Showing papers by "Mohamed Elhoseny published in 2015"
TL;DR: A Genetic Algorithm based method that optimizes heterogeneous sensor node clustering and greatly extends the network life, and the average improvement with respect to the second best performance based on the first-node-die and the last- node-die is 33.8% and 13%, respectively.
Abstract: In a heterogeneous Wireless Sensor Network (WSN), factors such as initial energy, data processing capability, etc greatly influence the network lifespan Despite the success of various clustering strategies of WSN, the numerous possible sensor clusters make searching for an optimal network structure an open challenge In this paper, we propose a Genetic Algorithm based method that optimizes heterogeneous sensor node clustering Compared with five state-of-the-art methods, our proposed method greatly extends the network life, and the average improvement with respect to the second best performance based on the first-node-die and the last-node-die is 338% and 13%, respectively The balanced energy consumption greatly improves the network life and allows the sensor energy to deplete evenly The computational efficiency of our method is comparable to the others and the overall average time across all experiments is 06 seconds with a standard deviation of 006
168 citations
TL;DR: The outcomes of patients with severe pneumonia who were admitted to the ICU were better than those of previous reports and early administration of combination antibiotics was practiced with vigilance.
13 citations