IGBDD: Intelligent Grid Based Data Dissemination Protocol for Mobile Sink in Wireless Sensor Networks

2014 ◽  
Vol 78 (1) ◽  
pp. 687-714 ◽  
Author(s):  
Mohammad Reza Majma ◽  
Hossein Pedram ◽  
Mehdi Dehghan
2017 ◽  
Vol 25 (1) ◽  
pp. 241-253 ◽  
Author(s):  
Abdul Waheed Khan ◽  
Javed Iqbal Bangash ◽  
Adnan Ahmed ◽  
Abdul Hanan Abdullah

2015 ◽  
Vol 11 (2) ◽  
pp. 890348 ◽  
Author(s):  
Abdul Waheed Khan ◽  
Abdul Hanan Abdullah ◽  
Mohammad Abdur Razzaque ◽  
Javed Iqbal Bangash ◽  
Ayman Altameem

2007 ◽  
Vol 43 (4) ◽  
pp. 1539-1551 ◽  
Author(s):  
Nen-Chung Wang ◽  
Yung-Fa Huang ◽  
Jong-Shin Chen ◽  
Po-Chi Yeh

2018 ◽  
Vol 10 (1) ◽  
pp. 185-200
Author(s):  
Mohammad Sedighimanesh ◽  
Ali Sedighimanesh

Purpose – Clustering, routing, and data dissemination are an important issue in wireless sensor networks. The basic functions of wireless sensor networks are phenomena controlling in the physical environment, and the reporting of sensed data to the central node called sink, in which more operations can be done on the data. The most important limitation of wireless sensor networks is energy consumption. There are several ways to increase the lifetime of these networks, that one of the most important is the using proper clustering method. The aim of this study is to reduce energy consumption using an effective clustering algorithm and for this purpose, the honeybee colony metaheuristic method was used for cluster heads selection. Methodology/approach/design – The simulation in this paper was done using MATLAB software and the proposed method is compared with the LEACH and SEED approach. Findings – The results of simulations in this research indicate that the research has significantly reduced the energy consumption in the network than LEACH and SEED algorithms. Originality/value – Given the energy constraints in the wireless sensor network, providing such solutions and using metaheuristic algorithms can dramatically reduce energy consumption and, consequently increase network lifetime.


Author(s):  
Omar Busaileh ◽  
Ammar Hawbani ◽  
Xingfu Wang ◽  
Ping Liu ◽  
Liang Zhao ◽  
...  

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