(SET) Smart Energy Management and Throughput Maximization

2017 ◽  
pp. 1-28 ◽  
Author(s):  
Hassan El Alami ◽  
Abdellah Najid
Keyword(s):  
Energy Management ◽  
Routing Protocols ◽  
Clustering Algorithm ◽  
Cluster Formation ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Base Station ◽  
Throughput Maximization ◽  
Cluster Heads ◽  
Smart Energy Management

Energy efficiency and throughput are critical factors in the design routing protocols of WSNs. Many routing protocols based on clustering algorithm have been proposed. Current clustering algorithms often use cluster head selection and cluster formation to reduce energy consumption and maximize throughput in WSNs. In this chapter, the authors present a new routing protocol based on smart energy management and throughput maximization for clustered WSNs. The main objective of this protocol is to solve the constraint of closest sensors to the base station which consume relatively more energy in sensed information traffics, and also decrease workload on CHs. This approach divides network field into free area which contains the closest sensors to the base station that communicate directly with, and clustered area which contains the sensors that transmit data to the base station through cluster head. So due to the sensors that communicate directly to the base station, the load on cluster heads is decreased. Thus, the cluster heads consume less energy causing the increase of network lifetime.

scholarly journals Design and performance evaluation of Improved DFACO protocol based on dynamic clustering in VANETs

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Sahar Ebadinezhad
Keyword(s):  
Performance Evaluation ◽  
Ant Colony Optimization ◽  
Routing Protocols ◽  
Clustering Algorithm ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Ant Colony ◽  
Minimum Number

AbstractThis study focuses on Vehicular Ad-hoc Networks (VANETs) stability in an environment that is dynamic which often leads to major challenges in VANETs, such as dynamic topology changes, shortest routing paths and also scalability. One of the best solutions for such challenges is clustering. In this study, we present five novel routing protocols based on Dynamic Flying Ant Colony Optimization (DFACO) algorithm to achieve minimum number of clusters, high accuracy, minimum time and solution cost by selecting the best cluster-head which is obtained from a new mechanism of dynamic metaheuristic-based clustering. In this regard, major improvements are applied on classical DFACO by adjusting the procedure for updating the pheromone and tuning the evaporation rate that has a major role in DFACO. In this research two individual phases of experiments are conducted for performance evaluation of proposed routing protocols. The presented solution is verified and compared to classic Ant Colony Optimization (ACO), DFACO and ACO Based Clustering Algorithm for VANET (CACONET) algorithms in phase one; and compared to clustering algorithms such as Center Position and Mobility CPM), Highest-Degree algorithm (HD), Angle-based Clustering Algorithm (ACA) in phase two through NS-2 and SUMO simulation tools. Simulation results have confirmed the expected behaviour and show that our proposed protocols achieve better node connectivity and cluster stability than the former.

An efficient clustering algorithm for wireless sensor networks

2015 ◽  
Vol 11 (3) ◽  
pp. 302-322 ◽  
Author(s):  
Mariam Alnuaimi ◽  
Khaled Shuaib ◽  
Klaithem Alnuaimi ◽  
Mohammed Abed-Hafez
Keyword(s):  
Network Lifetime ◽  
Duty Cycle ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Base Station ◽  
Energy Threshold ◽  
Content Type ◽  
Cluster Heads ◽  
Node Ranking

Purpose – This paper aims to propose a new node energy-efficient algorithm with energy threshold to replace cluster heads. The proposed algorithm uses node ranking to elect cluster heads based on energy levels and positions of the nodes in reference to the base station (BS) used as a sink for gathered information. Because the BS calculates the number of rounds a cluster head can remain for as a cluster head in advance, this reduces the amount of energy wasted on replacing cluster heads each round which is the case in most existing algorithms, thus prolonging the network lifetime. In addition, a hybrid redundant nodes duty cycle is used for nodes to take turn in covering the monitored area is shown to improve the performance further. Design/methodology/approach – Authors designed and implemented the proposed algorithm in MATLAB. The performance of the proposed algorithm was compared to other well-known algorithms using different evaluation metrics. The performance of the proposed algorithm was enhanced over existing ones by incorporating different mechanisms such as the use of an energy-based threshold value to replace CHs and the use of a hybrid duty-cycle on nodes. Findings – Through simulation, the authors showed how the proposed algorithm outperformed PEGASIS by 15 per cent and LEACH by almost 70 per cent for the network life-time criterion. They found that using a fixed pre-defined energy threshold to replace CHs improved the network lifetime by almost 15 per cent. They also found that the network lifetime can be further improved by almost 7 per cent when incorporating a variable energy threshold instead of a fixed value. In addition to that, using hybrid-redundant nodes duty-cycle has improved the network lifetime by an additional 8 per cent. Originality/value – The authors proposed an energy-efficient clustering algorithm for WSNs using node ranking in electing CHs and energy threshold to replace CHs instead of being replaced every round.

