Central Base-Station Controlled Density Aware Clustering Protocol for wireless sensor networks

2009 ◽  
Author(s):  
Mst.Jannatul Ferdous ◽  
Jannatul Ferdous ◽  
Tanay Dey
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Base Station ◽  
Wireless Sensor ◽  
Clustering Protocol ◽  
Central Base

scholarly journals An Energy-Aware Method for Selecting Cluster Heads in Wireless Sensor Networks

2020 ◽  
Vol 10 (21) ◽  
pp. 7886
Author(s):  
Atefeh Rahiminasab ◽  
Peyman Tirandazi ◽  
M. J. Ebadi ◽  
Ali Ahmadian ◽  
Mehdi Salimi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Cluster Head ◽  
Base Station ◽  
Energy Resources ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dynamic Clustering ◽  
Clustering Protocol

Wireless sensor networks (WSNs) include several sensor nodes that have limited capabilities. The most critical restriction in WSNs is energy resources. Moreover, since each sensor node’s energy resources cannot be recharged or replaced, it is inevitable to propose various methods for managing the energy resources. Furthermore, this procedure increases the network lifetime. In wireless sensor networks, the cluster head has a significant impact on system global scalability, energy efficiency, and lifetime. Furthermore, the cluster head is most important in combining, aggregating, and transferring data that are received from other cluster nodes. One of the substantial challenges in a cluster-based network is to choose a suitable cluster head. In this paper, to select an appropriate cluster head, we first model this problem by using multi-factor decision-making according to the four factors, including energy, mobility, distance to centre, and the length of data queues. Then, we use the Cluster Splitting Process (CSP) algorithm and the Analytical Hierarchy Process (AHP) method in order to provide a new method to solve this problem. These four factors are examined in our proposed approach, and our method is compared with the Base station Controlled Dynamic Clustering Protocol (BCDCP) algorithm. The simulation results show the proposed method in improving the network lifetime has better performance than the base station controlled dynamic clustering protocol algorithm. In our proposed method, the energy reduction is almost 5% more than the BCDCP method, and the packet loss rate in our proposed method is almost 25% lower than in the BCDCP method.

scholarly journals An Improvement on Low-Energy Adaptive Clustering Hierarchy (Leach) Porotocol for Wireless Sensor Networks

2021 ◽  
Author(s):  
Negin Behboudi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Base Station ◽  
Wireless Sensor ◽  
Distance Threshold ◽  
Adaptive Clustering ◽  
Clustering Protocol ◽  
Piecewise Function ◽  
Energy Behavior

Based on LEACH, a new clustering protocol for wireless sensor networks is proposed and implemented. A new visualization method is also introduced. There are two outcomes from the implemented protocol. The first outcome is prolonged network lifetime. The second outcome is an increase in flexibility of the location of the base station. Another contribution of this thesis is development of a visualization tool that helps users to understand the energy behavior of the sensors in similar applications. The first outcome —prolonged network lifetime —are due to considering the distance of each node from the base station while clusters are formed. The energy dissipation for transmitting certain amount of data is defined as a piecewise function which is divided by certain distance threshold. A piece of this piecewise function is implemented in this work, which leads to increased flexibility in the location of the base station.

A Novel Energy-Efficient Clustering Protocol Using Two-Stage Genetic Algorithm for Improving the Lifetime of Wireless Sensor Networks

2020 ◽  
Vol 19 (03) ◽  
pp. 2050019
Author(s):  
Ali Mahani ◽  
Ebrahim Farahmand ◽  
Saeide Sheikhpour ◽  
Nooshin Taheri-Chatrudi
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Clustering Protocol ◽  
New Energy ◽  
Energy Efficient Clustering

Wireless sensor networks (WSNs) are beginning to be deployed at an accelerated pace, and they have attracted significant attention in a broad spectrum of applications. WSNs encompass a large number of sensor nodes enabling a base station (BS) to sense and transmit data over the area where WSN is spread. As most sensor nodes have a limited energy capacity and at the same time transmit critical information, enhancing the lifetime and the reliability of WSNs are essential factors in designing these networks. Among many approaches, clustering of sensor nodes has proved to be an effective method of reducing energy consumption and increasing lifetime of WSNs. In this paper, a new energy-efficient clustering protocol is implemented using a two-step Genetic Algorithm (GA). In the first step of GA, cluster heads (CHs) are selected, and in the second step, cluster members are chosen based on their distance to the selected CHs. Compared to other clustering protocols, the lifetime of WSNs in the proposed clustering is improved. This improvement is the consequence of the fact that this clustering considers energy efficient parameters in clustering protocol.

scholarly journals An Improvement on Low-Energy Adaptive Clustering Hierarchy (Leach) Porotocol for Wireless Sensor Networks

2021 ◽  
Author(s):  
Negin Behboudi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Base Station ◽  
Wireless Sensor ◽  
Distance Threshold ◽  
Adaptive Clustering ◽  
Clustering Protocol ◽  
Piecewise Function ◽  
Energy Behavior

Based on LEACH, a new clustering protocol for wireless sensor networks is proposed and implemented. A new visualization method is also introduced. There are two outcomes from the implemented protocol. The first outcome is prolonged network lifetime. The second outcome is an increase in flexibility of the location of the base station. Another contribution of this thesis is development of a visualization tool that helps users to understand the energy behavior of the sensors in similar applications. The first outcome —prolonged network lifetime —are due to considering the distance of each node from the base station while clusters are formed. The energy dissipation for transmitting certain amount of data is defined as a piecewise function which is divided by certain distance threshold. A piece of this piecewise function is implemented in this work, which leads to increased flexibility in the location of the base station.

scholarly journals NEW CLUSTERING SCHEMES FOR WIRELESS SENSOR NETWORKS

2010 ◽  
Vol 11 (1) ◽  
pp. 51-69
Author(s):  
S. M. Mazinani ◽  
J. Chitizadeh ◽  
M. H. Yaghmaee ◽  
M. T. Honary ◽  
F. Tashtarian
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Clustering Protocol

In this paper, two clustering algorithms are proposed. In the first one, we investigate a clustering protocol for single hop wireless sensor networks that employs a competitive scheme for cluster head selection. The proposed algorithm is named EECS-M that is a modified version to the well known protocol EECS where some of the nodes become volunteers to be cluster heads with an equal probability.  In the competition phase in contrast to EECS using a fixed competition range for any volunteer node, we assign a variable competition range to it that is related to its distance to base station. The volunteer nodes compete in their competition ranges and every one with more residual energy would become cluster head. In the second one, we develop a clustering protocol for single hop wireless sensor networks. In the proposed algorithm some of the nodes become volunteers to be cluster heads. We develop a time based competitive clustering algorithm that the advertising time is based on the volunteer node’s residual energy. We assign to every volunteer node a competition range that may be fixed or variable as a function of distance to BS. The volunteer nodes compete in their competition ranges and every one with more energy would become cluster head. In both proposed algorithms, our objective is to balance the energy consumption of the cluster heads all over the network. Simulation results show the more balanced energy consumption and longer lifetime.

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