scholarly journals A New Centralized Clustering Algorithm for Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4391 ◽  
Author(s):  
Juan-Carlos Cuevas-Martinez ◽  
Antonio-Jesus Yuste-Delgado ◽  
Antonio-Jose Leon-Sanchez ◽  
Antonio-Jose Saez-Castillo ◽  
Alicia Triviño-Cabrera
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fuzzy System ◽  
Clustering Algorithm ◽  
Base Station ◽  
Wireless Sensor ◽  
Clustering Methods ◽  
Cluster Heads ◽  
Control Message ◽  
Message Exchange

Clustering is presently one of the main routing techniques employed in randomly deployed wireless sensor networks. This paper describes a novel centralized unequal clustering method for wireless sensor networks. The goals of the algorithm are to prolong the network lifetime and increase the reliability of the network while not compromising the data transmission. In the proposed method, the Base Station decides on the cluster heads according to the best scores obtained from a Type-2 Fuzzy system. The input parameters of the fuzzy system are estimated by the base station or gathered from the network with a careful design that reduces the control message exchange. The whole network is controlled by the base station in a rounds-based schedule that alternates rounds when the base station elects cluster heads, with other rounds in which the cluster heads previously elected, gather data from their contributing nodes and forward them to the base station. The setting of the number of rounds in which the Base Station keeps the same set of cluster heads is another contribution of the present paper. The results show significant improvements achieved by the proposal when compared to other current clustering methods.

scholarly journals A DISTRIBUTED ENERGY EFFICIENT CLUSTERING ALGORITHM FOR DATA AGGREGATION IN WIRELESS SENSOR NETWORKS

2018 ◽  
Vol 19 (1) ◽  
pp. 72-90
Author(s):  
Seyed Mohammad Bagher Musavi Shirazi ◽  
Maryam Sabet ◽  
Mohammad Reza Pajoohan
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Clustering Algorithm ◽  
Base Station ◽  
Wireless Sensor ◽  
Relay Nodes ◽  
Cluster Heads ◽  
Energy Efficient Clustering

Wireless sensor networks (WSNs) are a new generation of networks typically consisting of a large number of inexpensive nodes with wireless communications. The main purpose of these networks is to collect information from the environment for further processing. Nodes in the network have been equipped with limited battery lifetime, so energy saving is one of the major issues in WSNs. If we balance the load among cluster heads and prevent having an extra load on just a few nodes in the network, we can reach longer network lifetime. One solution to control energy consumption and balance the load among nodes is to use clustering techniques. In this paper, we propose a new distributed energy-efficient clustering algorithm for data aggregation in wireless sensor networks, called Distributed Clustering for Data Aggregation (DCDA). In our new approach, an optimal transmission tree is constructed among sensor nodes with a new greedy method. Base station (BS) is the root, cluster heads (CHs) and relay nodes are intermediate nodes, and other nodes (cluster member nodes) are the leaves of this transmission tree. DCDA balances load among CHs in intra-cluster and inter-cluster data communications using different cluster sizes. For efficient inter-cluster communications, some relay nodes will transfer data between CHs. Energy consumption, distance to the base station, and cluster heads’ centric metric are three main adjustment parameters for the cluster heads election. Simulation results show that the proposed protocol leads to the reduction of individual sensor nodes’ energy consumption and prolongs network lifetime, in comparison with other known methods. ABSTRAK: Rangkaian sensor wayarles (WSN) adalah rangkaian generasi baru yang terdiri daripada nod-nod murah komunikasi wayarles. Tujuan rangkaian-rangkaian ini adalah bagi mengumpul maklumat sekeliling untuk proses seterusnya. Nod dalam rangkaian ini dilengkapi bateri kurang jangka hayat, jadi simpanan tenaga adalah satu isu besar dalam WSN. Jika beban diimbang antara induk kelompok dan lebihan beban dihalang pada setiap rangkaian iaitu hanya sebilangan kecil nod pada tiap-tiap kelompok,  jangka hayat dapat dipanjangkan pada sesebuah rangkaian. Satu penyelesaian adalah dengan mengawal penggunaan tenaga dan mengimbangi beban antara nod menggunakan teknik berkelompok. Kajian ini mencadangkan kaedah baru pembahagian tenaga berkesan secara algoritma berkelompok bagi pembahagian data dalam WSN, dikenali sebagai Pembahagian Kelompok Kumpulan Data (DCDA). Melalui pendekatan baru ini, pokok transmisi optimum dibina antara nod sensor melalui kaedah baru. Stesen utama (BS) ialah akar, induk kelompok-kelompok (CHs) dan nod penyiar ialah nod perantara, dan nod-nod lain (nod-nod ahli kelompok) ialah daun bagi pokok trasmisi. DCDA mengimbangi beban CHs antara-kelompok dan dalam-kelompok komunikasi data daripada kelompok berbeza saiz. Bagi komunikasi berkesan dalam-kelompok, sebahagian nod penyampai akan memindahkan data antara CHs. Penggunaan tenaga, jarak ke stesen utama dan induk kelompok metrik sentrik adalah tiga parameter pelaras bagi pemilihan induk kelompok. Keputusan simulasi protokol yang dicadang menunjukkan pengurangan penggunaan tenaga pada nod-nod sensor individu dan memanjangkan jangka hayat rangkaian, berbanding kaedah-kaedah lain yang diketahui.

