The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Recentemente, vários algoritmos de agrupamento ponderado foram propostos, no entanto, até onde sabemos; não há nenhum que propague pesos para outros nós sem mensagem de peso para eleição de líder, normalize os parâmetros dos nós e considere os parâmetros dos nós vizinhos para calcular os pesos dos nós. Neste artigo, propomos um algoritmo Energy Efficient and Stable Weight Based Clustering (EE-SWBC) que elege os chefes do cluster sem enviar qualquer mensagem adicional de peso. Ele propaga os parâmetros do nó para seus vizinhos através da mensagem de descoberta de vizinhos (mensagem HELLO) e armazena esses parâmetros na lista de vizinhança. Cada nó normaliza parâmetros e calcula eficientemente seu próprio peso e os pesos dos nós vizinhos daquela tabela de vizinhança usando o Método de Decisão Gray (GDM). O GDM encontra a solução ideal (melhores parâmetros de nó na lista de vizinhança) e calcula os pesos dos nós em comparação com a solução ideal. O(s) nó(s) com peso máximo (parâmetros mais próximos da solução ideal) são eleitos como chefes do cluster. Como resultado, o EE-SWBC seleciona de forma justa nós potenciais com parâmetros mais próximos da solução ideal com menos sobrecarga. Diferentes métricas de desempenho de EE-SWBC e Distributed Weighted Clustering Algorithm (DWCA) são comparadas através de simulações. Os resultados da simulação mostram que o EE-SWBC mantém menos números médios de clusters estáveis com sobrecarga mínima, menos consumo de energia e menos alterações na estrutura do cluster dentro da rede em comparação com o DWCA.
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Safdar H. BOUK, Iwao SASASE, "Energy Efficient and Stable Weight Based Clustering for Mobile Ad Hoc Networks" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 9, pp. 2851-2863, September 2009, doi: 10.1587/transcom.E92.B.2851.
Abstract: Recently several weighted clustering algorithms have been proposed, however, to the best of our knowledge; there is none that propagates weights to other nodes without weight message for leader election, normalizes node parameters and considers neighboring node parameters to calculate node weights. In this paper, we propose an Energy Efficient and Stable Weight Based Clustering (EE-SWBC) algorithm that elects cluster heads without sending any additional weight message. It propagates node parameters to its neighbors through neighbor discovery message (HELLO Message) and stores these parameters in neighborhood list. Each node normalizes parameters and efficiently calculates its own weight and the weights of neighboring nodes from that neighborhood table using Grey Decision Method (GDM). GDM finds the ideal solution (best node parameters in neighborhood list) and calculates node weights in comparison to the ideal solution. The node(s) with maximum weight (parameters closer to the ideal solution) are elected as cluster heads. In result, EE-SWBC fairly selects potential nodes with parameters closer to ideal solution with less overhead. Different performance metrics of EE-SWBC and Distributed Weighted Clustering Algorithm (DWCA) are compared through simulations. The simulation results show that EE-SWBC maintains fewer average numbers of stable clusters with minimum overhead, less energy consumption and fewer changes in cluster structure within network compared to DWCA.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.2851/_p
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@ARTICLE{e92-b_9_2851,
author={Safdar H. BOUK, Iwao SASASE, },
journal={IEICE TRANSACTIONS on Communications},
title={Energy Efficient and Stable Weight Based Clustering for Mobile Ad Hoc Networks},
year={2009},
volume={E92-B},
number={9},
pages={2851-2863},
abstract={Recently several weighted clustering algorithms have been proposed, however, to the best of our knowledge; there is none that propagates weights to other nodes without weight message for leader election, normalizes node parameters and considers neighboring node parameters to calculate node weights. In this paper, we propose an Energy Efficient and Stable Weight Based Clustering (EE-SWBC) algorithm that elects cluster heads without sending any additional weight message. It propagates node parameters to its neighbors through neighbor discovery message (HELLO Message) and stores these parameters in neighborhood list. Each node normalizes parameters and efficiently calculates its own weight and the weights of neighboring nodes from that neighborhood table using Grey Decision Method (GDM). GDM finds the ideal solution (best node parameters in neighborhood list) and calculates node weights in comparison to the ideal solution. The node(s) with maximum weight (parameters closer to the ideal solution) are elected as cluster heads. In result, EE-SWBC fairly selects potential nodes with parameters closer to ideal solution with less overhead. Different performance metrics of EE-SWBC and Distributed Weighted Clustering Algorithm (DWCA) are compared through simulations. The simulation results show that EE-SWBC maintains fewer average numbers of stable clusters with minimum overhead, less energy consumption and fewer changes in cluster structure within network compared to DWCA.},
keywords={},
doi={10.1587/transcom.E92.B.2851},
ISSN={1745-1345},
month={September},}
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TY - JOUR
TI - Energy Efficient and Stable Weight Based Clustering for Mobile Ad Hoc Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 2851
EP - 2863
AU - Safdar H. BOUK
AU - Iwao SASASE
PY - 2009
DO - 10.1587/transcom.E92.B.2851
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 9
JA - IEICE TRANSACTIONS on Communications
Y1 - September 2009
AB - Recently several weighted clustering algorithms have been proposed, however, to the best of our knowledge; there is none that propagates weights to other nodes without weight message for leader election, normalizes node parameters and considers neighboring node parameters to calculate node weights. In this paper, we propose an Energy Efficient and Stable Weight Based Clustering (EE-SWBC) algorithm that elects cluster heads without sending any additional weight message. It propagates node parameters to its neighbors through neighbor discovery message (HELLO Message) and stores these parameters in neighborhood list. Each node normalizes parameters and efficiently calculates its own weight and the weights of neighboring nodes from that neighborhood table using Grey Decision Method (GDM). GDM finds the ideal solution (best node parameters in neighborhood list) and calculates node weights in comparison to the ideal solution. The node(s) with maximum weight (parameters closer to the ideal solution) are elected as cluster heads. In result, EE-SWBC fairly selects potential nodes with parameters closer to ideal solution with less overhead. Different performance metrics of EE-SWBC and Distributed Weighted Clustering Algorithm (DWCA) are compared through simulations. The simulation results show that EE-SWBC maintains fewer average numbers of stable clusters with minimum overhead, less energy consumption and fewer changes in cluster structure within network compared to DWCA.
ER -