets the design requirements in the real-time acquisition and information transmission of the information of the logistics transport vehicles and goods, and realizes the function of remote monitoring.

Handling Failures of Static Sensor Nodes in Wireless Sensor Network by Use of Mobile Sensors

2011 ◽  
Author(s):  
Edison Pignaton de Freitas ◽  
Tales Heimfarth ◽  
Ivayr Farah Netto ◽  
Carlos Eduardo Pereira ◽  
Armando Morado Ferreira ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Mobile Sensors ◽  
Wireless Sensor

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.

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