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.

Distributed Energy-Efficient Unequal Clustering Mechanism for Wireless Sensor Networks

2011 ◽  
Vol 186 ◽  
pp. 225-229
Author(s):  
Chang Jiang Jiang ◽  
Wei Ren Shi ◽  
Min Xiang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Base Station ◽  
Wireless Sensor ◽  
Distributed Energy ◽  
Unequal Clustering ◽  
Multihop Routing ◽  
Cluster Heads

Unequal clustering mechanism, in combination with inter-cluster multihop routing, provides a new effective way to balance the energy dissipation among nodes and prolong the lifetime of wireless sensor networks. In this paper, a distributed energy-efficient unequal clustering mechanism (DEEUC) is proposed and evaluated. By a time based competitive clustering algorithm, DEEUC partitions all nodes into clusters of unequal size, in which the clusters closer to the base station have smaller size. The cluster heads of these clusters can preserve some more energy for the inter-cluster relay traffic and the “hot-spots” problem can be avoided. For inter-cluster communication, DEEUC adopts an energy-aware multihop routing to reduce the energy consumption of the cluster heads. Simulation results demonstrate that the protocol can efficiently decrease the dead speed of the nodes and prolong the network lifetime

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.

An Energy-Efficient Unequal Clustering Algorithm in Wireless Sensor Networks

2012 ◽  
Vol 629 ◽  
pp. 801-807 ◽  
Author(s):  
Run Ze Wan ◽  
Jian Jun Lei ◽  
Qing Wei Xu ◽  
Xi Mei Gou
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Life Time ◽  
Base Station ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Cluster Heads

For wireless sensor networks, clustering algori-thms provides an effective way to prolong the life time using the multi-hop forwarding model. Nevertheless, they rarely consider the hot spots problem and the problem of unbalanced energy consumption among cluster heads. To solve the problems, we proposed an energy-efficient unequal clustering algorithm with the ideal of unequal clustering in the circle area where the cluster heads are in charge of different geographical scope according to different distance to the base station. Considering the cluster heads closer to the BS be burdened with heavy relay traffic, the cluster in inner layers, which is closer to the base station, is smaller than the outer layer. It could reduce the number of cluster members and lead to the proportional energy dissipation in each layer. Simulation results show that our algorithm improve energy utilization and prolonged the life of the entire Wireless Sensor Networks effectively.

K-Centers Clustering Protocol over Heterogeneous Wireless Sensor Networks

2014 ◽  
Vol 6 (4) ◽  
pp. 42-54
Author(s):  
Qing Yan Xie ◽  
Yizong Cheng ◽  
Qing-An Zeng
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Data Routing ◽  
Cluster Heads ◽  
Clustering Protocol ◽  
Heterogeneous Wireless Sensor Networks

This paper introduces a K-Centers clustering protocol for heterogeneous wireless sensor networks. Energy consumption is an important issue for wireless sensor networks, and sensor nodes consume most of their energy with data delivery. The energy needed to transmit data is proportional to the distance between sensor nodes and either cluster heads or a base station. Clustering is an efficient technique for saving energy and extending network life. The authors' protocol uses a K-centers clustering algorithm to alter the network, topology and establish data routing. The result is k cluster heads which accommodate the distribution of sensor nodes and achieve minimum maximum intra-cluster distances. Their simulations show that their algorithm will outperform K-Means under many but not all conditions. The authors' always produce better minimum maximum intra-cluster distances compared to K-means.

scholarly journals A Novel Framework to Secure CBWSNS Against the Selfishness Problem

2019 ◽  
Vol 7 (2) ◽  
pp. 7-16
Author(s):  
Poonam Mittal ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Defense Mechanism ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Security Level ◽  
Stochastic Algorithm ◽  
Worst Case ◽  
Cluster Heads