Clustering Algorithm to Reduce Power Consumptions for Wireless Sensor Networks

2012 ◽  
Vol 433-440 ◽  
pp. 5228-5232
Author(s):  
Mohammad Ahmadi ◽  
Hamid Faraji ◽  
Hossien Zohrevand
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Cluster Heads

A sensor network has many sensor nodes with limited energy. One of the important issues in these networks is the increase of the life time of the network. In this article, a clustering algorithm is introduced for wireless sensor networks that considering the parameters of distance and remaining energy of each node in the process of cluster head selection. The introduced algorithm is able to reduce the amount of consumed energy in the network. In this algorithm, the nodes that have more energy and less distance from the base station more probably will become cluster heads. Also, we use algorithm for finding the shortest path between cluster heads and base station. The results of simulation with the help of Matlab software show that the proposed algorithm increase the life time of the network compared with LEACH algorithm.

scholarly journals A Cognitive knowledged Energy-Efficient path selection using Centroid and Ant-Colony Optimized Hybrid protocol for WSN-Assisted IoT

2021 ◽  
Author(s):  
Prophess Raj Kumar Nalluri ◽  
Josemin Bala Gnanadhas
Keyword(s):  
Ant Colony Optimization ◽  
Energy Efficient ◽  
Cluster Formation ◽  
Cluster Head ◽  
Base Station ◽  
Path Selection ◽  
Ant Colony ◽  
Long Distance ◽  
Coverage Area ◽  
Cluster Heads

Abstract In WSN-assisted IoT environment, the sensors are resource constrained. The energy, computing and storage resources of deployed sensors in the sensing area are limited. Clustering is the key method for saving energy in wireless sensor networks. A hybrid protocol named as an Energy Efficient Centroid-based Ant colony Optimization (EECAO) protocol is proposed in this paper to improve the performance of the sensor network in WSN-assisted IoT environments. The protocol uses the concept of centroid based clustering to gather the information of local clusters and ant colony optimization to relay that information to the base station. proposed hybrid protocol includes multiple clustering factors such as energy cost, channel consistency and cognitive sensor throughput to select cluster heads and a new distributed cluster formation for self-organizing deployed sensors. Selection of the super cluster head among the cluster heads is based on the energy centroid position for a defined coverage area. In EECAO protocol, the energy level of cognitive sensors is the key parameter for defining the position of centroid. To reduce the long-distance communication, path optimization between the super cluster heads and the base station is carried out using an ant routing model. Our simulation results indicate that EECAO protocol performs better when benchmarked against existing ETSP and EECRP protocols. The proposed hybrid protocol EECAO is well-suited for networks that requires long lifetime when the base station is placed at either center, border or outside the network.

scholarly journals A Simple Ant Colony Optimization Algorithm to Select Cluster Heads in Ad Hoc Networks

2018 ◽  
Author(s):  
Mahboobeh Parsapoor ◽  
Urban Bilstrup
Keyword(s):  
Ad Hoc Networks ◽  
Ant Colony Optimization ◽  
Clustering Algorithm ◽  
Ad Hoc ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Cluster Heads ◽  
Hoc Networks

Forming a clustered network structure has been proposed as a solution to increase network performance, scalability, stability and manageability in an ad hoc network. A good clustering algorithm aims to select cluster heads among available nodes so that a number of specific constraints are satisfied; thus the cluster head selection problem is a multiobjective optimization problem. This paper proposes an algorithm on the basis of ant colony optimization (ACO) to be used to solve this problem. The proposed algorithm is a simple, one hop cluster formation algorithm, to form a clustered structure with the minimum number of clusters. The centralized ACO-based clustering algorithm is evaluated and compared with other clustering algorithms in ad hoc networks in terms of cluster density.

scholarly journals IMPROVED ARCHITECTURE FOR MAXIMIZING SYSTEM LIFETIME OF WIRELESS SENSOR NETWORK USING CLUSTERING ALGORITHM

2013 ◽  
pp. 143-146
Author(s):  
KANT KUMAR ADLAK ◽  
MANISH PANDEY
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Signal Transmission ◽  
Cluster Formation ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Energy Efficient Routing

Real time implementation of Ad-hoc Wireless Sensor Network has increased with great potential. Application areas of WSN’s are military warfare, disaster management, battle field, forest fire detection and other several monitoring area. Key challenge in WSN is to minimize the use of limited battery resources. Several energy efficient routing algorithms have been proposed till date. LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering protocol that divides the network into logical clusters and keeps rotating the cluster head selection to send data to sink. In this paper we propose a new technique of cluster formation based on organizational setup structure. New Network structure proposed will show an efficient increase in minimizing the node energy dissipation of signal transmission and will lead to maximize the system lifetime. We also propose a mix of Round-Robin algorithm into the cluster head selection for data transmission to base station. We compare the newly proposed clustering algorithm with the traditional LEACH algorithm.

