Abdulhakeem Amer A.
@nahrainuniv.edu.iq
Al-Nahrain University
College of Information Engineering
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Science, Multidisciplinary, Multidisciplinary, Multidisciplinary
Scopus Publications
Scopus Publications
Abdulhakeem A. Abdulameer and Raafat K. Oubida
AIP Publishing
Maha Ali Hussein, Lubna Emad Kadhim, and Abdulhakeem Amer Abdulameer
AIP Publishing
Sami Hasan and Abdulhakeem Amer
Iraqi Journal of Science University of Baghdad College of Science
Several remote sensor network (WSN) tasks require sensor information join. This in-processing Join is configured in parallel sensor hub to save battery power and limit the communication cost. Hence, a parallel join system is proposed for sensor networks. The proposed parallel join algorithm organizes in section-situated databases. A novel join method has been proposed for remote WSNs to limit the aggregate communication cost and enhance execution. This approach depends on two procedures; section-situated databases and parallel join algorithm utilized to store sensor information and speed up processing respectively. A segment arranged databases store information table in segmented shrewd. The Parallel-Joining WSN algorithm is effectively feasible for two clear reasons. Firstly, the decisive join conveyed fragments. Secondly, parallel-joining is in the fly processed sensor data. Creatively, a parallel dispersed algorithm has been developed to gain time compared to the single disseminated algorithm.
Sami Hasan and Abdulhakeem Amer
Iraqi Journal of Science University of Baghdad College of Science
The OSPF cost is proportionally indicated the transmitting packet overhead through a certain interface and inversely proportional to the interface bandwidth. Thus, this cost may minimized by direct packet transmitting to the other side via various probable paths simultaneously. Logically, the minimum weight path is the optimum path. This paper propose a novel Fuzzy Artificial Neural Network to create Smart Routing Protocol Algorithm. Consequently, the Fuzzy Artificial Neural Network Overlap has been reduced from (0.883 ms) to (0.602 ms) at fuzzy membership 1.5 to 4.5 respectively. This indicated the transmission time is two-fold faster than the standard overlapping time (1.3 ms).