scholarly journals ENHANCING ENERGY EFFICIENCY IN MOBILE ADHOC NETWORK USING AGGLOMERATIVE HIERARCHICAL CLUSTERING TECHNIQUE

2015 ◽  
Vol 3 (1) ◽  
pp. 27-35
Author(s):  
Kaliappan M ◽  
◽  
Dr. Paramasivan B ◽  
Keyword(s):  
Energy Efficiency ◽  
Hierarchical Clustering ◽  
Agglomerative Hierarchical Clustering ◽  
Clustering Technique ◽  
Mobile Adhoc Network ◽  
Adhoc Network

scholarly journals An Energy Efficient Clustering based Distributed Load Balancing Technique for Mobile Adhoc Networks

2019 ◽  
Vol 8 (9) ◽  
pp. 1869-1877
Keyword(s):  
Energy Efficiency ◽  
Load Balancing ◽  
Network Lifetime ◽  
Fault Tolerant ◽  
Mobile Nodes ◽  
Battery Lifetime ◽  
Mobile Adhoc Network ◽  
Distributed Load ◽  
Adhoc Network ◽  
Energy Efficient Clustering

In a mobile adhoc network (MANET), energy efficiency and mobility prediction are the two main challenging design issues due to the mobile nature of the nodes in any direction with limited battery lifetime, thus leads to adequate topology modifications. These two issues are mainly considered to maximize the lifetime of MANET. Load-balancing and reliable data transmission among the mobile nodes is mandatory to increase the network lifetime. To achieve this, clustering techniques can be employed to minimize the topology size and to aggregate the details related to the topology. In this paper, we introduce a new clustering based distributed load balancing (D-CALB) algorithm to maximize energy efficiency and network lifetime. Furthermore, a fault tolerant feature is included in the D-CALB algorithm, which maintains a secondary CH as a backup node in case of the failure of the present CH. The presented ZXCD- CALB algorithm has undergone an extensive set of experimentation under a varying number of nodes and speed. The detailed investigation of the experimental results verified the superior nature of the presented D-CALB algorithm over compared ones under several measures.

scholarly journals Hesitant Fuzzy Linguistic Agglomerative Hierarchical Clustering Algorithm and Its Application in Judicial Practice

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 370
Author(s):  
Shuangsheng Wu ◽  
Jie Lin ◽  
Zhenyu Zhang ◽  
Yushu Yang
Keyword(s):  
Hierarchical Clustering ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Agglomerative Hierarchical Clustering ◽  
Research Gaps ◽  
Judicial Practice ◽  
Linguistic Term ◽  
Clustering Effect ◽  
Hierarchical Clustering Algorithm ◽  
Fuzzy Linguistic

The fuzzy clustering algorithm has become a research hotspot in many fields because of its better clustering effect and data expression ability. However, little research focuses on the clustering of hesitant fuzzy linguistic term sets (HFLTSs). To fill in the research gaps, we extend the data type of clustering to hesitant fuzzy linguistic information. A kind of hesitant fuzzy linguistic agglomerative hierarchical clustering algorithm is proposed. Furthermore, we propose a hesitant fuzzy linguistic Boole matrix clustering algorithm and compare the two clustering algorithms. The proposed clustering algorithms are applied in the field of judicial execution, which provides decision support for the executive judge to determine the focus of the investigation and the control. A clustering example verifies the clustering algorithm’s effectiveness in the context of hesitant fuzzy linguistic decision information.

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