An optimal clustering mechanism based on Fuzzy-C means for wireless sensor networks

Su, Shengchao; Zhao, Shenghui

doi:10.1016/j.suscom.2017.08.001

Cited by 41 publications

(28 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Particle Swarm Optimization (PSO) are recently used to overcome problems of non-correlated clusters [10], [17]. It helps to prolong the life of WSN.…”

Section: Soft Computing Methods Like Fuzzy C-means Clustering (Fcm) mentioning

confidence: 99%

“…Nodes near sink are responsible to transmit data directly to sink even if they have low energy. ACEEC and THCEEC [9] are the centralized routing algorithms which results in better network lifetime as compared to the conventional distributed routing protocols like LEACH. The algorithm divides the whole network in regions which act as static clusters for WSN.…”

Section: Related Researchmentioning

confidence: 99%

“…Perfect-fusion, a simple technique has attracted many researchers' interest [2], [4]. LEACH (Low Energy Adaptive Clustering Hierarchy) [2], EEUC (Energy Efficient Unequal Clustering) [3], IB-LEACH (Intra-Balanced LEACH) [5], MR-LEACH (Multi-hop Routing LEACH) [6], MH-LEACH (Multi-Hop LEACH) [7], EMRP (Energy efficient multi-hop routing protocol) [8], ACEEC [9], OCM-FCM (Optimal Clustering Mechanism Fuzzy-C Means) [10], SEECP (Stable Energy Efficient Clustering Protocol) [11] and MLRC (Multi-Level Route-aware Clustering) [12] are some of the popular clustering protocols. In these protocols, all nodes in the network actively sense from the environment and continuously generate data.…”

Section: Introductionmentioning

confidence: 99%

“…The aim is to minimize the sum of distances between the SNs and the centroid of their cluster. OCM-FCM uses Fuzzy-C means clustering to form more uniform and correlated clusters in order to improve the lifetime of WSN [10].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Energy Efficient Algorithm for Wireless Sensor Network using Fuzzy C-Means Clustering

Jain¹,

Goel²

2018

ijacsa

View full text Add to dashboard Cite

Energy efficiency is a vital issue in wireless sensor networks. In this paper, an energy efficient routing algorithm has been proposed with an aim to enhance lifetime of network. In this paper, Fuzzy C-Means clustering has been used to form optimum number of static clusters. A concept of coherence is used to eliminate redundant data generation and transmission which avoids undue loss of energy. Intra-cluster and inter-cluster gateways are used to avoid nodes from transmitting data through long distances. A new strategy has been proposed to select robust nodes near sink for direct data transmissions. The proposed algorithm is compared with LEACH, MR-LEACH, MH-LEACH and OCM-FCM based upon lifetime, average energy consumption and throughput. From the results, it is confirmed that the performance of the proposed algorithm is much better than other algorithms and is more suitable for implementation in wireless sensor networks.

show abstract

“…Particle Swarm Optimization (PSO) are recently used to overcome problems of non-correlated clusters [10], [17]. It helps to prolong the life of WSN.…”

Section: Soft Computing Methods Like Fuzzy C-means Clustering (Fcm) mentioning

confidence: 99%

Section: Related Researchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Energy Efficient Algorithm for Wireless Sensor Network using Fuzzy C-Means Clustering

Jain¹,

Goel²

2018

ijacsa

View full text Add to dashboard Cite

show abstract

“…Main disadvantage is that it needs more computation time for clustering at initial stage. A consistent spatial CHs distribution and energy balance across the network is attained [21,25] using an energy efficient Fuzzy C means clustering. Nodes of the network are separated to specific set of clusters using fuzzy-C means algorithm.…”

Section: Literaturementioning

confidence: 99%

Network Lifetime Enhancement in WSN using Fuzzy Based Clustering Algorithm

D. L.*,

Prasanna

2020

IJITEE

View full text Add to dashboard Cite

These-days Wireless Sensor Networks (WSNs) has become integral part of many applications include tracking, monitoring and so on. Nodes are limited in battery, memory and processing capacity. Tracking and monitoring applications continue to work for longer hours; energy is the major constraint for network to transmit sensed data. State of the art specifies that by using clustering method energy-efficiency, scalability, and efficient-data-communication is achieved. Sensors deployed in the network be partitioned to clusters then one of the nodes is designated to become a Cluster Head (CH) that accumulate sensed information and sends to Sink/Base Station (BS). Normally CH is elected by considering nodes remaining energy and topological attributes related to the node in network. In this projected clustering method a centrality-metric “Cluster-Optimal-Degree-Centrality (CODC)”, is defined and also considered other parameters residual energy, distance between CHs, plus number of nodes belonging to a cluster guarantees better cluster configuration and CH selection. Fuzzy-Inference-System takes Expected-Residual-Energy (ERE) and CODC as inputs. Experiments are carried using ns-2; the proposed clustering method improves QoS, and efficiently prolongs network lifetime.

show abstract

A Threshold‐Based Optimization Energy‐Efficient Routing Technique in Heterogeneous Wireless Sensor Networks

Singh

2020

Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks

View full text Add to dashboard Cite

An optimal clustering mechanism based on Fuzzy-C means for wireless sensor networks

Cited by 41 publications

References 14 publications

Energy Efficient Algorithm for Wireless Sensor Network using Fuzzy C-Means Clustering

Energy Efficient Algorithm for Wireless Sensor Network using Fuzzy C-Means Clustering

Network Lifetime Enhancement in WSN using Fuzzy Based Clustering Algorithm

A Threshold‐Based Optimization Energy‐Efficient Routing Technique in Heterogeneous Wireless Sensor Networks

Contact Info

Product

Resources

About