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.

scholarly journals EZ-SEP: Extended Z-SEP Routing Protocol with Hierarchical Clustering Approach for Wireless Heterogeneous Sensor Network

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1021
Author(s):  
Zhanserik Nurlan ◽  
Tamara Zhukabayeva ◽  
Mohamed Othman
Keyword(s):  
Sensor Network ◽  
Hierarchical Clustering ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Cluster Head ◽  
Average Power ◽  
Base Station ◽  
Average Power Consumption ◽  
Clustering Approach ◽  
Heterogeneous Sensor Network

Wireless sensor networks (WSN) are networks of thousands of nodes installed in a defined physical environment to sense and monitor its state condition. The viability of such a network is directly dependent and limited by the power of batteries supplying the nodes of these networks, which represents a disadvantage of such a network. To improve and extend the life of WSNs, scientists around the world regularly develop various routing protocols that minimize and optimize the energy consumption of sensor network nodes. This article, introduces a new heterogeneous-aware routing protocol well known as Extended Z-SEP Routing Protocol with Hierarchical Clustering Approach for Wireless Heterogeneous Sensor Network or EZ-SEP, where the connection of nodes to a base station (BS) is done via a hybrid method, i.e., a certain amount of nodes communicate with the base station directly, while the remaining ones form a cluster to transfer data. Parameters of the field are unknown, and the field is partitioned into zones depending on the node energy. We reviewed the Z-SEP protocol concerning the election of the cluster head (CH) and its communication with BS and presented a novel extended mechanism for the selection of the CH based on remaining residual energy. In addition, EZ-SEP is weighted up using various estimation schemes such as base station repositioning, altering the field density, and variable nodes energy for comparison with the previous parent algorithm. EZ-SEP was executed and compared to routing protocols such as Z-SEP, SEP, and LEACH. The proposed algorithm performed using the MATLAB R2016b simulator. Simulation results show that our proposed extended version performs better than Z-SEP in the stability period due to an increase in the number of active nodes by 48%, in efficiency of network by the high packet delivery coefficient by 16% and optimizes the average power consumption compared to by 34.

Distance Density Based Clustering Algorithm in Wireless Sensor Network

2011 ◽  
Vol 291-294 ◽  
pp. 344-348
Author(s):  
Lin Lin ◽  
Shu Yan ◽  
Yi Nian
Keyword(s):  
Clustering Algorithm ◽  
Distribution Density ◽  
Simulation Experiment ◽  
Clustering Algorithms ◽  
Wireless Sensor ◽  
Energy Usage ◽  
Cluster Heads ◽  
Hierarchical Topology ◽  
Energy Factors ◽  
Density Based Clustering

The hierarchical topology of wireless sensor networks can effectively reduce the consumption in communication. Clustering algorithm is the foundation to realize herarchical structure, so it has been extensive researched. On the basis of Leach algorithm, a distance density based clustering algorithm (DDBC) is proposed, considering synthetically the distribution density of around nodes and the remaining energy factors of the node to dynamically banlance energy usage of nodes when selecting cluster heads. We analyzed the performance of DDBC through compared with the existing other clustering algorithms in simulation experiment. Results show that the proposed method can generare stable quantity cluster heads and banlance the energy load effectively.

scholarly journals GENETIC ALGORITHM-BASED CLUSTERING OF WIRELESS SENSOR NETWORK WITH NOVEL DATA ENCRYPTION

2017 ◽  
Vol 10 (13) ◽  
pp. 94
Author(s):  
Bachujayendra Kumar ◽  
Rajya Lakshmidevi K ◽  
M Verginraja Sarobin
Keyword(s):  
Genetic Algorithm ◽  
Energy Efficiency ◽  
Information Security ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Data Encryption ◽  
Base Station ◽  
Wireless Sensor ◽  
Clustering Techniques ◽  
Main Challenge

Wireless sensor networks (WSNs) have been used widely in so many applications. It is the most efficient way to monitor the information. There areso many ways to deploy the sensors. Many problems are not identified and solved. The main challenge of WSN is energy efficiency and information security. WSN power consumption is reduced by genetic algorithm-based clustering algorithm. Information from cluster head to base station may have a lot of chances to get hacked. The most reliable way to manage energy consumption is clustering, and encryption will suit best for information security. In this paper, we explain clustering techniques and a new algorithm to encrypt the data in the network.

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