Energy-aware optimization of the number of clusters and cluster-heads in WSN

2012 ◽  
Author(s):  
Hesham Abusaimeh ◽  
Shuang-Hua Yang
Keyword(s):  
Energy Aware ◽  
Number Of Clusters ◽  
Cluster Heads

An Improvement Routing Protocol Based LEACH for Wireless Sensor Networks

2014 ◽  
Vol 614 ◽  
pp. 472-475 ◽  
Author(s):  
Jin Gang Cao
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Base Station ◽  
Optimal Number ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Number Of Clusters ◽  
Cluster Heads

Due to limited energy, computing ability, and memory of Wireless sensor Networks(WSN), routing issue is one of the key factors for WSN. LEACH is the first clustering routing protocol, which can efficiently reduce the energy consumption and prolong the lifetime of WSN, but it also has some disadvantage. This paper proposed an improvement based LEACH, called LEACH-T. According to different number of clusters, LEACH-T uses variable time slot for different clusters in steady-state phase, and single-hop or multi-hop to transmit data between cluster heads and Base Station. Also it considered residual energy of sensor nodes and the optimal number of clusters during selection of the cluster heads. The simulation results show that LEACH-T has better performance than LEACH for prolonging the lifetime and reducing the energy consumption.

scholarly journals Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
E. Golden Julie ◽  
S. Tamil Selvi
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Energy Consumption ◽  
Network Lifetime ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Cluster Heads ◽  
Clustering Protocol ◽  
Neuro Fuzzy

Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.

Low Loss Energy-Aware Routing Protocol for Data Gathering Applications in Wireless Sensor Network

2012 ◽  
pp. 272-302
Author(s):  
Basma M. Mohammad El-Basioni ◽  
Sherine M. Abd El-Kader ◽  
Hussein S. Eissa ◽  
Mohammed M. Zahra
Keyword(s):  
Routing Protocol ◽  
Packet Loss ◽  
Data Gathering ◽  
Wireless Sensor ◽  
Low Loss ◽  
Energy Aware ◽  
Cluster Heads ◽  
Energy Aware Routing ◽  
Quality Of Service Parameters

But, as the energy-efficiency is critical for periodical data gathering applications in wireless sensor networks, it has the highest priority in algorithms design; also the latency, packet loss, and throughput are important factors and should be addressed. This chapter proposes a routing protocol inspired by an energy-efficient cluster-based routing protocol called Energy-Aware Routing Protocol (EAP). The new enhanced protocol that is called Low Loss Energy-Aware Routing Protocol (LLEAP) enhances the performance of EAP in terms of some quality of service parameters by adding a second iteration for constructing the tree structure for multi-hop communication among cluster heads, by modifying the used weights of the cluster heads and parent node selection, and finally by selecting suitable aggregation method to decrease losses and delay. Simulation results showed that LLEAP significantly outperforms EAP in terms of packet loss percentage by on average 93.4%.

Cluster Analysis of Antigenic Profiles of Tumors: Selection of Number of Clusters Using Akaike’s Information Criterion

1990 ◽  
Vol 29 (03) ◽  
pp. 200-204 ◽  
Author(s):  
J. A. Koziol
Keyword(s):  
Cluster Analysis ◽  
Basic Problem ◽  
Information Criterion ◽  
Akaike's Information Criterion ◽  
Cell Surface Antigens ◽  
Number Of Clusters ◽  
Akaike’S Information Criterion ◽  
Multinomial Data ◽  
Tumor Types ◽  
Selection Of

AbstractA basic problem of cluster analysis is the determination or selection of the number of clusters evinced in any set of data. We address this issue with multinomial data using Akaike’s information criterion and demonstrate its utility in identifying an appropriate number of clusters of tumor types with similar profiles of cell surface antigens.

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