Dynamic and cooperative nature of sensor nodes in Wireless Sensor Networks raises question on security. Various researchers work in this direction to spot malicious, selfish and compromised nodes. Various mechanisms followed are uniqueness of clustering, reputation system and an operation at specific nodes. LEACH is a hierarchical protocol in which most nodes transmit to cluster heads, and the cluster heads aggregate and compress the data and forward it to the base station (sink). Each node uses a stochastic algorithm at each round to determine whether it will become a cluster head in this round. Clustering process carried out in two stages takes the role of the reputation scheme and reveals specific operation at CH, IN and MNs beside their usual activities in cluster based wireless sensor networks. This paper mentioned the final structure of the security framework, corresponding attacks and defense mechanism of the model. It also discusses various security level processes of wireless sensor networks. Results implies that in a cluster-based protocol such as LEACH in which optimally 5% of the nodes are cluster heads it is likely that a significant portion of the network can be paralyzed or the entire network disabled, in the worst-case scenario, if these cluster heads are compromised. Our main contribution in this paper is our novel approach in maintaining trusted clusters through a trust-based decision-making cluster head election algorithm.

scholarly journals A Lightweight Intrusion Detection Method Based on Fuzzy Clustering Algorithm for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Hongchun Qu ◽  
Libiao Lei ◽  
Xiaoming Tang ◽  
Ping Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Intrusion Detection ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Detection Method ◽  
Base Station ◽  
Simulation Software ◽  
Wireless Sensor ◽  
Sensor Monitoring

For resource-constrained wireless sensor networks (WSNs), designing a lightweight intrusion detection technology has been a hot and difficult issue. In this paper, we proposed a lightweight intrusion detection method that was able to directly map the network status into sensor monitoring data received by base station, so that base station can sense the abnormal changes in the network. Our method is highlighted by the fusion of fuzzy c-means algorithm, one-class SVM, and sliding window procedure to effectively differentiate network attacks from abnormal data. Finally, the proposed method was tested on the wireless sensor network simulation software EXata and in real applications. The results showed that the intrusion detection method in this paper could effectively identify whether the abnormal data came from a network attack or just a noise. In addition, extra energy consumption can be avoided in all sensor monitoring nodes of the sensor network where our method has been deployed.

scholarly journals Marine Observation Beacon Clustering and Recycling Technology Based on Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3726 ◽  
Author(s):  
Zhang ◽  
Qi ◽  
Li
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Minimum Weight ◽  
Recovery Phase ◽  
Base Station ◽  
Wireless Sensor ◽  
Fuzzy Membership Function ◽  
Dijkstra Algorithm

Monitoring of marine polluted areas is an emergency task, where efficiency and low-power consumption are challenging for the recovery of marine monitoring equipment. Wireless sensor networks (WSNs) offer the potential for low-energy recovery of marine observation beacons. Reducing and balancing network energy consumption are major problems for this solution. This paper presents an energy-saving clustering algorithm for wireless sensor networks based on k-means algorithm and fuzzy logic system (KFNS). The algorithm is divided into three phases according to the different demands of each recovery phase. In the monitoring phase, a distributed method is used to select boundary nodes to reduce network energy consumption. The cluster routing phase solves the extreme imbalance of energy of nodes for clustering. In the recovery phase, the inter-node weights are obtained based on the fuzzy membership function. The Dijkstra algorithm is used to obtain the minimum weight path from the node to the base station, and the optimal recovery order of the nodes is obtained by using depth-first search (DFS). We compare the proposed algorithm with existing representative methods. Experimental results show that the algorithm has a longer life cycle and a more efficient recovery strategy.

An Improved Clustering Algorithm Based on Coverage Area for Wireless Sensor Networks

2012 ◽  
Vol 542-543 ◽  
pp. 643-646
Author(s):  
Li Jun Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Topology Control ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Control Approach ◽  
Cluster Heads ◽  
Network Scalability

Clustering is an effective topology control approach in wireless sensor networks, which can increase network scalability and lifetime. A clustering algorithm based on the total number of neighbor nodes is proposed to maximize the lifetime of the network. The larger amount of neighbor nodes, the more chance a node has to be selected as a cluster head. Therefore, it can ensure the minimum cluster heads in the whole network. By closing the communication parts of cluster head to avoid selecting as cluster head in next epoch, the energy of the whole system is consumed symmetrically. The simulations demonstrate the effectiveness of the algorithm.

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